WorldWideScience

Sample records for traffic congestion prediction

  1. Framework for Traffic Congestion Prediction

    NARCIS (Netherlands)

    Zaki, J.F.W.; Ali-Eldin, A.M.T.; Hussein, S.E.; Saraya, S.F.; Areed, F.F.

    2016-01-01

    Traffic Congestion is a complex dilemma facing most major cities. It has undergone a lot of research since the early 80s in an attempt to predict traffic in the short-term. Recently, Intelligent Transportation Systems (ITS) became an integral part of traffic research which helped in modeling and

  2. Framework for Traffic Congestion Management

    Directory of Open Access Journals (Sweden)

    Mahmud Hassan TALUKDAR

    2013-06-01

    Full Text Available Traffic Congestion is one of many serious global problems in all great cities resulted from rapid urbanization which always exert negative externalities upon society. The solution of traffic congestion is highly geocentric and due to its heterogeneous nature, curbing congestion is one of the hard tasks for transport planners. It is not possible to suggest unique traffic congestion management framework which could be absolutely applied for every great cities. Conversely, it is quite feasible to develop a framework which could be used with or without minor adjustment to deal with congestion problem. So, the main aim of this paper is to prepare a traffic congestion mitigation framework which will be useful for urban planners, transport planners, civil engineers, transport policy makers, congestion management researchers who are directly or indirectly involved or willing to involve in the task of traffic congestion management. Literature review is the main source of information of this study. In this paper, firstly, traffic congestion is defined on the theoretical point of view and then the causes of traffic congestion are briefly described. After describing the causes, common management measures, using world- wide, are described and framework for supply side and demand side congestion management measures are prepared.

  3. Rerouting algorithms solving the air traffic congestion

    Science.gov (United States)

    Adacher, Ludovica; Flamini, Marta; Romano, Elpidio

    2017-06-01

    Congestion in the air traffic network is a problem with an increasing relevance for airlines costs as well as airspace safety. One of the major issue is the limited operative capacity of the air network. In this work an Autonomous Agent approach is proposed to solve in real time the problem of air traffic congestion. The air traffic infrastructures are modeled with a graph and are considered partitioned in different sectors. Each sector has its own decision agent dealing with the air traffic control involved in it. Each agent sector imposes a real time aircraft scheduling to respect both delay and capacity constrains. When a congestion is predicted, a new aircraft scheduling is computed. Congestion is solved when the capacity constrains are satisfied once again. This can be done by delaying on ground aircraft or/and rerouting aircraft and/or postponing the congestion. We have tested two different algorithms that calculate K feasible paths for each aircraft involved in the congestion. Some results are reported on North Italian air space.

  4. An Efficient Traffic Congestion Monitoring System on Internet of Vehicles

    Directory of Open Access Journals (Sweden)

    Duc-Binh Nguyen

    2018-01-01

    Full Text Available Existing intelligent transport systems (ITS do not fully consider and resolve accuracy, instantaneity, and compatibility challenges while resolving traffic congestion in Internet of Vehicles (IoV environments. This paper proposes a traffic congestion monitoring system, which includes data collection, segmented structure establishment, traffic-flow modelling, local segment traffic congestion prediction, and origin-destination traffic congestion service for drivers. Macroscopic model-based traffic-flow factors were formalized on the basis of the analysis results. Fuzzy rules-based local segment traffic congestion prediction was performed to determine the traffic congestion state. To enhance prediction efficiency, this paper presents a verification process for minimizing false predictions which is based on the Rankine-Hugoniot condition and an origin-destination traffic congestion service is also provided. To verify the feasibility of the proposed system, a prototype was implemented. The experimental results demonstrate that the proposed scheme can effectively monitor traffic congestion in terms of accuracy and system response time.

  5. Joint QoS and Congestion Control Based on Traffic Prediction in SDN

    Directory of Open Access Journals (Sweden)

    Mohammad Mahdi Tajiki

    2017-12-01

    Full Text Available Due to the various network requirements of applications, quality of service (QoS-aware routing plays an important role in the networks. Recently proposed resource allocation algorithms focus on the current traffic matrix, which is not applicable for dynamic networks. In this paper, we exploit an estimation of flow matrix that gives our scheme the ability to sufficiently reduce the total packet loss and simultaneously raise the network throughput. In this way, we mathematically formulate the QoS-aware resource reallocation in software-defined networking (SDN networks based on the traffic prediction. To solve this optimization problem, two schemes are proposed: (i exact solution; and (ii fast suboptimal one. The proposed schemes are compared with the accuracy perspective. Moreover, the impact of prediction on resource reallocation is discussed. In this regard, it is shown that, compared with the conventional scheme, the proposed scheme decreases the packet loss and increases the throughput significantly.

  6. Road traffic congestion a concise guide

    CERN Document Server

    Falcocchio, John C

    2015-01-01

    This book on road traffic congestion in cities and suburbs describes congestion problems and shows how they can be relieved. The first part (Chapters 1 - 3) shows how congestion reflects transportation technologies and settlement patterns. The second part (Chapters 4 - 13) describes the causes, characteristics, and consequences of congestion. The third part (Chapters 14 - 23) presents various relief strategies - including supply adaptation and demand mitigation - for nonrecurring and recurring congestion. The last part (Chapter 24) gives general guidelines for congestion relief and provides a general outlook for the future. The book will be useful for a wide audience - including students, practitioners and researchers in a variety of professional endeavors: traffic engineers, transportation planners, public transport specialists, city planners, public administrators, and private enterprises that depend on transportation for their activities.  

  7. Making the Traffic Operations Case for Congestion Pricing: Operational Impacts of Congestion Pricing

    Energy Technology Data Exchange (ETDEWEB)

    Chin, Shih-Miao [ORNL; Hu, Patricia S [ORNL; Davidson, Diane [ORNL

    2011-02-01

    Congestion begins when an excess of vehicles on a segment of roadway at a given time, resulting in speeds that are significantly slower than normal or 'free flow' speeds. Congestion often means stop-and-go traffic. The transition occurs when vehicle density (the number of vehicles per mile in a lane) exceeds a critical level. Once traffic enters a state of congestion, recovery or time to return to a free-flow state is lengthy; and during the recovery process, delay continues to accumulate. The breakdown in speed and flow greatly impedes the efficient operation of the freeway system, resulting in economic, mobility, environmental and safety problems. Freeways are designed to function as access-controlled highways characterized by uninterrupted traffic flow so references to freeway performance relate primarily to the quality of traffic flow or traffic conditions as experienced by users of the freeway. The maximum flow or capacity of a freeway segment is reached while traffic is moving freely. As a result, freeways are most productive when they carry capacity flows at 60 mph, whereas lower speeds impose freeway delay, resulting in bottlenecks. Bottlenecks may be caused by physical disruptions, such as a reduced number of lanes, a change in grade, or an on-ramp with a short merge lane. This type of bottleneck occurs on a predictable or 'recurrent' basis at the same time of day and same day of week. Recurrent congestion totals 45% of congestion and is primarily from bottlenecks (40%) as well as inadequate signal timing (5%). Nonrecurring bottlenecks result from crashes, work zone disruptions, adverse weather conditions, and special events that create surges in demand and that account for over 55% of experienced congestion. Figure 1.1 shows that nonrecurring congestion is composed of traffic incidents (25%), severe weather (15%), work zones, (10%), and special events (5%). Between 1995 and 2005, the average percentage change in increased peak traveler

  8. Congestion transition in air traffic networks.

    Directory of Open Access Journals (Sweden)

    Bernardo Monechi

    Full Text Available Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.

  9. Congestion transition in air traffic networks.

    Science.gov (United States)

    Monechi, Bernardo; Servedio, Vito D P; Loreto, Vittorio

    2015-01-01

    Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.

  10. Towards Scalable Distributed Framework for Urban Congestion Traffic Patterns Warehousing

    Directory of Open Access Journals (Sweden)

    A. Boulmakoul

    2015-01-01

    Full Text Available We put forward architecture of a framework for integration of data from moving objects related to urban transportation network. Most of this research refers to the GPS outdoor geolocation technology and uses distributed cloud infrastructure with big data NoSQL database. A network of intelligent mobile sensors, distributed on urban network, produces congestion traffic patterns. Congestion predictions are based on extended simulation model. This model provides traffic indicators calculations, which fuse with the GPS data for allowing estimation of traffic states across the whole network. The discovery process of congestion patterns uses semantic trajectories metamodel given in our previous works. The challenge of the proposed solution is to store patterns of traffic, which aims to ensure the surveillance and intelligent real-time control network to reduce congestion and avoid its consequences. The fusion of real-time data from GPS-enabled smartphones integrated with those provided by existing traffic systems improves traffic congestion knowledge, as well as generating new information for a soft operational control and providing intelligent added value for transportation systems deployment.

  11. Traffic Congestion Evaluation and Signal Control Optimization Based on Wireless Sensor Networks: Model and Algorithms

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2012-01-01

    Full Text Available This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.

  12. Busy hour traffic congestion analysis in mobile macrocells | Ozovehe ...

    African Journals Online (AJOL)

    In this work, real live traffic data from integrated GSM/GPRS network was used for traffic congestion analysis. The analysis was carried out on 10 congesting cells using network management system (NMS) statistics data span for three years period. Correlation test showed that traffic channel (TCH) congestion depend only ...

  13. Research on Analysis Method of Traffic Congestion Mechanism Based on Improved Cell Transmission Model

    Directory of Open Access Journals (Sweden)

    Hongzhao Dong

    2012-01-01

    Full Text Available To analyze the spreading regularity of the initial traffic congestion, the improved cell transmission model (CTM is proposed to describe the evolution mechanism of traffic congestion in regional road grid. Ordinary cells and oriented cells are applied to render the crowd roads and their adjacent roads. Therefore the traffic flow could be simulated by these cells. Resorting to the proposed model, the duration of the initial traffic congestion could be predicted and the subsequent secondary congestion could be located. Accordingly, the spatial diffusion of traffic congestion could be estimated. At last, taking a road network region of Hangzhou city as an example, the simulation experiment is implemented to verify the proposed method by PARAMICS software. The result shows that the method could predict the duration of the initial congestion and estimate its spatial diffusion accurately.

  14. Management of Traffic Congestion in Urban Areas

    Directory of Open Access Journals (Sweden)

    Vilibald Premzl

    2012-10-01

    Full Text Available The use of road vehicles is increasing, the benefits they affordhave been progressively diminished by external costs.Whereas traffic increases as we approach the centre, the roadand open space decreases. The greater specialisation allows thecity growth in size and in traffic attraction. In this way urbangrowth feeds itself !mer-urban transp011 facilities also becomemore extensive. Growth in size of the city generates greateramounts of traffic and can eventually give rise to agglomerationdiseconomies. Higher transport costs, offices and shops, attractedby the accessibility of central locations, gradually replaceresidential uses, people being forced to seek housing inthe suburbs. As the urban area expands and offices in the citycentre are built denser and highe1; traffic congestion increases.This may result in the fall in centra/land values, since accessibilitydiminishes with the saturation of transport network. Increasedpollution takes various forms as noise, smoke andovercrowded housing in the centre, urban decay in the transitionalzone as commercial development is anticipated.

  15. The economic cost of traffic congestion in Florida.

    Science.gov (United States)

    2010-08-01

    Traffic congestion in the U.S. is bad and getting worse, and it is expensive. Appropriate solutions to this problem require appropriate information. A comprehensive and accurate analysis of congestion costs is a critical tool for planning and impleme...

  16. Green supply chain: Simulating road traffic congestion

    Science.gov (United States)

    Jalal, Muhammad Zulqarnain Hakim Abd; Nawawi, Mohd Kamal Mohd; Laailatul Hanim Mat Desa, Wan; Khalid, Ruzelan; Khalid Abduljabbar, Waleed; Ramli, Razamin

    2017-09-01

    With the increasing awareness of the consumers about environmental issues, businesses, households and governments increasingly want use green products and services which lead to green supply chain. This paper discusses a simulation study of a selected road traffic system that will contribute to the air pollution if in the congestion state. Road traffic congestion (RTC) can be caused by a temporary obstruction, a permanent capacity bottleneck in the network itself, and stochastic fluctuation in demand within a particular sector of the network, leading to spillback and queue propagation. A discrete-event simulation model is developed to represent the real traffic light control (TLC) system condition during peak hours. Certain performance measures such as average waiting time and queue length were measured using the simulation model. Existing system uses pre-set cycle time to control the light changes which is fixed time cycle. In this research, we test several other combination of pre-set cycle time with the objective to find the best system. In addition, we plan to use a combination of the pre-set cycle time and a proximity sensor which have the authority to manipulate the cycle time of the lights. The sensors work in such situation when the street seems to have less occupied vehicles, obviously it may not need a normal cycle for green light, and automatically change the cycle to street where vehicle is present.

  17. The impact of a congestion assistant on traffic flow efficiency and safety in congested traffic caused by a lane drop

    NARCIS (Netherlands)

    van Driel, Cornelie; van Arem, Bart

    2010-01-01

    This article presents the results of a microscopic traffic simulation study conducted to investigate the impact of a Congestion Assistant on traffic efficiency and traffic safety. The Congestion Assistant is an in-vehicle system in which an active pedal supports the driver when approaching

  18. Identifying the Onset of Congestion Rapidly with Existing Traffic Detectors

    OpenAIRE

    Coifman, Benjamin

    1999-01-01

    From an operations standpoint, the most important task of a traffic surveillance system is determining reliably whether the facility is free flowing or congested. The second most important task is responding rapidly when the facility becomes congested. Other tasks, such as quantifying the magnitude of congestion, are desirable, but tertiary. To address the first two tasks, this paper presents a new approach for traffic surveillance using existing detectors. Rather than expending a considerabl...

  19. A theory of traffic congestion at moving bottlenecks

    Energy Technology Data Exchange (ETDEWEB)

    Kerner, Boris S [Daimler AG, GR/PTF, HPC: G021, 71059 Sindelfingen (Germany); Klenov, Sergey L, E-mail: boris.kerner@daimler.co [Department of Physics, Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Moscow Region (Russian Federation)

    2010-10-22

    The physics of traffic congestion occurring at a moving bottleneck on a multi-lane road is revealed based on the numerical analyses of vehicular traffic with a discrete stochastic traffic flow model in the framework of three-phase traffic theory. We find that there is a critical speed of a moving bottleneck at which traffic breakdown, i.e. a first-order phase transition from free flow to synchronized flow, occurs spontaneously at the moving bottleneck, if the flow rate upstream of the bottleneck is great enough. The greater the flow rate, the higher the critical speed of the moving bottleneck. A diagram of congested traffic patterns at the moving bottleneck is found, which shows regions in the flow-rate-moving-bottleneck-speed plane in which congested patterns emerge spontaneously or can be induced through large enough disturbances in an initial free flow. A comparison of features of traffic breakdown and resulting congested patterns at the moving bottleneck with known ones at an on-ramp (and other motionless) bottleneck is made. Nonlinear features of complex interactions and transformations of congested traffic patterns occurring at on- and off-ramp bottlenecks due to the existence of the moving bottleneck are found. The physics of the phenomenon of traffic congestion due to 'elephant racing' on a multi-lane road is revealed.

  20. A theory of traffic congestion at moving bottlenecks

    International Nuclear Information System (INIS)

    Kerner, Boris S; Klenov, Sergey L

    2010-01-01

    The physics of traffic congestion occurring at a moving bottleneck on a multi-lane road is revealed based on the numerical analyses of vehicular traffic with a discrete stochastic traffic flow model in the framework of three-phase traffic theory. We find that there is a critical speed of a moving bottleneck at which traffic breakdown, i.e. a first-order phase transition from free flow to synchronized flow, occurs spontaneously at the moving bottleneck, if the flow rate upstream of the bottleneck is great enough. The greater the flow rate, the higher the critical speed of the moving bottleneck. A diagram of congested traffic patterns at the moving bottleneck is found, which shows regions in the flow-rate-moving-bottleneck-speed plane in which congested patterns emerge spontaneously or can be induced through large enough disturbances in an initial free flow. A comparison of features of traffic breakdown and resulting congested patterns at the moving bottleneck with known ones at an on-ramp (and other motionless) bottleneck is made. Nonlinear features of complex interactions and transformations of congested traffic patterns occurring at on- and off-ramp bottlenecks due to the existence of the moving bottleneck are found. The physics of the phenomenon of traffic congestion due to 'elephant racing' on a multi-lane road is revealed.

  1. Traffic Congestion Detection System through Connected Vehicles and Big Data.

    Science.gov (United States)

    Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo

    2016-04-28

    This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.

  2. How Congested Jakarta is? Perception of Jakarta’s Citizen on Traffic Congestion

    Directory of Open Access Journals (Sweden)

    Muhammad Halley Yudhistira

    2017-11-01

    Full Text Available This paper aims to reveal the behavior and perception of Jakarta’s citizens on traffic congestion in Jakarta. Although this approach is somewhat well-developed in behavioral science, its utilization in urban economics study, is still limited. Detecting the traffic congestion and its cause mainly relies on physical (engineering methods, i.e V/C ratio. Here, we define the traffic congestion through two variables; ordinal traffic congestion perception and proportion of expected travel time to perceived travel time. Using a non-probabilistic sampling survey held in one of densest business district in Jakarta called Sudirman-Thamrin Golden Triangle Area; the estimation results show that travel behavior plays a major role in affecting travel time perceptions.

  3. 434 Urban Traffic Congestion and Its Attendant Health Effects on ...

    African Journals Online (AJOL)

    User

    2010-10-17

    Oct 17, 2010 ... Keywords: Congestion, Effects, Health, Road Traffic, and Road Users. ..... of transport problems that can be identified are: bad roads, fuel problem (high fuel price .... Cities.www.ghanaweb.com/ghanahomepage/news archive.

  4. Exploring spatio-temporal patterns in traffic congestion data

    DEFF Research Database (Denmark)

    Kveladze, Irma; Agerholm, Niels; Reinau, Kristian Hegner

    2017-01-01

    An efficient infrastructure is essential for economic development. However, economic growth has been closely connected to the increasing road transport. This increases traffic congestions significantly, and road network gets near or at its capacity limits. Hence, congestion has become a central...

  5. Traffic Congestion Detection System through Connected Vehicles and Big Data

    OpenAIRE

    Néstor Cárdenas-Benítez; Raúl Aquino-Santos; Pedro Magaña-Espinoza; José Aguilar-Velazco; Arthur Edwards-Block; Aldo Medina Cass

    2016-01-01

    This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which ...

  6. A theory of traffic congestion at heavy bottlenecks

    Energy Technology Data Exchange (ETDEWEB)

    Kerner, Boris S [Daimler AG, GR/ETI, HPC: G021, 71059 Sindelfingen (Germany)

    2008-05-30

    Spatiotemporal features and physics of vehicular traffic congestion occurring due to heavy highway bottlenecks caused for example by bad weather conditions or accidents are found based on simulations in the framework of three-phase traffic theory. A model of a heavy bottleneck is presented. Under a continuous non-limited increase in bottleneck strength, i.e., when the average flow rate within a congested pattern allowed by the heavy bottleneck decreases continuously up to zero, the evolution of the traffic phases in congested traffic, synchronized flow and wide moving jams, is studied. It is found that at a small enough flow rate within the congested pattern, the pattern exhibits a non-regular structure: a pinch region of synchronized flow within the pattern disappears and appears randomly over time; wide moving jams upstream of the pinch region exhibit a complex non-regular dynamics in which the jams appear and disappear randomly. At greater bottleneck strengths, wide moving jams merge onto a mega-wide moving jam (mega-jam) within which low-speed patterns with a complex non-regular spatiotemporal dynamics occur. We show that when the bottleneck strength is great enough, only the mega-jam survives and synchronized flow remains only within its downstream front separating free flow and congested traffic. Theoretical results presented can explain why no sequence of wide moving jams can often be distinguished in non-homogeneous traffic congestion measured at very heavy bottlenecks caused by bad weather conditions or accidents.

  7. A theory of traffic congestion at heavy bottlenecks

    International Nuclear Information System (INIS)

    Kerner, Boris S

    2008-01-01

    Spatiotemporal features and physics of vehicular traffic congestion occurring due to heavy highway bottlenecks caused for example by bad weather conditions or accidents are found based on simulations in the framework of three-phase traffic theory. A model of a heavy bottleneck is presented. Under a continuous non-limited increase in bottleneck strength, i.e., when the average flow rate within a congested pattern allowed by the heavy bottleneck decreases continuously up to zero, the evolution of the traffic phases in congested traffic, synchronized flow and wide moving jams, is studied. It is found that at a small enough flow rate within the congested pattern, the pattern exhibits a non-regular structure: a pinch region of synchronized flow within the pattern disappears and appears randomly over time; wide moving jams upstream of the pinch region exhibit a complex non-regular dynamics in which the jams appear and disappear randomly. At greater bottleneck strengths, wide moving jams merge onto a mega-wide moving jam (mega-jam) within which low-speed patterns with a complex non-regular spatiotemporal dynamics occur. We show that when the bottleneck strength is great enough, only the mega-jam survives and synchronized flow remains only within its downstream front separating free flow and congested traffic. Theoretical results presented can explain why no sequence of wide moving jams can often be distinguished in non-homogeneous traffic congestion measured at very heavy bottlenecks caused by bad weather conditions or accidents

  8. Traffic Congestion Detection and Avoidance using Vehicular Communication

    Directory of Open Access Journals (Sweden)

    Ajay Narendrabhai Upadhyaya

    2015-01-01

    Full Text Available Traffic congestion is a serious problem in big cities. With the number of vehicles increasing rapidly, especially in cities whose economy is booming, the situation is getting even worse. Drivers, unaware of congestion ahead eventually join it and increase the severity of it. The ability of a driver to know the traffic conditions on the roads ahead enables him/her to seek alternate routes through which time and fuel can be saved. Due to recent advancements in vehicular technologies, vehicular communication has emerged. The objective of this work is to check feasibility of using infrastructure based vehicular communication for detecting and avoiding traffic congestion. In this paper we propose a Signal Agent (SA and Car Agent(CAbased approach for detecting and avoiding traffic congestion. We analyze performance of the proposed approach for two different road network scenarios using simulations: structured grid network (like Gandhinagar City of Gujarat, India and apart of typical city road network ( Tiwan city. With the proposed approach we get reduction of 10.05% in trip duration of vehicles, reduction of 10.08% in number of vehicles in entire traffic road network and 9.82% in heavy traffic area. In an accident scenario, about 72.63% vehicles changed their route due to awareness of congestion. Error in trip time estimation and vehicle count estimation is observed to be less than 1%.

  9. Modeling truck traffic volume growth congestion.

    Science.gov (United States)

    2009-05-01

    Modeling of the statewide transportation system is an important element in understanding issues and programming of funds to thwart potential congestion. As Alabama grows its manufacturing economy, the number of heavy vehicles traversing its highways ...

  10. Impact Analysis of Land Use on Traffic Congestion Using Real-Time Traffic and POI

    Directory of Open Access Journals (Sweden)

    Tianqi Zhang

    2017-01-01

    Full Text Available This paper proposed a new method to describe, compare, and classify the traffic congestion points in Beijing, China, by using the online map data and further revealed the relationship between traffic congestion and land use. The data of the point of interest (POI and the real-time traffic was extracted from an electronic map of the area in the fourth ring road of Beijing. The POIs were quantified based on the architectural area of the land use; the congestion points were identified based on real-time traffic. Then, the cluster analysis using the attributes of congestion time was conducted to identify the main traffic congestion areas. The result of a linear regression analysis between the congestion time and the land use showed that the influence of the high proportion of commercial land use on the traffic congestion was significant. Also, we considered five types of land use through performing a linear regression analysis between the congestion time and the ratio of four types of land use. The results showed that the reasonable ratio of land use types could efficiently reduce congestion time. This study makes contributions to the policy-making of urban land use.

  11. Traffic Congestion Detection System through Connected Vehicles and Big Data

    Directory of Open Access Journals (Sweden)

    Néstor Cárdenas-Benítez

    2016-04-01

    Full Text Available This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.

  12. Impact Analysis of Land Use on Traffic Congestion Using Real-Time Traffic and POI

    OpenAIRE

    Zhang, Tianqi; Sun, Lishan; Yao, Liya; Rong, Jian

    2017-01-01

    This paper proposed a new method to describe, compare, and classify the traffic congestion points in Beijing, China, by using the online map data and further revealed the relationship between traffic congestion and land use. The data of the point of interest (POI) and the real-time traffic was extracted from an electronic map of the area in the fourth ring road of Beijing. The POIs were quantified based on the architectural area of the land use; the congestion points were identified based on ...

  13. Congestion and communication in confined ant traffic

    Science.gov (United States)

    Gravish, Nick; Gold, Gregory; Zangwill, Andrew; Goodisman, Michael A. D.; Goldman, Daniel I.

    2014-03-01

    Many social animals move and communicate within confined spaces. In subterranean fire ants Solenopsis invicta, mobility within crowded nest tunnels is important for resource and information transport. Within confined tunnels, communication and traffic flow are at odds: trafficking ants communicate through tactile interactions while stopped, yet ants that stop to communicate impose physical obstacles on the traffic. We monitor the bi-directional flow of fire ant workers in laboratory tunnels of varied diameter D. The persistence time of communicating ant aggregations, τ, increases approximately linearly with the number of participating ants, n. The sensitivity of traffic flow increases as D decreases and diverges at a minimum diameter, Dc. A cellular automata model incorporating minimal traffic features--excluded volume and communication duration--reproduces features of the experiment. From the model we identify a competition between information transfer and the need to maintain jam-free traffic flow. We show that by balancing information transfer and traffic flow demands, an optimum group strategy exists which maximizes information throughput. We acknowledge funding from NSF PoLS #0957659 and #PHY-1205878.

  14. Determinants of Traffic Congestion in the Metropolis of Douala ...

    African Journals Online (AJOL)

    On the other hand, urban agglomeration used as a proxy for traffic congestion has a negative effect on urban growth and economic growth. Based on the above results, it is recommended that a remedial infrastructural development plan and a sustainable polycentric land use pattern with alternative efficient mode of public ...

  15. Modelling traffic congestion using queuing networks

    Indian Academy of Sciences (India)

    Flow-density curves; uninterrupted traffic; Jackson networks. ... ness - also suffer from a big handicap vis-a-vis the Indian scenario: most of these models do .... more well-known queuing network models and onsite data, a more exact Road Cell ...

  16. Research on Urban Road Traffic Congestion Charging Based on Sustainable Development

    Science.gov (United States)

    Ye, Sun

    Traffic congestion is a major problem which bothers our urban traffic sustainable development at present. Congestion charging is an effective measure to alleviate urban traffic congestion. The paper first probes into several key issues such as the goal, the pricing, the scope, the method and the redistribution of congestion charging from theoretical angle. Then it introduces congestion charging practice in Singapore and London and draws conclusion and suggestion that traffic congestion charging should take scientific plan, support of public, public transportation development as the premise.

  17. Research on Congestion Pricing in Multimode Traffic considering Delay and Emission

    Directory of Open Access Journals (Sweden)

    Hongna Dai

    2015-01-01

    Full Text Available Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.

  18. Alleviating Traffic Congestion in Manila, Appraisal of the Pasig Expressway

    OpenAIRE

    Glenn Jenkins; BAHER EL-HIFNAWI

    2002-01-01

    Travel in Metro Manila at present is characterized by high levels of congestion, slow travel speeds, long journey times and limited road capacity. The situation will be further exacerbated due to the expected growth in population and income and the subsequent increase in car ownership. Localized traffic management schemes are no longer sufficient to solve the problem. Solutions on the demand side curbing the demand for car ownership and use should be considered together with solutions on the ...

  19. Indirect Damage of Urban Flooding: Investigation of Flood-Induced Traffic Congestion Using Dynamic Modeling

    Directory of Open Access Journals (Sweden)

    Jingxuan Zhu

    2018-05-01

    Full Text Available In many countries, industrialization has led to rapid urbanization. Increased frequency of urban flooding is one consequence of the expansion of urban areas which can seriously affect the productivity and livelihoods of urban residents. Therefore, it is of vital importance to study the effects of rainfall and urban flooding on traffic congestion and driver behavior. In this study, a comprehensive method to analyze the influence of urban flooding on traffic congestion was developed. First, a flood simulation was conducted to predict the spatiotemporal distribution of flooding based on Storm Water Management Model (SWMM and TELAMAC-2D. Second, an agent-based model (ABM was used to simulate driver behavior during a period of urban flooding, and a car-following model was established. Finally, in order to study the mechanisms behind how urban flooding affects traffic congestion, the impact of flooding on urban traffic was investigated based on a case study of the urban area of Lishui, China, covering an area of 4.4 km2. It was found that for most events, two-hour rainfall has a certain impact on traffic congestion over a five-hour period, with the greatest impact during the hour following the cessation of the rain. Furthermore, the effects of rainfall with 10- and 20-year return periods were found to be similar and small, whereas the effects with a 50-year return period were obvious. Based on a combined analysis of hydrology and transportation, the proposed methods and conclusions could help to reduce traffic congestion during flood seasons, to facilitate early warning and risk management of urban flooding, and to assist users in making informed decisions regarding travel.

  20. Monitoring road traffic congestion using a macroscopic traffic model and a statistical monitoring scheme

    KAUST Repository

    Zeroual, Abdelhafid

    2017-08-19

    Monitoring vehicle traffic flow plays a central role in enhancing traffic management, transportation safety and cost savings. In this paper, we propose an innovative approach for detection of traffic congestion. Specifically, we combine the flexibility and simplicity of a piecewise switched linear (PWSL) macroscopic traffic model and the greater capacity of the exponentially-weighted moving average (EWMA) monitoring chart. Macroscopic models, which have few, easily calibrated parameters, are employed to describe a free traffic flow at the macroscopic level. Then, we apply the EWMA monitoring chart to the uncorrelated residuals obtained from the constructed PWSL model to detect congested situations. In this strategy, wavelet-based multiscale filtering of data has been used before the application of the EWMA scheme to improve further the robustness of this method to measurement noise and reduce the false alarms due to modeling errors. The performance of the PWSL-EWMA approach is successfully tested on traffic data from the three lane highway portion of the Interstate 210 (I-210) highway of the west of California and the four lane highway portion of the State Route 60 (SR60) highway from the east of California, provided by the Caltrans Performance Measurement System (PeMS). Results show the ability of the PWSL-EWMA approach to monitor vehicle traffic, confirming the promising application of this statistical tool to the supervision of traffic flow congestion.

  1. Monitoring road traffic congestion using a macroscopic traffic model and a statistical monitoring scheme

    KAUST Repository

    Zeroual, Abdelhafid; Harrou, Fouzi; Sun, Ying; Messai, Nadhir

    2017-01-01

    Monitoring vehicle traffic flow plays a central role in enhancing traffic management, transportation safety and cost savings. In this paper, we propose an innovative approach for detection of traffic congestion. Specifically, we combine the flexibility and simplicity of a piecewise switched linear (PWSL) macroscopic traffic model and the greater capacity of the exponentially-weighted moving average (EWMA) monitoring chart. Macroscopic models, which have few, easily calibrated parameters, are employed to describe a free traffic flow at the macroscopic level. Then, we apply the EWMA monitoring chart to the uncorrelated residuals obtained from the constructed PWSL model to detect congested situations. In this strategy, wavelet-based multiscale filtering of data has been used before the application of the EWMA scheme to improve further the robustness of this method to measurement noise and reduce the false alarms due to modeling errors. The performance of the PWSL-EWMA approach is successfully tested on traffic data from the three lane highway portion of the Interstate 210 (I-210) highway of the west of California and the four lane highway portion of the State Route 60 (SR60) highway from the east of California, provided by the Caltrans Performance Measurement System (PeMS). Results show the ability of the PWSL-EWMA approach to monitor vehicle traffic, confirming the promising application of this statistical tool to the supervision of traffic flow congestion.

  2. Dynamic Traffic Congestion Simulation and Dissipation Control Based on Traffic Flow Theory Model and Neural Network Data Calibration Algorithm

    Directory of Open Access Journals (Sweden)

    Li Wang

    2017-01-01

    Full Text Available Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole.

  3. Traffic congestion forecasting model for the INFORM System. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Azarm, A.; Mughabghab, S.; Stock, D.

    1995-05-01

    This report describes a computerized traffic forecasting model, developed by Brookhaven National Laboratory (BNL) for a portion of the Long Island INFORM Traffic Corridor. The model has gone through a testing phase, and currently is able to make accurate traffic predictions up to one hour forward in time. The model will eventually take on-line traffic data from the INFORM system roadway sensors and make projections as to future traffic patterns, thus allowing operators at the New York State Department of Transportation (D.O.T.) INFORM Traffic Management Center to more optimally manage traffic. It can also form the basis of a travel information system. The BNL computer model developed for this project is called ATOP for Advanced Traffic Occupancy Prediction. The various modules of the ATOP computer code are currently written in Fortran and run on PC computers (pentium machine) faster than real time for the section of the INFORM corridor under study. The following summarizes the various routines currently contained in the ATOP code: Statistical forecasting of traffic flow and occupancy using historical data for similar days and time (long term knowledge), and the recent information from the past hour (short term knowledge). Estimation of the empirical relationships between traffic flow and occupancy using long and short term information. Mechanistic interpolation using macroscopic traffic models and based on the traffic flow and occupancy forecasted (item-1), and the empirical relationships (item-2) for the specific highway configuration at the time of simulation (construction, lane closure, etc.). Statistical routine for detection and classification of anomalies and their impact on the highway capacity which are fed back to previous items.

  4. (GIS-T) application for traffic congestion analyses in the De

    African Journals Online (AJOL)

    generation known as the 'traditional stopwatch and traffic congestion registration ... transportation safety analysis, travel demand analysis, traffic monitoring and .... many transportation agencies use distance measuring instruments (DMIs) in their probe vehicles. ..... Spatial Implications of the Tuberculosis DOTS Strategy in.

  5. Probabilistic Predictions of Traffic Demand for En Route Sectors Based on Individual Flight Data

    Science.gov (United States)

    2010-01-01

    The Traffic Flow Management System (TFMS) predicts the demand for each sector, and traffic managers use these predictions to spot possible congestion and to take measures to prevent it. These predictions of sector demand, however, are currently made ...

  6. An efficient statistical-based approach for road traffic congestion monitoring

    KAUST Repository

    Abdelhafid, Zeroual

    2017-12-14

    In this paper, we propose an effective approach which has to detect traffic congestion. The detection strategy is based on the combinational use of piecewise switched linear traffic (PWSL) model with exponentially-weighted moving average (EWMA) chart. PWSL model describes traffic flow dynamics. Then, PWSL residuals are used as the input of EWMA chart to detect traffic congestions. The evaluation results of the developed approach using data from a portion of the I210-W highway in Califorina showed the efficiency of the PWSL-EWMA approach in in detecting traffic congestions.

  7. An efficient statistical-based approach for road traffic congestion monitoring

    KAUST Repository

    Abdelhafid, Zeroual; Harrou, Fouzi; Sun, Ying

    2017-01-01

    In this paper, we propose an effective approach which has to detect traffic congestion. The detection strategy is based on the combinational use of piecewise switched linear traffic (PWSL) model with exponentially-weighted moving average (EWMA) chart. PWSL model describes traffic flow dynamics. Then, PWSL residuals are used as the input of EWMA chart to detect traffic congestions. The evaluation results of the developed approach using data from a portion of the I210-W highway in Califorina showed the efficiency of the PWSL-EWMA approach in in detecting traffic congestions.

  8. Traffic Flow Prediction Using MI Algorithm and Considering Noisy and Data Loss Conditions: An Application to Minnesota Traffic Flow Prediction

    Directory of Open Access Journals (Sweden)

    Seyed Hadi Hosseini

    2014-10-01

    Full Text Available Traffic flow forecasting is useful for controlling traffic flow, traffic lights, and travel times. This study uses a multi-layer perceptron neural network and the mutual information (MI technique to forecast traffic flow and compares the prediction results with conventional traffic flow forecasting methods. The MI method is used to calculate the interdependency of historical traffic data and future traffic flow. In numerical case studies, the proposed traffic flow forecasting method was tested against data loss, changes in weather conditions, traffic congestion, and accidents. The outcomes were highly acceptable for all cases and showed the robustness of the proposed flow forecasting method.

  9. Vehicle Routing with Traffic Congestion and Drivers' Driving and Working Rules

    NARCIS (Netherlands)

    Kok, A.L.; Hans, Elias W.; Schutten, Johannes M.J.; Zijm, Willem H.M.

    2010-01-01

    For the intensively studied vehicle routing problem (VRP), two real-life restrictions have received only minor attention in the VRP-literature: traffic congestion and driving hours regulations. Traffic congestion causes late arrivals at customers and long travel times resulting in large transport

  10. Congestion Tolling for Mixed Urban Freight and Passenger Traffic

    Directory of Open Access Journals (Sweden)

    Xie Chaoda

    2017-01-01

    Full Text Available This paper investigates the welfare effects of optimal tolling on urban traffic congestion, in a bottleneck model, with mixed freight and passenger users. The users’ marginal utility of time is considered to be varying with time. Under both no-toll equilibrium and socially optimal tolling, the users are found to sort their arrival time according to the increasing rates of marginal utility at the destination. The optimal toll that maximizes social welfare does not change each user's indirect utilit y relative to the no-toll equilibrium, but completely removes the queue, which also removes the barrier of freight carriers to accept congestion pricing by relating their marginal utilities directly to the toll. When the toll is equally rebated, the proposed social optimal tolling is a Pareto improvement relative to the no-toll equilibrium. Those more productive users also suffer more in both no-toll equilibrium and optimal tolling, which indicates that a differentiated redistribution of toll revenues could be an incentive to improve productivity.

  11. Emergency medical service providers' experiences with traffic congestion.

    Science.gov (United States)

    Griffin, Russell; McGwin, Gerald

    2013-02-01

    The population's migration from urban to suburban areas has resulted in a more dispersed population and has increased traffic flow, possibly resulting in longer emergency response times. Although studies have examined the effect of response times on time to definitive care and survival, no study has addressed the possible causes of slowed response time from the point of view of emergency medical services (EMS) first responders. To assess the variables most commonly associated with increased emergency response time as described by the opinions and views of EMS first responders. A total of 500 surveys were sent to randomly selected individuals registered as first responders with the Alabama Department of Public Health, and 112 surveys were returned completed. The survey included questions regarding roadway design, response to emergency calls, in-vehicle technology aimed at decreasing travel time, and public education regarding emergency response. Respondents reported traveling on city streets most often during emergency calls, and encountering traffic more often on interstates and national highways. Traffic congestion, on average, resulted in nearly 10min extra response time. Most agreed that the most effective in-vehicle technology for reducing response time was a pre-emptive green light device; however, very few reported availability of this device in their emergency vehicles. Public education regarding how to react to approaching emergency vehicles was stated as having the greatest potential impact on reducing emergency response time. The results of the survey suggest that the best methods for reducing emergency response times are those that are easy to implement (e.g., public education). Copyright © 2013 Elsevier Inc. All rights reserved.

  12. Large-scale transportation network congestion evolution prediction using deep learning theory.

    Science.gov (United States)

    Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

    2015-01-01

    Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

  13. Large-scale transportation network congestion evolution prediction using deep learning theory.

    Directory of Open Access Journals (Sweden)

    Xiaolei Ma

    Full Text Available Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS and Internet of Things (IoT, transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

  14. Traffic congestion and blood pressure elevation: A comparative cross-sectional study in Lebanon.

    Science.gov (United States)

    Bou Samra, Patrick; El Tomb, Paul; Hosni, Mohammad; Kassem, Ahmad; Rizk, Robin; Shayya, Sami; Assaad, Sarah

    2017-12-01

    This comparative cross-sectional study examines the association between traffic congestion and elevation of systolic and/or diastolic blood pressure levels among a convenience sample of 310 drivers. Data collection took place during a gas station pause at a fixed time of day. Higher average systolic (142 vs 123 mm Hg) and diastolic (87 vs 78 mm Hg) blood pressures were detected among drivers exposed to traffic congestion compared with those who were not exposed (P<.001), while controlling for body mass index, age, sex, pack-year smoking, driving hours per week, and occupational driving. Moreover, among persons exposed to traffic congestion, longer exposure time was associated with higher systolic and diastolic blood pressures. Further studies are needed to better understand the mechanisms of the significant association between elevated blood pressure and traffic congestion. ©2017 Wiley Periodicals, Inc.

  15. Short paper: Distributed vehicular traffic congestion detection algorithm for urban environments

    OpenAIRE

    Milojevic, M.; Rakocevic, V.

    2013-01-01

    Vehicular traffic congestion is a well-known economic and social problem generating significant costs and safety challenges, and increasing pollution in the cities. Current intelligent transport systems and vehicular networking technologies rely heavily on the supporting network infrastructure which is still not widely available. This paper contributes towards the development of distributed and cooperative vehicular traffic congestion detection by proposing a new vehicle-to-vehicle (V2V) cong...

  16. Experienced travel time prediction for congested freeways

    OpenAIRE

    Yildirimoglu, Mehmet; Geroliminis, Nikolaos

    2013-01-01

    Travel time is an important performance measure for transportation systems, and dissemination of travel time information can help travelers make reliable travel decisions such as route choice or departure time. Since the traffic data collected in real time reflects the past or current conditions on the roadway, a predictive travel time methodology should be used to obtain the information to be disseminated. However, an important part of the literature either uses instantaneous travel time ass...

  17. A model of jam formation in congested traffic

    Science.gov (United States)

    Bunzarova, N. Zh; Pesheva, N. C.; Priezzhev, V. B.; Brankov, J. G.

    2017-12-01

    We study a model of irreversible jam formation in congested vehicular traffic on an open segment of a single-lane road. The vehicles obey a stochastic discrete-time dynamics which is a limiting case of the generalized Totally Asymmetric Simple Exclusion Process. Its characteristic features are: (a) the existing clusters of jammed cars cannot break into parts; (b) when the leading vehicle of a cluster hops to the right, the whole cluster follows it deterministically, and (c) any two clusters of vehicles, occupying consecutive positions on the chain, may become nearest-neighbors and merge irreversibly into a single cluster. The above dynamics was used in a one-dimensional model of irreversible aggregation by Bunzarova and Pesheva [Phys. Rev. E 95, 052105 (2017)]. The model has three stationary non-equilibrium phases, depending on the probabilities of injection (α), ejection (β), and hopping (p) of particles: a many-particle one, MP, a completely jammed phase CF, and a mixed MP+CF phase. An exact expression for the stationary probability P(1) of a completely jammed configuration in the mixed MP+CF phase is obtained. The gap distribution between neighboring clusters of jammed cars at large lengths L of the road is studied. Three regimes of evolution of the width of a single gap are found: (i) growing gaps with length of the order O(L) when β > p; (ii) shrinking gaps with length of the order O(1) when β < p; and (iii) critical gaps at β = p, of the order O(L 1/2). These results are supported by extensive Monte Carlo calculations.

  18. Temporal-Spatial Analysis of Traffic Congestion Based on Modified CTM

    Directory of Open Access Journals (Sweden)

    Chenglong Chu

    2015-01-01

    Full Text Available A modified cell transmission model (CTM is proposed to depict the temporal-spatial evolution of traffic congestion on urban freeways. Specifically, drivers’ adaptive behaviors and the corresponding influence on traffic flows are emphasized. Two piecewise linear regression models are proposed to describe the relationship of flow and density (occupancy. Several types of cellular connections are designed to depict urban rapid roads with on/off-ramps and junctions. Based on the data collected on freeway of Queen Elizabeth, Ontario, Canada, we show that the new model provides a relatively higher accuracy of temporal-spatial evolution of traffic congestions.

  19. Grid Mapping for Spatial Pattern Analyses of Recurrent Urban Traffic Congestion Based on Taxi GPS Sensing Data

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-03-01

    Full Text Available Traffic congestion is one of the most serious problems that impact urban transportation efficiency, especially in big cities. Identifying traffic congestion locations and occurring patterns is a prerequisite for urban transportation managers in order to take proper countermeasures for mitigating traffic congestion. In this study, the historical GPS sensing data of about 12,000 taxi floating cars in Beijing were used for pattern analyses of recurrent traffic congestion based on the grid mapping method. Through the use of ArcGIS software, 2D and 3D maps of the road network congestion were generated for traffic congestion pattern visualization. The study results showed that three types of traffic congestion patterns were identified, namely: point type, stemming from insufficient capacities at the nodes of the road network; line type, caused by high traffic demand or bottleneck issues in the road segments; and region type, resulting from multiple high-demand expressways merging and connecting to each other. The study illustrated that the proposed method would be effective for discovering traffic congestion locations and patterns and helpful for decision makers to take corresponding traffic engineering countermeasures in order to relieve the urban traffic congestion issues.

  20. Mendenhall Glacier Visitor Center vehicular and pedestrian traffic congestion study

    Science.gov (United States)

    2007-05-01

    The Mendenhall Glacier Visitor Center of Tongass National Forest in Juneau, Alaska is experiencing vehicular and pedestrian congestion. This study was initiated by the United States Forest Service, Alaska Region, in cooperation with Western Federal L...

  1. Intelligent Traffic Control System Implementation for Traffic Violation Control, Congestion Control and Stolen Vehicle Detection

    Directory of Open Access Journals (Sweden)

    Swarup Suresh Kulkarni

    2017-07-01

    Full Text Available Traffic is significant issue in our nation, particularly in urban ranges. Aftereffect of this, activity clog issue happens. Crisis vehicle like rescue vehicle, fire unit, squad cars confront bunches of issue to achieve their goal on account of congested driving conditions, coming about loss of human lives. To minimize this issue we approach new idea name as ”Traffic control framework for blockage control and stolen Vehicle location”. In this framework activity freedom done by transforming Red flag into Green flag. We demonstrate idea of what is called ”Green wave”. Alongside this, we distinguish stolen vehicle by utilizing extremely advantageous RFID innovation. In the event that stolen vehicle is been distinguished, the framework gives ready sign through ringer. Framework sends Message with the assistance of GSM to Police station. In this framework we Use diverse RFID labels for recognizing rescue vehicle, stolen Vehicles. On the off chance that Red flag is on and IR sensor is initiated, then framework gives ringer alarm to movement police. This is novel framework which encourage great answer for comprehend traffic clog.

  2. HOW TRAVEL DEMAND AFFECTS DETECTION OF NON-RECURRENT TRAFFIC CONGESTION ON URBAN ROAD NETWORKS

    Directory of Open Access Journals (Sweden)

    B. Anbaroglu

    2016-06-01

    Full Text Available Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpected delays may disrupt just-in-time delivery and manufacturing processes, which could lose them payment. Consequently, research on non-recurrent congestion detection on urban road networks has recently gained attention. By analysing large amounts of traffic data collected on a daily basis, traffic operation centres can improve their methods to detect non-recurrent congestion rapidly and then revise their existing plans to mitigate its effects. Space-time clusters of high link journey time estimates correspond to non-recurrent congestion events. Existing research, however, has not considered the effect of travel demand on the effectiveness of non-recurrent congestion detection methods. Therefore, this paper investigates how travel demand affects detection of non-recurrent traffic congestion detection on urban road networks. Travel demand has been classified into three categories as low, normal and high. The experiments are carried out on London’s urban road network, and the results demonstrate the necessity to adjust the relative importance of the component evaluation criteria depending on the travel demand level.

  3. Game theoretic analysis of congestion, safety and security networks, air traffic and emergency departments

    CERN Document Server

    Zhuang, Jun

    2015-01-01

    Maximizing reader insights into the roles of intelligent agents in networks, air traffic and emergency departments, this volume focuses on congestion in systems where safety and security are at stake, devoting special attention to applying game theoretic analysis of congestion to: protocols in wired and wireless networks; power generation, air transportation and emergency department overcrowding. Reviewing exhaustively the key recent research into the interactions between game theory, excessive crowding, and safety and security elements, this book establishes a new research angle by illustrating linkages between the different research approaches and serves to lay the foundations for subsequent analysis. Congestion (excessive crowding) is defined in this work as all kinds of flows; e.g., road/sea/air traffic, people, data, information, water, electricity, and organisms. Analyzing systems where congestion occurs – which may be in parallel, series, interlinked, or interdependent, with flows one way or both way...

  4. Impact of Incidents on Traffic Congestion in Dar es Salaam City

    Directory of Open Access Journals (Sweden)

    David Mfinanga

    2013-06-01

    Full Text Available Poorly managed traffic incidents have largely contributed to congestion and delay in the city of Dar es Salaam. A thorough understanding of travel delays caused by incidents is therefore essential for effective countermeasures against the increasing congestion. The method used to determine delays in this research is based on the deterministic queuing theory. Information on incidents was obtained from traffic surveys, traffic police and road users. Counting of the number of vehicles passing the incident location was done on incident and incident-free days. The cumulative traffic counts on incident and incident-free days were then calculated and used to plot the queuing diagram used to determine incident induced delay. This method turned out to be a useful tool for estimating incident induced delay in areas with less sophisticated equipment i.e. where there are no sensors, CCTV cameras, etc. The method provided good estimates of incident induced delay which may help planners and transportation officials in better understanding incident related congestion and in selecting more effective countermeasures against incident related traffic congestion in the city. It was found out that the effects of incidents were different for the different zones, types of incidents and the periods the incident occurred. In addition to the incident duration and the number of vehicles affected, the impact of incidents also depended on availability of alternative routes, number of lanes on the road, discipline of the driver in manoeuvring at incident location and traffic control at the scene.

  5. Containing air pollution and traffic congestion: Transport policy and the environment in Singapore

    Science.gov (United States)

    Chin, Anthony T. H.

    Land transportation remains one of the main contributors of noise and air pollution in urban areas. This is in addition to traffic congestion and accidents which result in the loss of productive activity. While there is a close relationship between traffic volumes and levels of noise and air pollution, transport authorities often assume that solving traffic congestion would reduce noise and air pollutant levels. Tight control over automobile ownership and use in Singapore has contributed in improving traffic flows, travel speeds and air quality. The adoption of internationally accepted standards on automobile emissions and gasoline have been effective in reducing air pollution from motor vehicles. Demand management measures have largely focused on controlling the source of traffic congestion, i.e. private automobile ownership and its use especially within the Central Business District during the day. This paper reviews and analyzes the effectiveness of two measures which are instrumental in controlling congestion and automobile ownership, i.e. road pricing and the vehicle quota scheme (VQS). While these measures have been successful in achieving desired objectives, it has also led to the spreading of traffic externalities to other roads in the network, loss in consumer welfare and rent seeking by automobile traders.

  6. Towards reducing traffic congestion using cooperative adaptive cruise control on a freeway with a ramp

    Directory of Open Access Journals (Sweden)

    Georges Arnaout

    2011-12-01

    Full Text Available Purpose: In this paper, the impact of Cooperative Adaptive Cruise Control (CACC systems on traffic performance is examined using microscopic agent-based simulation. Using a developed traffic simulation model of a freeway with an on-ramp - created to induce perturbations and to trigger stop-and-go traffic, the CACC system’s effect on the traffic performance is studied. The previously proposed traffic simulation model is extended and validated. By embedding CACC vehicles in different penetration levels, the results show significance and indicate the potential of CACC systems to improve traffic characteristics and therefore can be used to reduce traffic congestion. The study shows that the impact of CACC is positive but is highly dependent on the CACC market penetration. The flow rate of the traffic using CACC is proportional to the market penetration rate of CACC equipped vehicles and the density of the traffic.Design/methodology/approach: This paper uses microscopic simulation experiments followed by a quantitative statistical analysis. Simulation enables researchers manipulating the system variables to straightforwardly predict the outcome on the overall system, giving researchers the unique opportunity to interfere and make improvements to performance. Thus with simulation, changes to variables that might require excessive time, or be unfeasible to carry on real systems, are often completed within seconds.Findings: The findings of this paper are summarized as follow:•\tProvide and validate a platform (agent-based microscopic traffic simulator in which any CACC algorithm (current or future may be evaluated.•\tProvide detailed analysis associated with implementation of CACC vehicles on freeways.•\tInvestigate whether embedding CACC vehicles on freeways has a significant positive impact or not.Research limitations/implications: The main limitation of this research is that it has been conducted solely in a computer laboratory. Laboratory

  7. Traffic conflict assessment for non-lane-based movements of motorcycles under congested conditions

    Directory of Open Access Journals (Sweden)

    Long Xuan Nguyen

    2014-03-01

    Full Text Available Traffic conflict under congested conditions is one of the main safety issues of motorcycle traffic in developing countries. Unlike cars, motorcycles often display non-lane-based movements such as swerving or oblique following of a lead vehicle when traffic becomes congested. Very few studies have quantitatively evaluated the effects of such non-lane-based movements on traffic conflict. Therefore, in this study we aim to develop an integrated model to assess the traffic conflict of motorcycles under congested conditions. The proposed model includes a concept of safety space to describe the non-lane-based movements unique to motorcycles, new features developed for traffic conflict assessment such as parameters of acceleration and deceleration, and the conditions for choosing a lead vehicle. Calibration data were extracted from video clips taken at two road segments in Ho Chi Minh City. A simulation based on the model was developed to verify the dynamic non-lane-based movements of motorcycles. Subsequently, the assessment of traffic conflict was validated by calculating the probability of sudden braking at each time interval according to the change in the density of motorcycle flow. Our findings underscore the fact that higher flow density may lead to conflicts associated with a greater probability of sudden breaking. Three types of motorcycle traffic conflicts were confirmed, and the proportions of each type were calculated and discussed.

  8. Communication efficiency and congestion of signal traffic in large-scale brain networks.

    Science.gov (United States)

    Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R

    2014-01-01

    The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.

  9. Launching automated rotary parking system: Towards traffic congestion free Dhaka city

    Science.gov (United States)

    Islam, Mohummad Shariful; Tithi, Afshana Morshed; Hossain, Farzad; Shetu, Rifat Sultana; Amin, S. M. Abdullah Al; Chowdhury, Shakia Zannatul Ferdous

    2017-12-01

    Bangladesh is the most densely populated city in the whole world, which is visible more in the capital city Dhaka. People have to suffer and valuable times are being wasted for this chronic quandary. Lack of proper planning of the city, different speed vehicles on the same road, over population, inadequate road space, unplanned stoppage or parking etc. are responsible for causing the traffic congestion in Dhaka City. Among those insufficient/unplanned parking system is one of the main reasons for causing traffic congestion. The automated rotary car parking system is the best and suitable because of its less utilization of space compared to other systems. It is a friendly parking system due to the non-utilization of noise/pollution related mechanism. The aim of this paper is to develop an automated car parking system with a minimum cost for reducing congestion in Dhaka city.

  10. Game theoretic analysis of congestion, safety and security traffic and transportation theory

    CERN Document Server

    Zhuang, Jun

    2015-01-01

    Maximizing reader insights into the interactions between game theory, excessive crowding and safety and security elements in traffic and transportation theory, this book establishes a new research angle by illustrating linkages between different research approaches and through laying the foundations for subsequent analysis. Congestion (excessive crowding) is defined in this work as all kinds of flows; e.g., road/sea/air traffic, people, data, information, water, electricity, and organisms. Analyzing systems where congestion occurs – which may be in parallel, series, interlinked, or interdependent, with flows one way or both ways – this book puts forward new congestion models, breaking new ground by introducing game theory and safety/security. Addressing the multiple actors who may hold different concerns regarding system reliability; e.g. one or several terrorists, a government, various local or regional government agencies, or others with stakes for or against system reliability, this book describes how ...

  11. Congestion Control and Traffic Scheduling for Collaborative Crowdsourcing in SDN Enabled Mobile Wireless Networks

    Directory of Open Access Journals (Sweden)

    Dawei Shen

    2018-01-01

    Full Text Available Currently, a number of crowdsourcing-based mobile applications have been implemented in mobile networks and Internet of Things (IoT, targeted at real-time services and recommendation. The frequent information exchanges and data transmissions in collaborative crowdsourcing are heavily injected into the current communication networks, which poses great challenges for Mobile Wireless Networks (MWN. This paper focuses on the traffic scheduling and load balancing problem in software-defined MWN and designs a hybrid routing forwarding scheme as well as a congestion control algorithm to achieve the feasible solution. The traffic scheduling algorithm first sorts the tasks in an ascending order depending on the amount of tasks and then solves it using a greedy scheme. In the proposed congestion control scheme, the traffic assignment is first transformed into a multiknapsack problem, and then the Artificial Fish Swarm Algorithm (AFSA is utilized to solve this problem. Numerical results on practical network topology reveal that, compared with the traditional schemes, the proposed congestion control and traffic scheduling schemes can achieve load balancing, reduce the probability of network congestion, and improve the network throughput.

  12. A Systems Dynamics Approach to Explore Traffic Congestion and Air Pollution Link in the City of Accra, Ghana

    Directory of Open Access Journals (Sweden)

    Alex A. N. M. Pappoe

    2010-01-01

    Full Text Available Economic development and urbanization poses myriad challenges to transportation systems in relation to negative externalities such as traffic congestion and environmental health risks. Accra, the capital of Ghana, faces mounting urban planning problems, for example traffic congestion, air pollution, traffic safety, and land use planning, among others. The paper aims to provide a system dynamics perspective of the problems. Most of the drivers and cause-effect relationships of traffic congestion and its attendant air pollution are investigated and analyzed using causal loop diagrams. The paper further suggests mechanisms by which the negative externalities associated with road transport in the city of Accra can be addressed.

  13. Road Traffic Congestion Management Based on a Search-Allocation Approach

    Directory of Open Access Journals (Sweden)

    Raiyn Jamal

    2017-03-01

    Full Text Available This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA. An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT technologies.

  14. Modelling CO concentrations under free-flowing and congested traffic conditions in Ireland

    Energy Technology Data Exchange (ETDEWEB)

    Broderick, B; Budd, U; Misstear, B [Dept. of Civil, Structural and Environmental Engineering, Trinity Coll. Dublin (Ireland); Ceburnis, D; Jennings, S G [Dept. of Experimental Physics, National Univ. of Ireland, Galway (Ireland)

    2004-07-01

    The assessment and management of air quality is required under the EU Air Quality Framework Directive and its Daughter Directives (CEC, 1996, 1999, 2000) which specify the limits for certain pollutants, including carbon monoxide (CO). Air quality modelling is used to predict the future impact of road improvements, often as part of an Environmental Impact Assessment. The U.S. National Commission on Air Quality found in 1981 that such models may typically overpredict or underpredict actual concentrations by a factor of two. Even twenty years later the U.K. Department of the Environment Transport and the Regions (UK DETR, 2001) concurred that ''If the prediction of an annual mean concentration lies within {+-}50% of the measurement, a user would not consider that the model has behaved badly.'' The Daughter Directive (CEC, 2000) concerned with CO allows 50% uncertainty in modelling of the eight-hour average concentration. An assessment of CALINE4 was performed for two contrasting sites: a free-flowing motorway and a periodically-congested roundabout. Air quality was continuously monitored over a one-year period at both sites. The data collected was compared with model predictions based on local and regional meteorological data, site geometry and traffic volumes. The modelled and monitored results were compared through both graphical and statistical analysis (Broderick B.M. et al., 2003). (orig.)

  15. Real Driving Emissions in Congested Traffic: A Comparison of Cold and Hot Start

    OpenAIRE

    Khalfan, A; Andrews, GE; Li, H

    2016-01-01

    Air quality NO₂ and PM exceedances in cities are common, where congested traffic occurs and the monitoring station is at the roadside. This work investigated real world emissions for a Euro 4 SI vehicle on a congested road by a roadside air quality monitoring station that exceeds European air quality standards for NOx and PM. The PEMS used was the Temet FTIR with Horiba OBS pitot tube exhaust mass flow sensor and gas sampler. Twenty nine hot start repeat journeys were made at different times ...

  16. The conscious city II: traffic congestion and the tipping point in greater Vancouver

    OpenAIRE

    Holt, Rebecca

    2007-01-01

    The Conscious City II explores how broad, long-term change toward sustainability in cities can be fostered, nurtured and facilitated. Using a qualitative, mixed-method approach, this research adapts a model from Malcolm Gladwell’s Tipping Point framework to explore how social consciousness can be mobilized to achieve change toward sustainability through an analysis of traffic congestion in Greater Vancouver. The results demonstrate the important influence of leadership, context and message on...

  17. Evaluating Environmental Impact of Traffic Congestion in Real Time Based on Sparse Mobile Crowd-sourced Data

    Science.gov (United States)

    2018-02-02

    Traffic congestion at arterial intersections and freeway bottlenecks degrades the air quality and threatens the public health. Conventionally, air pollutants are monitored by sparsely-distributed Quality Assurance Air Monitoring Sites. Sparse mobile ...

  18. Reducing Traffic Congestions by Introducing CACC-Vehicles on a Multi-Lane Highway Using Agent-Based Approach

    Science.gov (United States)

    Arnaout, Georges M.; Bowling, Shannon R.

    2011-01-01

    Traffic congestion is an ongoing problem of great interest to researchers from different areas in academia. With the emerging technology for inter-vehicle communication, vehicles have the ability to exchange information with predecessors by wireless communication. In this paper, we present an agent-based model of traffic congestion and examine the impact of having CACC (Cooperative Adaptive Cruise Control) embedded vehicle(s) on a highway system consisting of 4 traffic lanes without overtaking. In our model, CACC vehicles adapt their acceleration/deceleration according to vehicle-to-vehicle inter-communication. We analyze the average speed of the cars, the shockwaves, and the evolution of traffic congestion throughout the lifecycle of the model. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce the oscillatory behavior (stop and go) resulting from the acceleration/deceleration of the vehicles.

  19. Highly Dynamic and Adaptive Traffic Congestion Avoidance in Real-Time Inspired by Honey Bee Behavior

    Science.gov (United States)

    Wedde, Horst F.; Lehnhoff, Sebastian; van Bonn, Bernhard; Bay, Z.; Becker, S.; Böttcher, S.; Brunner, C.; Büscher, A.; Fürst, T.; Lazarescu, A. M.; Rotaru, E.; Senge, S.; Steinbach, B.; Yilmaz, F.; Zimmermann, T.

    Traffic congestions have become a major problem in metropolitan areas world-wide, within and between cities, to an extent where they make driving and transportation times largely unpredictable. Due to the highly dynamic character of congestion building and dissolving this phenomenon appears even to resist a formal treatment. Static approaches, and even more their global management, have proven counterproductive in practice. Given the latest progress in VANET technology and the remarkable commercially driven efforts like in the European C2C consortium, or the VSC Project in the US, allow meanwhile to tackle various aspects of traffic regulation through VANET communication. In this paper we introduce a novel, completely decentralized multi-agent routing algorithm (termed BeeJamA) which we have derived from the foraging behavior of honey bees. It is highly dynamic, adaptive, robust, and scalable, and it allows for both avoiding congestions, and minimizing traveling times to individual destinations. Vehicle guidance is provided well ahead of every intersection, depending on the individual speeds. Thus strict deadlines are imposed on, and respected by, the BeeJamA algorithm. We report on extensive simulation experiments which show the superior performance of BeeJamA over conventional approaches.

  20. Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation.

    Science.gov (United States)

    Son, Sanghyun; Baek, Yunju

    2015-08-18

    As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

  1. Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation

    Directory of Open Access Journals (Sweden)

    Sanghyun Son

    2015-08-01

    Full Text Available As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

  2. Vehicular Traffic Optimization in VANETs: a Proposal for Nodes Re-routing and Congestion Reduction

    Directory of Open Access Journals (Sweden)

    Mauro Tropea

    2015-01-01

    Full Text Available Recently, vehicular networking has grown up in terms of interest and transmission capability, due to the possibility of exploiting the distributed communication paradigm in a mobile scenario, where moving nodes are represented by vehicles. In this paper, we focus our attention on the optimization of traffic flowing in a vehicular environment with vehicle-roadside capability. As shown in the next sections, the proposed idea exploits the information that is gathered by road-side units with the main aim of redirecting traffic flows (in terms of vehicles to less congested roads, with an overall system optimization, also in terms of Carbon Dioxide emissions reduction. A deep campaign of simulations has been carried out to give more effectiveness to our proposal.

  3. Time allocation shifts and pollutant exposure due to traffic congestion: an analysis using the national human activity pattern survey.

    Science.gov (United States)

    Zhang, Kai; Batterman, Stuart A

    2009-10-15

    Traffic congestion increases air pollutant exposures of commuters and urban populations due to the increased time spent in traffic and the increased vehicular emissions that occur in congestion, especially "stop-and-go" traffic. Increased time in traffic also decreases time in other microenvironments, a trade-off that has not been considered in previous time activity pattern (TAP) analyses conducted for exposure assessment purposes. This research investigates changes in time allocations and exposures that result from traffic congestion. Time shifts were derived using data from the National Human Activity Pattern Survey (NHAPS), which was aggregated to nine microenvironments (six indoor locations, two outdoor locations and one transport location). After imputing missing values, handling outliers, and conducting other quality checks, these data were stratified by respondent age, employment status and period (weekday/weekend). Trade-offs or time-shift coefficients between time spent in vehicles and the eight other microenvironments were then estimated using robust regression. For children and retirees, congestion primarily reduced the time spent at home; for older children and working adults, congestion shifted the time spent at home as well as time in schools, public buildings, and other indoor environments. Changes in benzene and PM(2.5) exposure were estimated for the current average travel delay in the U.S. (9 min day(-1)) and other scenarios using the estimated time shifts coefficients, concentrations in key microenvironments derived from the literature, and a probabilistic analysis. Changes in exposures depended on the duration of the congestion and the pollutant. For example, a 30 min day(-1) travel delay was determined to account for 21+/-12% of current exposure to benzene and 14+/-8% of PM(2.5) exposure. The time allocation shifts and the dynamic approach to TAPs improve estimates of exposure impacts from congestion and other recurring events.

  4. Transport growth in Bangkok: Energy, environment, and traffic congestion. Workshop proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Philpott, J. [Asia Regional Office, Bangkok (Thailand)

    1995-07-01

    Bangkok, the capital of Thailand, is a physically and economically complexcity with a complicated transport system. With daily traffic congestion averaging 16 hours, the air quality is such that to breathe street level pollution for 8 eight hours is roughly equivalent to smoking nine cigarettes per day. Estimates suggest idling traffic costs up to $1.6 billion annually. Energy use within the transport sector is on a steady rise with an estimated increase in 11 years of two and one half times. Severe health impacts have begun to effect many residents - young children and the elderly being particularly vulnerable. Bangkok`s air quality and congestion problems are far from hopeless. Great potential exists for Bangkok to remedy its transport-related problems. The city has many necessary characteristics that allow an efficient, economical system of transport. For example, its high density level makes the city a prime candidate for an efficient system of mass transit and the multitude and close proximity of shops, street vendors, restaurants, and residential areas is highly conducive to walking and cycling. Technical knowledge and capacity to devise and implement innovative policies and projects to address air quality and congestion problems is plentiful. There is also consensus among Bangkokians that something needs to be done immediately to clear the air and the roads. However, little has been done. This report proposes a new approach to transport planning for Bangkok that integrates consideration of ecological, social, and financial viability in the process of making decisions regarding managing existing infrastructure and investments in new infrastructure. Selected papers have been indexed separately for inclusion in the Energy Science and Technology Database.

  5. Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study.

    Science.gov (United States)

    Cole, Justin; Beare, Richard; Phan, Thanh G; Srikanth, Velandai; MacIsaac, Andrew; Tan, Christianne; Tong, David; Yee, Susan; Ho, Jesslyn; Layland, Jamie

    2017-01-01

    Recent evidence suggests hospitals fail to meet guideline specified time to percutaneous coronary intervention (PCI) for a proportion of ST elevation myocardial infarction (STEMI) presentations. Implicit in achieving this time is the rapid assembly of crucial catheter laboratory staff. As a proof-of-concept, we set out to create regional maps that graphically show the impact of traffic congestion and distance to destination on staff recall travel times for STEMI, thereby producing a resource that could be used by staff to improve reperfusion time for STEMI. Travel times for staff recalled to one inner and one outer metropolitan hospital at midnight, 6 p.m., and 7 a.m. were estimated using Google Maps Application Programming Interface. Computer modeling predictions were overlaid on metropolitan maps showing color coded staff recall travel times for STEMI, occurring within non-peak and peak hour traffic congestion times. Inner metropolitan hospital staff recall travel times were more affected by traffic congestion compared with outer metropolitan times, and the latter was more affected by distance. The estimated mean travel times to hospital during peak hour were greater than midnight travel times by 13.4 min to the inner and 6.0 min to the outer metropolitan hospital at 6 p.m. ( p  travel time can predict optimal residence of staff when on-call for PCI.

  6. Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles.

    Science.gov (United States)

    Wan, Jiafu; Liu, Jianqi; Shao, Zehui; Vasilakos, Athanasios V; Imran, Muhammad; Zhou, Keliang

    2016-01-11

    The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction.

  7. Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles

    Directory of Open Access Journals (Sweden)

    Jiafu Wan

    2016-01-01

    Full Text Available The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I and Vehicle to Vehicle (V2V communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction.

  8. Hybrid Electromagnetism-Like Algorithm for Dynamic Supply Chain Network Design under Traffic Congestion and Uncertainty

    Directory of Open Access Journals (Sweden)

    Javid Jouzdani

    2016-01-01

    Full Text Available With the constantly increasing pressure of the competitive environment, supply chain (SC decision makers are forced to consider several aspects of business climate. More specifically, they should take into account the endogenous features (e.g., available means of transportation, and the variety of products and exogenous criteria (e.g., the environmental uncertainty, and transportation system conditions. In this paper, a mixed integer nonlinear programming (MINLP model for dynamic design of a supply chain network is proposed. In this model, multiple products and multiple transportation modes, the time value of money, traffic congestion, and both supply-side and demand-side uncertainties are considered. Due to the complexity of such models, conventional solution methods are not applicable; therefore, two hybrid Electromagnetism-Like Algorithms (EMA are designed and discussed for tackling the problem. The numerical results show the applicability of the proposed model and the capabilities of the solution approaches to the MINLP problem.

  9. Predicting Information Flows in Network Traffic.

    Science.gov (United States)

    Hinich, Melvin J.; Molyneux, Robert E.

    2003-01-01

    Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)

  10. Congestion Prediction Modeling for Quality of Service Improvement in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ga-Won Lee

    2014-04-01

    Full Text Available Information technology (IT is pushing ahead with drastic reforms of modern life for improvement of human welfare. Objects constitute “Information Networks” through smart, self-regulated information gathering that also recognizes and controls current information states in Wireless Sensor Networks (WSNs. Information observed from sensor networks in real-time is used to increase quality of life (QoL in various industries and daily life. One of the key challenges of the WSNs is how to achieve lossless data transmission. Although nowadays sensor nodes have enhanced capacities, it is hard to assure lossless and reliable end-to-end data transmission in WSNs due to the unstable wireless links and low hard ware resources to satisfy high quality of service (QoS requirements. We propose a node and path traffic prediction model to predict and minimize the congestion. This solution includes prediction of packet generation due to network congestion from both periodic and event data generation. Simulation using NS-2 and Matlab is used to demonstrate the effectiveness of the proposed solution.

  11. Reducing a congestion with introduce the greedy algorithm on traffic light control

    Science.gov (United States)

    Catur Siswipraptini, Puji; Hendro Martono, Wisnu; Hartanti, Dian

    2018-03-01

    The density of vehicles causes congestion seen at every junction in the city of jakarta due to the static or manual traffic timing lamp system consequently the length of the queue at the junction is uncertain. The research has been aimed at designing a sensor based traffic system based on the queue length detection of the vehicle to optimize the duration of the green light. In detecting the length of the queue of vehicles using infrared sensor assistance placed in each intersection path, then apply Greedy algorithm to help accelerate the movement of green light duration for the path that requires, while to apply the traffic lights regulation program based on greedy algorithm which is then stored on microcontroller with Arduino Mega 2560 type. Where a developed system implements the greedy algorithm with the help of the infrared sensor it will extend the duration of the green light on the long vehicle queue and accelerate the duration of the green light at the intersection that has the queue not too dense. Furthermore, the design is made to form an artificial form of the actual situation of the scale model or simple simulator (next we just called as scale model of simulator) of the intersection then tested. Sensors used are infrared sensors, where the placement of sensors in each intersection on the scale model is placed within 10 cm of each sensor and serves as a queue detector. From the results of the test process on the scale model with a longer queue obtained longer green light time so it will fix the problem of long queue of vehicles. Using greedy algorithms can add long green lights for 2 seconds on tracks that have long queues at least three sensor levels and accelerate time at other intersections that have longer queue sensor levels less than level three.

  12. Discovering urban mobility patterns with PageRank based traffic modeling and prediction

    Science.gov (United States)

    Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

    2017-11-01

    Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.

  13. Heterogeneity Index for the Assessment of Relationship Between Land Use Pattern and Road Traffic Congestion in Apapa-Oworoshoki Express way, Lagos Metropolis

    Science.gov (United States)

    Alaigba, D. B.; Soumah, M.; Banjo, M. O.

    2017-05-01

    The problem of urban mobility is complicated by traffic delay, resulting from poor planning, high population density and poor condition of roads within urban spaces. This study assessed traffic congestion resulting from differential contribution made by various land-uses along Apapa-Oworoshoki expressway in Lagos metropolis. The data for this study was from both primary and secondary sources; GPS point data was collected at selected points for traffic volume count; observation of the nature of vehicular traffic congestion, and land use types along the corridor. Existing data on traffic count along the corridor, connectivity map and land use map sourced from relevant authorities were acquired. Traffic congestion within the area was estimated using volume capacity ratio (V/C). Heterogeneity Index was developed and used to quantify the percentage contribution to traffic volume from various land-use categories. Analytical Hierarchical Processing (AHP) and knowledge-based weighting were used to rank the importance of different heterogeneity indices. Results showed significant relationship between the degree of heterogeneity of the land use pattern and road traffic congestion. Volume Capacity Ratio computed revealed that the route corridor exceeds its designed capacity in the southward direction between the hours of 8am and 12pm on working days. Five major nodes were analyzed along the corridor, and were all above the expected Passenger Car Unit (PCU), these are "Oshodi" 15 %, "Airport junction" 10 %, "Cele bus stop" 21 %, "Mile 2" 14 %, "Berger" 15 % and "Tincan bus stop" 33 % indicating heavy traffic congestion.

  14. Defending and attacking a network of two arcs subject to traffic congestion

    International Nuclear Information System (INIS)

    Bier, Vicki M.; Hausken, Kjell

    2013-01-01

    To study the effects of intentional attacks on transportation systems, we consider drivers who choose the more time-efficient of two arcs (possibly of different lengths). Both arcs are subjected to traffic congestion, and also to interdiction or blockage (e.g., by a terrorist attack). The model has three types of strategic actors: the government; the terrorist; and potential drivers. The government protects travel, while the terrorist interdicts travel, along the two arcs. Drivers choose the arc that gives the shortest travel time, and cannot choose an interdicted arc. The drivers have reservation travel times, such that if the actual travel time will exceed an individual driver's reservation travel time, that driver would prefer not to travel; the reservation travel times are allowed to vary among drivers. The objective function of the master problem, which the government minimizes and the terrorist maximizes, is the sum of the total travel time plus the reservation travel times of the non-travelers. Each potential driver decides endogenously whether to travel, according to whether the actual travel time is greater or lesser than that driver's reservation travel time

  15. Increasing Intelligence in Inter-Vehicle Communications to Reduce Traffic Congestions: Experiments in Urban and Highway Environments.

    Directory of Open Access Journals (Sweden)

    Rodolfo I Meneguette

    Full Text Available Intelligent Transportation Systems (ITS rely on Inter-Vehicle Communication (IVC to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services for passengers. Traffic congestion is an urban mobility problem, which causes stress to drivers and economic losses. In this context, this work proposes a solution for the detection, dissemination and control of congested roads based on inter-vehicle communication, called INCIDEnT. The main goal of the proposed solution is to reduce the average trip time, CO emissions and fuel consumption by allowing motorists to avoid congested roads. The simulation results show that our proposed solution leads to short delays and a low overhead. Moreover, it is efficient with regard to the coverage of the event and the distance to which the information can be propagated. The findings of the investigation show that the proposed solution leads to (i high hit rate in the classification of the level of congestion, (ii a reduction in average trip time, (iii a reduction in fuel consumption, and (iv reduced CO emissions.

  16. Analisis Penerapan Metode Transmitter Receiver Unit (TRU Upgrading Untuk Mengatasi Traffic Congestion Jaringan GSM Pada BTS Area Purwokerto Kota

    Directory of Open Access Journals (Sweden)

    Alfin Hikmaturokhman

    2011-05-01

    Full Text Available Semakin banyaknya pengguna selular maka akan semakin banyak trafik yang akan tertampung. Trafik yang melebihi kapasitas kanal yang disediakan dapat menyebabkan kondisi Traffic Congestion. Untuk menanganinya diperlukan metode penambahan kapasitas kanal agar semua trafik dapat tertampung dengan baik. Metode ini disebut dengan TRU Upgrading. Transmitter Receiver Unit (TRU adalah hardware yang terletak pada Radio Base Station dalam BTS yang berisi slot-slot kanal sedangkan metode TRU Upgrading adalah metode dengan menambahkan/upgrade kapasitas kanal yang tersedia dari konfigurasi TRU yang telah ada sebelumnya, misalkan pada BTS Pabuaran memiliki konfigurasi 3x2x3 karena terjadi kejenuhan pelanggan maka konfigurasi TRU diupgrade menjadi 3x4x3. Perubahan konfigurasi TRU maka merubah konfigurasi BTS-nya serta menambah kapasitas kanalnya. Key Performance Indicator (KPI yang baik pada Indosat adalah menggunakan batas GoS 2%. Nilai GoS ini dikaitkan dengan tabel Erlang untuk mendapatkan sebuah nilai intensitas trafik. Jika nilai intensitas trafik konfigurasi TRU yang digunakan kurang dari nilai intensitas trafik pelanggan maka disebut traffic congestion. Sebagai akibat dari traffic congestion adalah kondisi blocking. TRU Upgrading ini dilakukan dengan harapan nilai blocking panggilan menjadi 0 %. Pada Purwokerto kota, diterapkan  TRU Upgrading untuk cell Grendeng 3, Pabuaran 2, dan Unsoed 1 karena trafik pelanggan yang terjadi melebihi nilai intensitas trafik dari konfigurasi TRU yang digunakan.   Untuk cell Unsoed 1 dan Grendeng 3 meski telah dilakukan TRU Upgrading menjadi 4 buah TRU tetap terjadi traffic congestion sebesar 8 sampai dengan 15 Erlang dikarenakan pada cell-cell ini mengcover area yang padat penduduk. Sedang untuk Pabuaran 2 penerapan TRU upgrading mencapai keefektifan sebesar 100%.

  17. Reasoning the causality of city sprawl, traffic congestion, and green land disappearance in Taiwan using the CLD model.

    Science.gov (United States)

    Chen, Mei-Chih; Chang, Kaowen

    2014-11-06

    Many city governments choose to supply more developable land and transportation infrastructure with the hope of attracting people and businesses to their cities. However, like those in Taiwan, major cities worldwide suffer from traffic congestion. This study applies the system thinking logic of the causal loops diagram (CLD) model in the System Dynamics (SD) approach to analyze the issue of traffic congestion and other issues related to roads and land development in Taiwan's cities. Comparing the characteristics of development trends with yearbook data for 2002 to 2013 for all of Taiwan's cities, this study explores the developing phenomenon of unlimited city sprawl and identifies the cause and effect relationships in the characteristics of development trends in traffic congestion, high-density population aggregation in cities, land development, and green land disappearance resulting from city sprawl. This study provides conclusions for Taiwan's cities' sustainability and development (S&D). When developing S&D policies, during decision making processes concerning city planning and land use management, governments should think with a holistic view of carrying capacity with the assistance of system thinking to clarify the prejudices in favor of the unlimited developing phenomena resulting from city sprawl.

  18. Integrated Control of Mixed Traffic Networks using Model Predictive Control

    NARCIS (Netherlands)

    Van den Berg, M.

    2010-01-01

    Motivation The growth of our road infrastructure cannot keep up with the growing mobility of people, and the corresponding increase in traffic demand. This results in daily congestion on the freeways. It is an illusion that the problem of congestion can be solved completely within a few years, but

  19. Incorporation of Duffing Oscillator and Wigner-Ville Distribution in Traffic Flow Prediction

    Directory of Open Access Journals (Sweden)

    Anamarija L. Mrgole

    2017-02-01

    Full Text Available The main purpose of this study was to investigate the use of various chaotic pattern recognition methods for traffic flow prediction. Traffic flow is a variable, dynamic and complex system, which is non-linear and unpredictable. The emergence of traffic flow congestion in road traffic is estimated when the traffic load on a specific section of the road in a specific time period is close to exceeding the capacity of the road infrastructure. Under certain conditions, it can be seen in concentrating chaotic traffic flow patterns. The literature review of traffic flow theory and its connection with chaotic features implies that this kind of method has great theoretical and practical value. Researched methods of identifying chaos in traffic flow have shown certain restrictions in their techniques but have suggested guidelines for improving the identification of chaotic parameters in traffic flow. The proposed new method of forecasting congestion in traffic flow uses Wigner-Ville frequency distribution. This method enables the display of a chaotic attractor without the use of reconstruction phase space.

  20. A NEW PREDICTIVE MODEL FOR CONGESTION CONTROL IN WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    NAJME TANZADE PANAH

    2017-06-01

    Full Text Available With the increase of various applications in the domain of wireless sensor networks, the tendency to use wireless sensors has gradually increased in different applications. On the other hand, diverse traffic with different priorities generated by these sensors requires providing adaptive quality of services based on users` needs. In this paper, a congestion control predictor model is proposed for wireless sensor networks, which considers parameters like network energy consumption, packet loss rate and percentage of delivered high and medium priority packets to the destination. This method consists of congestion prevention, congestion control, and energy control plans using shortest path selection algorithm. In the congestion prevention plan, congestion is prevented by investigating the queues length. In the congestion control plan, the congestion is controlled by reducing the transmission rate. Finally, the energy control plan aims to partially balance the energy of nodes to prevent network failures due to node energy outage. Simulation results indicated that the proposed method has a higher efficiency regarding the aforementioned parameters. In addition, comparisons with other well-known methods showed the effectiveness of the proposed method.

  1. Study on the Reduced Traffic Congestion Method Based on Dynamic Guidance Information

    Science.gov (United States)

    Li, Shu-Bin; Wang, Guang-Min; Wang, Tao; Ren, Hua-Ling; Zhang, Lin

    2018-05-01

    This paper studies how to generate the reasonable information of travelers’ decision in real network. This problem is very complex because the travelers’ decision is constrained by different human behavior. The network conditions can be predicted by using the advanced dynamic OD (Origin-Destination, OD) estimation techniques. Based on the improved mesoscopic traffic model, the predictable dynamic traffic guidance information can be obtained accurately. A consistency algorithm is designed to investigate the travelers’ decision by simulating the dynamic response to guidance information. The simulation results show that the proposed method can provide the best guidance information. Further, a case study is conducted to verify the theoretical results and to draw managerial insights into the potential of dynamic guidance strategy in improving traffic performance. Supported by National Natural Science Foundation of China under Grant Nos. 71471104, 71771019, 71571109, and 71471167; The University Science and Technology Program Funding Projects of Shandong Province under Grant No. J17KA211; The Project of Public Security Department of Shandong Province under Grant No. GATHT2015-236; The Major Social and Livelihood Special Project of Jinan under Grant No. 20150905

  2. Variations in exposure to traffic pollution while travelling by different modes in a low density, less congested city.

    Science.gov (United States)

    Kingham, Simon; Longley, Ian; Salmond, Jenny; Pattinson, Woodrow; Shrestha, Kreepa

    2013-10-01

    This research assessed the comparative risk associated with exposure to traffic pollution when travelling via different transport modes in Christchurch, New Zealand. Concentrations of PM1, UFPs and CO were monitored on pre-defined routes during the morning and evening commute on people travelling concurrently by car, bus and bicycle. It was found that car drivers were consistently exposed to the highest levels of CO; on-road cyclists were exposed to higher levels of all pollutants than off-road cyclists; car and bus occupants were exposed to higher average levels of UFP than cyclists, and travellers were occasionally exposed to very high levels of pollution for short periods of time. PM10 and PM2.5 were found to be poor indicators of exposure to traffic pollution. Studying Christchurch adds to our understanding as it was a lower density city with limited traffic congestion compared most other cities previously studied. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

    Directory of Open Access Journals (Sweden)

    Prajakta Desai

    Full Text Available Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN, wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction, across variations in: (a environmental parameters such as road network topology and configuration; (b algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

  4. Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

    Science.gov (United States)

    Desai, Prajakta; Loke, Seng W; Desai, Aniruddha

    2017-01-01

    Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

  5. Hopf bifurcation and uncontrolled stochastic traffic-induced chaos in an RED-AQM congestion control system

    International Nuclear Information System (INIS)

    Wang Jun-Song; Yuan Rui-Xi; Gao Zhi-Wei; Wang De-Jin

    2011-01-01

    We study the Hopf bifurcation and the chaos phenomena in a random early detection-based active queue management (RED-AQM) congestion control system with a communication delay. We prove that there is a critical value of the communication delay for the stability of the RED-AQM control system. Furthermore, we show that the system will lose its stability and Hopf bifurcations will occur when the delay exceeds the critical value. When the delay is close to its critical value, we demonstrate that typical chaos patterns may be induced by the uncontrolled stochastic traffic in the RED-AQM control system even if the system is still stable, which reveals a new route to the chaos besides the bifurcation in the network congestion control system. Numerical simulations are given to illustrate the theoretical results. (general)

  6. Traffic Predictive Control: Case Study and Evaluation

    Science.gov (United States)

    2017-06-26

    This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficien...

  7. Variations in exposure to traffic pollution while travelling by different modes in a low density, less congested city

    International Nuclear Information System (INIS)

    Kingham, Simon; Longley, Ian; Salmond, Jenny; Pattinson, Woodrow; Shrestha, Kreepa

    2013-01-01

    This research assessed the comparative risk associated with exposure to traffic pollution when travelling via different transport modes in Christchurch, New Zealand. Concentrations of PM 1 , UFPs and CO were monitored on pre-defined routes during the morning and evening commute on people travelling concurrently by car, bus and bicycle. It was found that car drivers were consistently exposed to the highest levels of CO; on-road cyclists were exposed to higher levels of all pollutants than off-road cyclists; car and bus occupants were exposed to higher average levels of UFP than cyclists, and travellers were occasionally exposed to very high levels of pollution for short periods of time. PM 10 and PM 2.5 were found to be poor indicators of exposure to traffic pollution. Studying Christchurch adds to our understanding as it was a lower density city with limited traffic congestion compared most other cities previously studied. -- Highlights: •This paper compared commuter exposure by car, bus, and on- and off-road cyclists. •The sampling was carried out in a low density, less congested city. •As in larger cities, car occupants were exposed to the highest levels of pollution. •On-road cyclists are exposed to higher levels of pollutants than off-road cyclists. •PM 10 and PM 2.5 are inappropriate indicators of exposure to vehicle emissions. -- This study carried out in a low density, less congested city, found that like studies in large or densely populated urban areas car drivers are still exposed to the worst quality air

  8. Qualitative and Quantitative Analysis of Congested Marine Traffic Environment – An Application Using Marine Traffic Simulation System

    Directory of Open Access Journals (Sweden)

    Kazuhiko Hasegawa

    2013-06-01

    Full Text Available Difficulty of sailing is quite subjective matter. It depends on various factors. Using Marine Traffic Simulation System (MTSS developed by Osaka University this challenging subject is discussed. In this system realistic traffic flow including collision avoidance manoeuvres can be reproduced in a given area. Simulation is done for southward of Tokyo Bay, Strait of Singapore and off-Shanghai area changing traffic volume from 5 or 50 to 150 or 200% of the present volume. As a result, strong proportional relation between near-miss ratio and traffic density per hour per sailed area is found, independent on traffic volume, area size and configuration. The quantitative evaluation index of the difficulty of sailing, here called risk rate of the area is defined using thus defined traffic density and near-miss ratio.

  9. HETEROGENEITY INDEX FOR THE ASSESSMENT OF RELATIONSHIP BETWEEN LAND USE PATTERN AND ROAD TRAFFIC CONGESTION IN APAPA-OWOROSHOKI EXPRESS WAY, LAGOS METROPOLIS

    Directory of Open Access Journals (Sweden)

    D. B. Alaigba

    2017-05-01

    Full Text Available The problem of urban mobility is complicated by traffic delay, resulting from poor planning, high population density and poor condition of roads within urban spaces. This study assessed traffic congestion resulting from differential contribution made by various land-uses along Apapa-Oworoshoki expressway in Lagos metropolis. The data for this study was from both primary and secondary sources; GPS point data was collected at selected points for traffic volume count; observation of the nature of vehicular traffic congestion, and land use types along the corridor. Existing data on traffic count along the corridor, connectivity map and land use map sourced from relevant authorities were acquired. Traffic congestion within the area was estimated using volume capacity ratio (V/C. Heterogeneity Index was developed and used to quantify the percentage contribution to traffic volume from various land-use categories. Analytical Hierarchical Processing (AHP and knowledge-based weighting were used to rank the importance of different heterogeneity indices. Results showed significant relationship between the degree of heterogeneity of the land use pattern and road traffic congestion. Volume Capacity Ratio computed revealed that the route corridor exceeds its designed capacity in the southward direction between the hours of 8am and 12pm on working days. Five major nodes were analyzed along the corridor, and were all above the expected Passenger Car Unit (PCU, these are “Oshodi” 15 %, “Airport junction” 10 %, “Cele bus stop” 21 %, “Mile 2” 14 %, “Berger” 15 % and “Tincan bus stop” 33 % indicating heavy traffic congestion.

  10. Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction

    Directory of Open Access Journals (Sweden)

    Hua-pu Lu

    2015-01-01

    Full Text Available With the rapid development of urban informatization, the era of big data is coming. To satisfy the demand of traffic congestion early warning, this paper studies the method of real-time traffic flow state identification and prediction based on big data-driven theory. Traffic big data holds several characteristics, such as temporal correlation, spatial correlation, historical correlation, and multistate. Traffic flow state quantification, the basis of traffic flow state identification, is achieved by a SAGA-FCM (simulated annealing genetic algorithm based fuzzy c-means based traffic clustering model. Considering simple calculation and predictive accuracy, a bilevel optimization model for regional traffic flow correlation analysis is established to predict traffic flow parameters based on temporal-spatial-historical correlation. A two-stage model for correction coefficients optimization is put forward to simplify the bilevel optimization model. The first stage model is built to calculate the number of temporal-spatial-historical correlation variables. The second stage model is present to calculate basic model formulation of regional traffic flow correlation. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling and computing methods.

  11. The dynamics of urban traffic congestion and the price of parking

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; de Palma, André

    2013-01-01

    We consider commuting in a congested urban area. While an efficient time-varying toll may eliminate queuing, a toll may not be politically feasible. We study the benefit of a substitute: a parking fee at the workplace. An optimal time-varying parking fee is charged at zero rate when there is queu...

  12. Driver support in congestion. An assessment of user needs and impacts on driver and traffic flow

    NARCIS (Netherlands)

    van Driel, Cornelie

    2007-01-01

    Mobility is a key factor for modern societies. However, it also brings about problems, such as congestion, accidents and pollution. High expectations rest on in-vehicle systems to contribute to solving these problems. These so-called driver support systems use advanced information and communication

  13. Parking fees as a substitute for roadpricing in a dynamic model of traffic congestion

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Palma, André de

    2011-01-01

    We consider the morning commute under bottleneck congestion. The maximally e¢ cient time varying toll can eliminate queueing, but may not be available. We consider a situation where travellers can be charged a parking fee at a time varying rate that applies from the time of passage of the facilit...

  14. Data rate based congestion control in V2V communication for traffic safety applications

    NARCIS (Netherlands)

    Belagal Math, C.; Özgür, A.; Heemstra de Groot, S.M.; Li, H.

    2015-01-01

    Vehicle-to-Vehicle (V2V) communication systems intend to increase safety and efficiency of the transportation networks. At high vehicle density, the communication channel may become congested, impairing the reliability of the safety applications. As a counter measure, the European Telecommunications

  15. Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service

    OpenAIRE

    Horvitz, Eric J.; Apacible, Johnson; Sarin, Raman; Liao, Lin

    2012-01-01

    We present research on developing models that forecast traffic flow and congestion in the Greater Seattle area. The research has led to the deployment of a service named JamBayes, that is being actively used by over 2,500 users via smartphones and desktop versions of the system. We review the modeling effort and describe experiments probing the predictive accuracy of the models. Finally, we present research on building models that can identify current and future surprises, via efforts on mode...

  16. The Physics of Traffic Congestion and Road Pricing in Transportation Planning

    Science.gov (United States)

    Levinson, David

    2010-03-01

    This presentation develops congestion theory and congestion pricing theory from its micro- foundations, the interaction of two or more vehicles. Using game theory, with a two- player game it is shown that the emergence of congestion depends on the players' relative valuations of early arrival, late arrival, and journey delay. Congestion pricing can be used as a cooperation mechanism to minimize total costs (if returned to the players). The analysis is then extended to the case of the three- player game, which illustrates congestion as a negative externality imposed on players who do not themselves contribute to it. A multi-agent model of travelers competing to utilize a roadway in time and space is presented. To realize the spillover effect among travelers, N-player games are constructed in which the strategy set includes N+1 strategies. We solve the N-player game (for N = 7) and find Nash equilibria if they exist. This model is compared to the bottleneck model. The results of numerical simulation show that the two models yield identical results in terms of lowest total costs and marginal costs when a social optimum exists. Moving from temporal dynamics to spatial complexity, using consistent agent- based techniques, we model the decision-making processes of users and infrastructure owner/operators to explore the welfare consequence of price competition, capacity choice, and product differentiation on congested transportation networks. Component models include: (1) An agent-based travel demand model wherein each traveler has learning capabilities and unique characteristics (e.g. value of time); (2) Econometric facility provision cost models; and (3) Representations of road authorities making pricing and capacity decisions. Different from small-network equilibrium models in prior literature, this agent- based model is applicable to pricing and investment analyses on large complex networks. The subsequent economic analysis focuses on the source, evolution

  17. Highway traffic noise prediction based on GIS

    Science.gov (United States)

    Zhao, Jianghua; Qin, Qiming

    2014-05-01

    Before building a new road, we need to predict the traffic noise generated by vehicles. Traditional traffic noise prediction methods are based on certain locations and they are not only time-consuming, high cost, but also cannot be visualized. Geographical Information System (GIS) can not only solve the problem of manual data processing, but also can get noise values at any point. The paper selected a road segment from Wenxi to Heyang. According to the geographical overview of the study area and the comparison between several models, we combine the JTG B03-2006 model and the HJ2.4-2009 model to predict the traffic noise depending on the circumstances. Finally, we interpolate the noise values at each prediction point and then generate contours of noise. By overlaying the village data on the noise contour layer, we can get the thematic maps. The use of GIS for road traffic noise prediction greatly facilitates the decision-makers because of GIS spatial analysis function and visualization capabilities. We can clearly see the districts where noise are excessive, and thus it becomes convenient to optimize the road line and take noise reduction measures such as installing sound barriers and relocating villages and so on.

  18. Optimum principle for a vehicular traffic network: minimum probability of congestion

    Energy Technology Data Exchange (ETDEWEB)

    Kerner, Boris S, E-mail: boris.kerner@daimler.com [Daimler AG, GR/PTF, HPC: G021, 71059 Sindelfingen (Germany)

    2011-03-04

    We introduce an optimum principle for a vehicular traffic network with road bottlenecks. This network breakdown minimization (BM) principle states that the network optimum is reached when link flow rates are assigned in the network in such a way that the probability for spontaneous occurrence of traffic breakdown in at least one of the network bottlenecks during a given observation time reaches the minimum possible value. Based on numerical simulations with a stochastic three-phase traffic flow model, we show that in comparison to the well-known Wardrop's principles, the application of the BM principle permits considerably greater network inflow rates at which no traffic breakdown occurs and, therefore, free flow remains in the whole network. (fast track communication)

  19. Optimum principle for a vehicular traffic network: minimum probability of congestion

    International Nuclear Information System (INIS)

    Kerner, Boris S

    2011-01-01

    We introduce an optimum principle for a vehicular traffic network with road bottlenecks. This network breakdown minimization (BM) principle states that the network optimum is reached when link flow rates are assigned in the network in such a way that the probability for spontaneous occurrence of traffic breakdown in at least one of the network bottlenecks during a given observation time reaches the minimum possible value. Based on numerical simulations with a stochastic three-phase traffic flow model, we show that in comparison to the well-known Wardrop's principles, the application of the BM principle permits considerably greater network inflow rates at which no traffic breakdown occurs and, therefore, free flow remains in the whole network. (fast track communication)

  20. Human Factors of Automated Driving : Predicting the Effects of Authority Transitions on Traffic Flow Efficiency

    NARCIS (Netherlands)

    Varotto, S.F.; Hoogendoorn, R.G.; Van Arem, B.; Hoogendoorn, S.P.

    2014-01-01

    Automated driving potentially has a significant impact on traffic flow efficiency. Automated vehicles, which possess cooperative capabilities, are expected to reduce congestion levels for instance by increasing road capacity, by anticipating traffic conditions further downstream and also by

  1. Traffic Route Guidance using Feedback of Predicted Travel Times : Improving Travel Times in the Berlin Traffic Network

    OpenAIRE

    Bergsten, Arvid; Zetterberg, Daniel

    2008-01-01

    Traffic congestions constitute a problem in many large cities. Congestions can be handled by reducing the network demand, expanding the infrastructure, or by utilizing the road network more efficiently. This master thesis presents a methodology for route guidance, based on automatic feedback control from the current traffic situation. Through variable direction signs or individual in-car devices, all vehicles with a certain origin and destination (which are both normally intermediate) are gui...

  2. Reducing Congestion in Obstructed Highways with Traffic Data Dissemination Using Ad hoc Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Coveney PeterV

    2010-01-01

    Full Text Available Vehicle-to-vehicle communications can be used effectively for intelligent transport systems (ITSs and location-aware services. The ability to disseminate information in an ad hoc fashion allows pertinent information to propagate faster through a network. In the realm of ITS, the ability to spread warning information faster and further is of great advantage to receivers. In this paper we propose and present a message-dissemination procedure that uses vehicular wireless protocols to influence vehicular flow, reducing congestion in road networks. The computational experiments we present show how a car-following model and lane-change algorithm can be adapted to "react" to the reception of information. This model also illustrates the advantages of coupling together with vehicular flow modelling tools and network simulation tools.

  3. Urban traffic simulated from the dual representation: Flow, crisis and congestion

    International Nuclear Information System (INIS)

    Hu Maobin; Jiang Rui; Wang Ruili; Wu Qingsong

    2009-01-01

    We propose a traffic simulation model for urban system based on the dual graph representation of a urban road network and with a random entering vehicle rate. To avoid the shortcoming of 'Space Syntax' of ignoring the road's metric distance, we consider both the motion of the vehicles along roads and the navigation of the vehicles in the network. Simulations have shown some basic properties of urban traffic system, such as flux fluctuation, crisis and dissipation, phase transition from a free flow to jams, overall capacity, the distribution of traveling time, and the fundamental diagram. The system's behavior greatly depends on the topology of the transportation network. A well-planned lattice grid can keep more vehicles travelling. The critical entering vehicle rate is much greater in lattice grid than in a self-organized network. The vehicles have to travel longer time in a self-organized urban system due to the navigation cost.

  4. Cross-Layer Active Predictive Congestion Control Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yinfeng Wu

    2009-10-01

    Full Text Available In wireless sensor networks (WSNs, there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node‟s neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  5. Cross-layer active predictive congestion control protocol for wireless sensor networks.

    Science.gov (United States)

    Wan, Jiangwen; Xu, Xiaofeng; Feng, Renjian; Wu, Yinfeng

    2009-01-01

    In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  6. Operational performance of a congested corridor with lanes dedicated to autonomous vehicle traffic

    Directory of Open Access Journals (Sweden)

    Zachary Vander Laan

    2017-06-01

    Full Text Available This paper considers the operational performance impact of autonomous vehicles (AV on a multi-lane freeway corridor with separate lanes dedicated to AV and non-AV traffic. Autonomous vehicle behavior is modeled at the macroscopic level by modifying the fundamental diagram relating hourly traffic flow and vehicle density, a step that is justified by adjusting a parameter from Newell’s car-following model at the microscopic level and transforming back to a macroscopic representation. The model is applied to the I-95 corridor between Washington, DC and Baltimore, MD during the PM peak period, where the impact of introducing a managed AV-only lane is assessed at varying penetration rates of autonomous vehicles. The results show that the overall corridor performance metrics improve with increasing penetration rates up to 30%, 40% or 50% (depending on the underlying assumptions that govern AV behavior, after which the performance deteriorates drastically. Implications of the results are discussed in light of the per-lane and aggregated metrics, and future directions for research are proposed.

  7. An Experimental Study of the Noise Due to Traffic in a Congested Urban Area

    Science.gov (United States)

    Sangeetha, M.; Sankar, P.

    2016-03-01

    Noise pollution in an urban environment is an issue of serious concern in the major cities of India. There are various factors that contribute to the increase of noise levels in urban areas. The intensity of traffic is one of the factors which contributes to a drastic increase in environmental noise. The management of noise pollution has to be considered in the decision making process. In this paper, an attempt is made to study the existing noise level due to the traffic in Velachery which is declared as a sensitive area by the Ministry of Environment and Forestry (MoEF). The noise level data is collected using the MS6710 digital sound meter. The Custic simulation software version 3.2 is used for finding the propagation of noise. The spatial patterns of measurement were also calculated, in the sub-urban area of Velachery, Chennai, Tamilnadu, India. A means of transmitting this data to vehicles moving in the area, through a wireless medium is simulated using NCTUns 6.0 (network simulator), to enable drivers to understand the environmental conditions. A hardware was also designed which can be used to transmit and receive the noise data using the Zigbee module. A noise transmitting station is placed at a junction, so that it can transmit this noise data to the receivers which are fitted inside the vehicles.

  8. Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent

    Directory of Open Access Journals (Sweden)

    Yan Liu

    2016-01-01

    Full Text Available The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs, are studied in detail, using the largest Lyapunov exponent. With the introduction of phase space reconstruction based on the time sequence, the high-dimensional traffic is projected onto the low dimension reconstructed phase space, and a reduced dynamic system is obtained from the dynamic system viewpoint. Then, a numerical method for computing the largest Lyapunov exponent of the low-dimensional dynamic system is presented. Further, the longest predictable time, which is related to chaotic behaviors in the system, is studied using the largest Lyapunov exponent, and the Wolf method is used to predict the evolution of the traffic in a local area network by both Dot and Interval predictions, and a reliable result is obtained by the presented method. As the conclusion, the results show that the largest Lyapunov exponent can be used to describe the sensitivity of the trajectory in the reconstructed phase space to the initial values. Moreover, Dot Prediction can effectively predict the flow burst. The numerical simulation also shows that the presented method is feasible and efficient for predicting the complex dynamic behaviors in LAN traffic, especially for congestion and attack in networks, which are the main two complex phenomena behaving as chaos in networks.

  9. Predicting Taxi-Out Time at Congested Airports with Optimization-Based Support Vector Regression Methods

    Directory of Open Access Journals (Sweden)

    Guan Lian

    2018-01-01

    Full Text Available Accurate prediction of taxi-out time is significant precondition for improving the operationality of the departure process at an airport, as well as reducing the long taxi-out time, congestion, and excessive emission of greenhouse gases. Unfortunately, several of the traditional methods of predicting taxi-out time perform unsatisfactorily at congested airports. This paper describes and tests three of those conventional methods which include Generalized Linear Model, Softmax Regression Model, and Artificial Neural Network method and two improved Support Vector Regression (SVR approaches based on swarm intelligence algorithm optimization, which include Particle Swarm Optimization (PSO and Firefly Algorithm. In order to improve the global searching ability of Firefly Algorithm, adaptive step factor and Lévy flight are implemented simultaneously when updating the location function. Six factors are analysed, of which delay is identified as one significant factor in congested airports. Through a series of specific dynamic analyses, a case study of Beijing International Airport (PEK is tested with historical data. The performance measures show that the proposed two SVR approaches, especially the Improved Firefly Algorithm (IFA optimization-based SVR method, not only perform as the best modelling measures and accuracy rate compared with the representative forecast models, but also can achieve a better predictive performance when dealing with abnormal taxi-out time states.

  10. Scalable data-driven short-term traffic prediction

    NARCIS (Netherlands)

    Friso, K.; Wismans, L. J.J.; Tijink, M. B.

    2017-01-01

    Short-term traffic prediction has a lot of potential for traffic management. However, most research has traditionally focused on either traffic models-which do not scale very well to large networks, computationally-or on data-driven methods for freeways, leaving out urban arterials completely. Urban

  11. Learning Behavior Models for Interpreting and Predicting Traffic Situations

    OpenAIRE

    Gindele, Tobias

    2014-01-01

    In this thesis, we present Bayesian state estimation and machine learning methods for predicting traffic situations. The cognitive ability to assess situations and behaviors of traffic participants, and to anticipate possible developments is an essential requirement for several applications in the traffic domain, especially for self-driving cars. We present a method for learning behavior models from unlabeled traffic observations and develop improved learning methods for decision trees.

  12. Coordinated Traffic Incident and Congestion Management (TIM-CM) : Mitigating Regional Impacts of Major Traffic Incidents in the Seattle I-5 Corridor

    Science.gov (United States)

    2018-02-02

    Within the Seattle metropolitan area, traffic incident management (TIM) operations provide a multi-jurisdictional and coordinated strategy to detect, respond to, and clear traffic incidents so that traffic flow can be restored quickly and safely. The...

  13. Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

    International Nuclear Information System (INIS)

    Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

    2015-01-01

    Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

  14. Accurate Multisteps Traffic Flow Prediction Based on SVM

    Directory of Open Access Journals (Sweden)

    Zhang Mingheng

    2013-01-01

    Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

  15. Prediction of traffic-related nitrogen oxides concentrations using Structural Time-Series models

    Science.gov (United States)

    Lawson, Anneka Ruth; Ghosh, Bidisha; Broderick, Brian

    2011-09-01

    Ambient air quality monitoring, modeling and compliance to the standards set by European Union (EU) directives and World Health Organization (WHO) guidelines are required to ensure the protection of human and environmental health. Congested urban areas are most susceptible to traffic-related air pollution which is the most problematic source of air pollution in Ireland. Long-term continuous real-time monitoring of ambient air quality at such urban centers is essential but often not realistic due to financial and operational constraints. Hence, the development of a resource-conservative ambient air quality monitoring technique is essential to ensure compliance with the threshold values set by the standards. As an intelligent and advanced statistical methodology, a Structural Time Series (STS) based approach has been introduced in this paper to develop a parsimonious and computationally simple air quality model. In STS methodology, the different components of a time-series dataset such as the trend, seasonal, cyclical and calendar variations can be modeled separately. To test the effectiveness of the proposed modeling strategy, average hourly concentrations of nitrogen dioxide and nitrogen oxides from a congested urban arterial in Dublin city center were modeled using STS methodology. The prediction error estimates from the developed air quality model indicate that the STS model can be a useful tool in predicting nitrogen dioxide and nitrogen oxides concentrations in urban areas and will be particularly useful in situations where the information on external variables such as meteorology or traffic volume is not available.

  16. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.

    Science.gov (United States)

    Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

    2017-06-26

    Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

  17. Analysis of vehicular traffic flow in the major areas of Kuala Lumpur utilizing open-traffic

    Science.gov (United States)

    Manogaran, Saargunawathy; Ali, Muhammad; Yusof, Kamaludin Mohamad; Suhaili, Ramdhan

    2017-09-01

    Vehicular traffic congestion occurs when a large number of drivers are overcrowded on the road and the traffic flow does not run smoothly. Traffic congestion causes chaos on the road and interruption to daily activities of users. Time consumed on road give lots of negative effects on productivity, social behavior, environmental and cost to economy. Congestion is worsens and leads to havoc during the emergency such as flood, accidents, road maintenance and etc., where behavior of traffic flow is always unpredictable and uncontrollable. Real-time and historical traffic data are critical inputs for most traffic flow analysis applications. Researcher attempt to predict traffic using simulations as there is no exact model of traffic flow exists due to its high complexity. Open Traffic is an open source platform available for traffic data analysis linked to Open Street Map (OSM). This research is aimed to study and understand the Open Traffic platform. The real-time traffic flow pattern in Kuala Lumpur area was successfully been extracted and analyzed using Open Traffic. It was observed that the congestion occurs on every major road in Kuala Lumpur and most of it owes to the offices and the economic and commercial centers during rush hours. At some roads the congestion occurs at night due to the tourism activities.

  18. Validation of a multi-objective, predictive urban traffic model

    NARCIS (Netherlands)

    Wilmink, I.R.; Haak, P. van den; Woldeab, Z.; Vreeswijk, J.

    2013-01-01

    This paper describes the results of the verification and validation of the ecoStrategic Model, which was developed, implemented and tested in the eCoMove project. The model uses real-time and historical traffic information to determine the current, predicted and desired state of traffic in a

  19. Congestion levies; Congestieheffingen

    Energy Technology Data Exchange (ETDEWEB)

    Verhoef, E.T. [Vakgroep Ruimtelijke Economie, Vrije Universiteit en Tinbergen Instituut, Amsterdam (Netherlands)

    1998-02-20

    Traffic jams or congestion can be controlled by means of Pigouvian levies. Congestion costs comprise both time losses as scheduling costs. Because a part of those costs are external costs, the free market output is not Pareto-efficient, and therefore levies are required to recover the efficiency. With some restrictions, road-pricing for the western part of the Netherlands is considered to be a feasible option

  20. 4K Video Traffic Prediction using Seasonal Autoregressive Modeling

    Directory of Open Access Journals (Sweden)

    D. R. Marković

    2017-06-01

    Full Text Available From the perspective of average viewer, high definition video streams such as HD (High Definition and UHD (Ultra HD are increasing their internet presence year over year. This is not surprising, having in mind expansion of HD streaming services, such as YouTube, Netflix etc. Therefore, high definition video streams are starting to challenge network resource allocation with their bandwidth requirements and statistical characteristics. Need for analysis and modeling of this demanding video traffic has essential importance for better quality of service and experience support. In this paper we use an easy-to-apply statistical model for prediction of 4K video traffic. Namely, seasonal autoregressive modeling is applied in prediction of 4K video traffic, encoded with HEVC (High Efficiency Video Coding. Analysis and modeling were performed within R programming environment using over 17.000 high definition video frames. It is shown that the proposed methodology provides good accuracy in high definition video traffic modeling.

  1. Predictive functional control for active queue management in congested TCP/IP networks.

    Science.gov (United States)

    Bigdeli, N; Haeri, M

    2009-01-01

    Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.

  2. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

    Directory of Open Access Journals (Sweden)

    Haiyang Yu

    2017-06-01

    Full Text Available Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs, for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs and long short-term memory (LSTM neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

  3. Network traffic anomaly prediction using Artificial Neural Network

    Science.gov (United States)

    Ciptaningtyas, Hening Titi; Fatichah, Chastine; Sabila, Altea

    2017-03-01

    As the excessive increase of internet usage, the malicious software (malware) has also increase significantly. Malware is software developed by hacker for illegal purpose(s), such as stealing data and identity, causing computer damage, or denying service to other user[1]. Malware which attack computer or server often triggers network traffic anomaly phenomena. Based on Sophos's report[2], Indonesia is the riskiest country of malware attack and it also has high network traffic anomaly. This research uses Artificial Neural Network (ANN) to predict network traffic anomaly based on malware attack in Indonesia which is recorded by Id-SIRTII/CC (Indonesia Security Incident Response Team on Internet Infrastructure/Coordination Center). The case study is the highest malware attack (SQL injection) which has happened in three consecutive years: 2012, 2013, and 2014[4]. The data series is preprocessed first, then the network traffic anomaly is predicted using Artificial Neural Network and using two weight update algorithms: Gradient Descent and Momentum. Error of prediction is calculated using Mean Squared Error (MSE) [7]. The experimental result shows that MSE for SQL Injection is 0.03856. So, this approach can be used to predict network traffic anomaly.

  4. Depression increasingly predicts mortality in the course of congestive heart failure.

    Science.gov (United States)

    Jünger, Jana; Schellberg, Dieter; Müller-Tasch, Thomas; Raupp, Georg; Zugck, Christian; Haunstetter, Armin; Zipfel, Stephan; Herzog, Wolfgang; Haass, Markus

    2005-03-02

    Congestive heart failure (CHF) is frequently associated with depression. However, the impact of depression on prognosis has not yet been sufficiently established. To prospectively investigate the influence of depression on mortality in patients with CHF. In 209 CHF patients depression was assessed by the Hospital Anxiety and Depression Scale (HADS-D). Compared to survivors (n=164), non-survivors (n=45) were characterized by a higher New York Heart Association (NYHA) functional class (2.8+/-0.7 vs. 2.5+/-0.6), and a lower left ventricular ejection fraction (LVEF) (18+/-8 vs. 23+/-10%) and peakVO(2) (13.1+/-4.5 vs. 15.4+/-5.2 ml/kg/min) at baseline. Furthermore, non-survivors had a higher depression score (7.5+/-4.0 vs. 6.1+/-4.3) (all P<0.05). After a mean follow-up of 24.8 months the depression score was identified as a significant indicator of mortality (P<0.01). In multivariate analysis the depression score predicted mortality independent from NYHA functional class, LVEF and peakVO(2). Combination of depression score, LVEF and peakVO(2) allowed for a better risk stratification than combination of LVEF and peakVO(2) alone. The risk ratio for mortality in patients with an elevated depression score (i.e. above the median) rose over time to 8.2 after 30 months (CI 2.62-25.84). The depression score predicts mortality independent of somatic parameters in CHF patients not treated for depression. Its prognostic power increases over time and should, thus, be accounted for in risk stratification and therapy.

  5. A Trial-and-Error Method with Autonomous Vehicle-to-Infrastructure Traffic Counts for Cordon-Based Congestion Pricing

    Directory of Open Access Journals (Sweden)

    Zhiyuan Liu

    2017-01-01

    Full Text Available This study proposes a practical trial-and-error method to solve the optimal toll design problem of cordon-based pricing, where only the traffic counts autonomously collected on the entry links of the pricing cordon are needed. With the fast development and adoption of vehicle-to-infrastructure (V2I facilities, it is very convenient to autonomously collect these data. Two practical properties of the cordon-based pricing are further considered in this article: the toll charge on each entry of one pricing cordon is identical; the total inbound flow to one cordon should be restricted in order to maintain the traffic conditions within the cordon area. Then, the stochastic user equilibrium (SUE with asymmetric link travel time functions is used to assess each feasible toll pattern. Based on a variational inequality (VI model for the optimal toll pattern, this study proposes a theoretically convergent trial-and-error method for the addressed problem, where only traffic counts data are needed. Finally, the proposed method is verified based on a numerical network example.

  6. Traffic

    International Nuclear Information System (INIS)

    Lichtblau, G.

    2001-01-01

    This chapter deals with passenger and freight traffic, public and private transportation, traffic related environmental impacts, future developments, traffic indicators, regional traffic planning, health costs due to road traffic related air pollution, noise pollution, measures and regulations for traffic control and fuels for traffic. In particular energy consumption, energy efficiency, pollutant emissions ( CO 2 , SO 2 , NO x , HC, CO, N 2 O, NH 3 and particulates) and environmental effects of the different types of traffic and different types of fuels are compared and studied. Legal regulations and measures for an effective traffic control are discussed. (a.n.)

  7. Virtual network topology reconfiguration based on big data analytics for traffic prediction

    OpenAIRE

    Morales Alcaide, Fernando; Ruiz Ramírez, Marc; Velasco Esteban, Luis Domingo

    2016-01-01

    Big data analytics is applied for IP traffic prediction. When the virtual topology needs to be reconfigured, predicted and current traffic matrices are used to find the optimal topology. Exhaustive simulation results reveal large benefits. Peer Reviewed

  8. A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

    Directory of Open Access Journals (Sweden)

    Meng Fan-Bo

    2016-01-01

    Full Text Available Network traffic is a significantly important parameter for network traffic engineering, while it holds highly dynamic nature in the network. Accordingly, it is difficult and impossible to directly predict traffic amount of end-to-end flows. This paper proposes a new prediction algorithm to network traffic using the wavelet analysis. Firstly, network traffic is converted into the time-frequency domain to capture time-frequency feature of network traffic. Secondly, in different frequency components, we model network traffic in the time-frequency domain. Finally, we build the prediction model about network traffic. At the same time, the corresponding prediction algorithm is presented to attain network traffic prediction. Simulation results indicates that our approach is promising.

  9. Probabilistic prediction of aggregate traffic demand using uncertainty in individual flight predictions.

    Science.gov (United States)

    2009-08-01

    Federal Aviation Administration (FAA) air traffic flow management (TFM) : decision-making is based primarily on a comparison of deterministic predictions of demand : and capacity at National Airspace System (NAS) elements such as airports, fixes and ...

  10. Vehicular traffic noise prediction using soft computing approach.

    Science.gov (United States)

    Singh, Daljeet; Nigam, S P; Agrawal, V P; Kumar, Maneek

    2016-12-01

    A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles

    OpenAIRE

    Wan, Jiafu; Liu, Jianqi; Shao, Zehui; Vasilakos, Athanasios V.; Imran, Muhammad; Zhou, Keliang

    2016-01-01

    The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and Io...

  12. A Traffic Prediction Algorithm for Street Lighting Control Efficiency

    Directory of Open Access Journals (Sweden)

    POPA Valentin

    2013-01-01

    Full Text Available This paper presents the development of a traffic prediction algorithm that can be integrated in a street lighting monitoring and control system. The prediction algorithm must enable the reduction of energy costs and improve energy efficiency by decreasing the light intensity depending on the traffic level. The algorithm analyses and processes the information received at the command center based on the traffic level at different moments. The data is collected by means of the Doppler vehicle detection sensors integrated within the system. Thus, two methods are used for the implementation of the algorithm: a neural network and a k-NN (k-Nearest Neighbor prediction algorithm. For 500 training cycles, the mean square error of the neural network is 9.766 and for 500.000 training cycles the error amounts to 0.877. In case of the k-NN algorithm the error increases from 8.24 for k=5 to 12.27 for a number of 50 neighbors. In terms of a root means square error parameter, the use of a neural network ensures the highest performance level and can be integrated in a street lighting control system.

  13. The impact of real-time and predictive traffic information on travelers' behavior on the I-4 corridor. Final report.

    Science.gov (United States)

    2003-07-01

    Real time and predicted traffic information plays a key role in the successful implementation of advanced traveler information systems (ATIS) and advance traffic management systems (ATMS). Traffic information is essentially valuable to both transport...

  14. Road traffic noise prediction model for heterogeneous traffic based on ASJ-RTN Model 2008 with consideration of horn

    Science.gov (United States)

    Hustim, M.; Arifin, Z.; Aly, S. H.; Ramli, M. I.; Zakaria, R.; Liputo, A.

    2018-04-01

    This research aimed to predict the noise produced by the traffic in the road network in Makassar City using ASJ-RTN Model 2008 by calculating the horn sound. Observations were taken at 37 survey points on road side. The observations were conducted at 06.00 - 18.00 and 06.00 - 21.00 which research objects were motorcycle (MC), light vehicle (LV) and heavy vehicle (HV). The observed data were traffic volume, vehicle speed, number of horn and traffic noise using Sound Level Meter Tenmars TM-103. The research result indicates that prediction noise model by calculating the horn sound produces the average noise level value of 78.5 dB having the Pearson’s correlation and RMSE of 0.95 and 0.87. Therefore, ASJ-RTN Model 2008 prediction model by calculating the horn sound is said to be sufficiently good for predicting noise level.

  15. Mathematical principles of road congestion pricing

    African Journals Online (AJOL)

    route during the morning peak hour: cost and demand functions. the same at all traffic levels. Although car running costs rise with increases in travel time in congested urban travel conditions, they are usually regarded by road users as being.

  16. Model Predictive Control for Integrating Traffic Control Measures

    NARCIS (Netherlands)

    Hegyi, A.

    2004-01-01

    Dynamic traffic control measures, such as ramp metering and dynamic speed limits, can be used to better utilize the available road capacity. Due to the increasing traffic volumes and the increasing number of traffic jams the interaction between the control measures has increased such that local

  17. Predicting future traffic offenders by pre-drivers’ attitudes towards risky driving

    OpenAIRE

    Slavinskienė, Justina; Žardeckaitė-Matulaitienė, Kristina; Endriulaitienė, Auksė; Šeibokaitė, Laura; Markšaitytė, Rasa

    2017-01-01

    Worldwide statistics indicate that novice drivers are still one of the riskiest drivers’ groups as they highly contribute to road accidents and traffic rules violations. Thus, the psychological variables that allow predicting whether novice drivers will violate traffic rules are important in risky driving research. The aim of this study is to find out if pre-drivers’ attitudes towards risky driving measured before obtaining driving license could predict future traffic offences during the firs...

  18. Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method

    Directory of Open Access Journals (Sweden)

    Yuhan Jia

    2017-01-01

    Full Text Available Accurate traffic flow prediction is increasingly essential for successful traffic modeling, operation, and management. Traditional data driven traffic flow prediction approaches have largely assumed restrictive (shallow model architectures and do not leverage the large amount of environmental data available. Inspired by deep learning methods with more complex model architectures and effective data mining capabilities, this paper introduces the deep belief network (DBN and long short-term memory (LSTM to predict urban traffic flow considering the impact of rainfall. The rainfall-integrated DBN and LSTM can learn the features of traffic flow under various rainfall scenarios. Experimental results indicate that, with the consideration of additional rainfall factor, the deep learning predictors have better accuracy than existing predictors and also yield improvements over the original deep learning models without rainfall input. Furthermore, the LSTM can outperform the DBN to capture the time series characteristics of traffic flow data.

  19. Driving with a congestion assistant : mental workload and acceptance

    NARCIS (Netherlands)

    Brookhuis, K.A.; Driel, C. J.G. van; Hof, T.; Arem, B. van; Hoedemaeker, M.

    2009-01-01

    New driver support systems are developed and introduced to the market at increasing speed. In conditions of traffic congestion drivers may be supported by a" Congestion Assistant", a system that combines the features of a Congestion Warning System (acoustic warning and gas pedal counterforce) and a

  20. Route Optimization for Offloading Congested Meter Fixes

    Science.gov (United States)

    Xue, Min; Zelinski, Shannon

    2016-01-01

    The Optimized Route Capability (ORC) concept proposed by the FAA facilitates traffic managers to identify and resolve arrival flight delays caused by bottlenecks formed at arrival meter fixes when there exists imbalance between arrival fixes and runways. ORC makes use of the prediction capability of existing automation tools, monitors the traffic delays based on these predictions, and searches the best reroutes upstream of the meter fixes based on the predictions and estimated arrival schedules when delays are over a predefined threshold. Initial implementation and evaluation of the ORC concept considered only reroutes available at the time arrival congestion was first predicted. This work extends previous work by introducing an additional dimension in reroute options such that ORC can find the best time to reroute and overcome the 'firstcome- first-reroute' phenomenon. To deal with the enlarged reroute solution space, a genetic algorithm was developed to solve this problem. Experiments were conducted using the same traffic scenario used in previous work, when an arrival rush was created for one of the four arrival meter fixes at George Bush Intercontinental Houston Airport. Results showed the new approach further improved delay savings. The suggested route changes from the new approach were on average 30 minutes later than those using other approaches, and fewer numbers of reroutes were required. Fewer numbers of reroutes reduce operational complexity and later reroutes help decision makers deal with uncertain situations.

  1. Effective Road Model for Congestion Control in VANETs

    OpenAIRE

    Dongre, Manoj M.; Bawane, Narendra G.

    2016-01-01

    Congestion on the roads is a key problem to deal with, which wastes valuable time.. Due to high mobility rate and relative speed link failure occur very often. VANET is used to tackle the problem of congestion, and make decisions well in advance to avoid traffic congestion. In this paper we proposed a solution to detect and control the traffic congestion by using of both (V2V) and (V2I), as a result the drivers become aware of the location of congestion as well as way to avoid getting stuck i...

  2. Comparison of classical statistical methods and artificial neural network in traffic noise prediction

    International Nuclear Information System (INIS)

    Nedic, Vladimir; Despotovic, Danijela; Cvetanovic, Slobodan; Despotovic, Milan; Babic, Sasa

    2014-01-01

    Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period L eq . Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model

  3. Comparison of classical statistical methods and artificial neural network in traffic noise prediction

    Energy Technology Data Exchange (ETDEWEB)

    Nedic, Vladimir, E-mail: vnedic@kg.ac.rs [Faculty of Philology and Arts, University of Kragujevac, Jovana Cvijića bb, 34000 Kragujevac (Serbia); Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs [Faculty of Economics, University of Kragujevac, Djure Pucara Starog 3, 34000 Kragujevac (Serbia); Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs [Faculty of Economics, University of Niš, Trg kralja Aleksandra Ujedinitelja, 18000 Niš (Serbia); Despotovic, Milan, E-mail: mdespotovic@kg.ac.rs [Faculty of Engineering, University of Kragujevac, Sestre Janjic 6, 34000 Kragujevac (Serbia); Babic, Sasa, E-mail: babicsf@yahoo.com [College of Applied Mechanical Engineering, Trstenik (Serbia)

    2014-11-15

    Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.

  4. Predicted congestions never occur. On the gap between transport modeling and human behavior

    Directory of Open Access Journals (Sweden)

    Harald FREY

    2011-01-01

    Full Text Available This paper presents an introduction to meso-scale transport modeling and issues of human behaviour in transport systems. Along with other examples of the human ability to learn in transport systems we look at the comparison of real life data and the prediction of modeling tools for the closure of Vienna’s inner ring road during the 2008 European Football Championship (EURO 2008. Some light is shed on the scientific question, whether currently used modeling tools are able to adequately reproduce the real-life behaviour of human beings in the transport system and should be used for transport policy decision making.

  5. Robust, Optimal, Predictive, and Integrated Road Traffic Control : Research proposal

    NARCIS (Netherlands)

    Van de Weg, G.S.; Hegyi, A.; Hoogendoorn, S.P.

    2014-01-01

    The development of control strategies for traffic lights, ramp metering installations, and variable speed limits to improve the throughput of road traffic networks can contribute to a more efficient use of road networks. In this project, a hierarchical controller will be developed for the

  6. Injury risk prediction for traffic accidents in Porto Alegre/RS, Brazil

    OpenAIRE

    Perone, Christian S.

    2015-01-01

    This study describes the experimental application of Machine Learning techniques to build prediction models that can assess the injury risk associated with traffic accidents. This work uses an freely available data set of traffic accident records that took place in the city of Porto Alegre/RS (Brazil) during the year of 2013. This study also provides an analysis of the most important attributes of a traffic accident that could produce an outcome of injury to the people involved in the accident.

  7. Real time driver information for congestion management.

    Science.gov (United States)

    2015-07-01

    Traffic demand in the U.S. has grown substantially over the past few years because of the increase in population and : urbanization in large cities. This causes traffic congestion to spread out over U.S. highways and arterials, and subsequently : lea...

  8. A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

    Science.gov (United States)

    Huang, Darong; Bai, Xing-Rong

    Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

  9. Research on urban road congestion pricing strategy considering carbon dioxide emissions

    NARCIS (Netherlands)

    Wang, Y.; Peng, Z.; Wang, K.; Song, X.; Yao, B.; Feng, T.

    2015-01-01

    Congestion pricing strategy has been recognized as an effective countermeasure in the practical field of urban traffic congestion mitigation. In this paper, a bi-level programming model considering carbon dioxide emission is proposed to mitigate traffic congestion and reduce carbon dioxide

  10. Lagrangian Multi-Class Traffic State Estimation

    NARCIS (Netherlands)

    Yuan, Y.

    2013-01-01

    Road traffic is important to everybody in the world. People travel and commute everyday. For those who travel by cars (or other types of road vehicles), traffic congestion is a daily experience. One essential goal of traffic researchers is to reduce traffic congestion and to improve the whole

  11. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    Directory of Open Access Journals (Sweden)

    Su Yang

    Full Text Available Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1 Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2 The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3 The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

  12. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    Science.gov (United States)

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

  13. Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

    OpenAIRE

    Cui, Zhiyong; Ke, Ruimin; Wang, Yinhai

    2018-01-01

    Short-term traffic forecasting based on deep learning methods, especially long short-term memory (LSTM) neural networks, has received much attention in recent years. However, the potential of deep learning methods in traffic forecasting has not yet fully been exploited in terms of the depth of the model architecture, the spatial scale of the prediction area, and the predictive power of spatial-temporal data. In this paper, a deep stacked bidirectional and unidirectional LSTM (SBU- LSTM) neura...

  14. Developing a stochastic traffic volume prediction model for public-private partnership projects

    Science.gov (United States)

    Phong, Nguyen Thanh; Likhitruangsilp, Veerasak; Onishi, Masamitsu

    2017-11-01

    Transportation projects require an enormous amount of capital investment resulting from their tremendous size, complexity, and risk. Due to the limitation of public finances, the private sector is invited to participate in transportation project development. The private sector can entirely or partially invest in transportation projects in the form of Public-Private Partnership (PPP) scheme, which has been an attractive option for several developing countries, including Vietnam. There are many factors affecting the success of PPP projects. The accurate prediction of traffic volume is considered one of the key success factors of PPP transportation projects. However, only few research works investigated how to predict traffic volume over a long period of time. Moreover, conventional traffic volume forecasting methods are usually based on deterministic models which predict a single value of traffic volume but do not consider risk and uncertainty. This knowledge gap makes it difficult for concessionaires to estimate PPP transportation project revenues accurately. The objective of this paper is to develop a probabilistic traffic volume prediction model. First, traffic volumes were estimated following the Geometric Brownian Motion (GBM) process. Monte Carlo technique is then applied to simulate different scenarios. The results show that this stochastic approach can systematically analyze variations in the traffic volume and yield more reliable estimates for PPP projects.

  15. 交通拥堵条件下的公交发车间隔过渡模型研究%A Bus Departure Time Interval Transition Model Considering Traffic Congestion

    Institute of Scientific and Technical Information of China (English)

    董红召; 孔娟娟; 刘晴辉

    2016-01-01

    The existing planning models of bus departure time interval usually ignored the important impact factor of real-time traffic congestion. To solve the issue, a departure time interval transition method is presented considering passenger travel demand and traffic congestion. The bus operating hours is divided into several temporary periods separately according to the passenger travel demand and the congestion conditions by the clustering method of samples with sequence. Then these temporary periods are combined to form a period set, in which each period possess the features including passenger travel flow and traffic congestion. Consequently, the departure interval transition model is established to adjust the transient time separately between two neighbor periods to match the passenger travel demand and departure plan. Finally a practical experiment for one bus route in Hangzhou is implemented to verify the proposed model by PARAMICS simulation. The result shows that the model can keep the load ratio in the range of 40%to 70%with the precondition of satisfying the passenger travel demand, and help to improve the service level and the efficiency of the bus transit system.%针对现有公交发车间隔模型忽略了交通拥堵状态对公交运营影响的问题,提出了交通拥堵条件下响应客流需求的发车间隔设计方法。采用有序样本聚类方法,分别根据客流需求及交通拥堵状态对时间段进行聚类划分,并融合处理为若干具有不同客流与拥堵状态综合特征的时间段;分析相邻时段综合特征关系,建立了发车间隔的过渡模型,该模型确定发车时段之间的衔接时长,通过调整衔接时间长度将发车序列在时间轴上平移,弥补交通拥堵造成的客流需求与发车计划匹配错位。最后采用杭州市某线路的运营数据对该模型进行了分析验证,PARAMICS交通仿真实验表明,该模型在满足客流需求的前提下使

  16. Internet Congestion Control System

    Directory of Open Access Journals (Sweden)

    Pranoto Rusmin

    2010-10-01

    Full Text Available Internet congestion occurs when resource demands exceeds the network capacity. But, it is not the only reason. Congestion can happen on some users because some others user has higher sending rate. Then some users with lower sending rate will experience congestion. This partial congestion is caused by inexactly feedback. At this moment congestion are solved by the involvement of two controlling mechanisms. These mechanisms are flow/congestion control in the TCP source and Active Queue Management (AQM in the router. AQM will provide feedback to the source a kind of indication for the occurrence of the congestion in the router, whereas the source will adapt the sending rate appropriate with the feedback. These mechanisms are not enough to solve internet congestion problem completely. Therefore, this paper will explain internet congestion causes, weakness, and congestion control technique that researchers have been developed. To describe congestion system mechanisms and responses, the system will be simulated by Matlab.

  17. Predicting Posttraumatic Stress Symptoms in Children after Road Traffic Accidents

    Science.gov (United States)

    Landolt, Markus A.; Vollrath, Margarete; Timm, Karin; Gnehm, Hanspeter E.; Sennhauser, Felix H.

    2005-01-01

    Objective: To prospectively assess the prevalence, course, and predictors of posttraumatic stress symptoms (PTSSs) in children after road traffic accidents (RTAs). Method: Sixty-eight children (6.5-14.5 years old) were interviewed 4-6 weeks and 12 months after an RTA with the Child PTSD Reaction Index (response rate 58.6%). Their mothers (n = 60)…

  18. Proactive Traffic Information Control in Emergency Evacuation Network

    Directory of Open Access Journals (Sweden)

    Zhengfeng Huang

    2015-01-01

    Full Text Available Traffic demand in emergency evacuation is usually too large to be effectively managed with reactive traffic information control methods. These methods adapt to the road traffic passively by publishing real-time information without consideration of the routing behavior feedback produced by evacuees. Other remedy measures have to be prepared in case of nonrecurring congestion under these methods. To use the network capacity fully to mitigate near-future evacuation traffic congestion, we propose proactive traffic information control (PTIC model. Based on the mechanism between information and routing behavior feedback, this model can change the route choice of evacuees in advance by dissipating strategic traffic information. Generally, the near-future traffic condition is difficult to accurately predict because it is uncertain in evacuation. Assume that the value of traffic information obeys certain distribution within a range, and then real-time traffic information may reflect the most-likely near-future traffic condition. Unlike the real-time information, the proactive traffic information is a selection within the range to achieve a desired level of the road network performance index (total system travel time. In the aspect of the solution algorithm, differential equilibrium decomposed optimization (D-EDO is proposed to compare with other heuristic methods. A field study on a road network around a large stadium is used to validate the PTIC.

  19. Model for Predicting Traffic Signs Functional Service Life – The Republic of Croatia Case Study

    Directory of Open Access Journals (Sweden)

    Dario Babić

    2017-06-01

    Full Text Available Traffic signs are the basic elements of communication between the relevant road authorities and road users. They manage, regulate, inform and warn road users to ensure their safe movement throughout transport networks. Traffic signs must be timely visible to all traffic participants in all weather and traffic conditions in order to fulfil their function, which means they must have satisfactory retroreflection properties. This paper presents a research of the deterioration of traffic signs retroreflection. The aim of this article is to develop models that will effectively enable predicting the retroreflection of traffic signs and thus optimize the maintenance activities and replacement of road signs to increase road safety. The research included measurements of retroreflection of retroreflective material Classes I and II (white, red and blue colour and Class III (red and yellow colour. Based on the collected data from the City of Zagreb (Republic of Croatia, the authors developed the models to estimate the functional service life of certain colours and materials used to make traffic signs. Considering that the average coefficient of determination for all the models is between 0.55-0.60, they present an effective tool in the traffic sign maintenance system.

  20. Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones

    Directory of Open Access Journals (Sweden)

    Cuiping Zhang

    2014-01-01

    Full Text Available Traffic safety evaluation for traffic analysis zones (TAZs plays an important role in transportation safety planning and long-range transportation plan development. This paper aims to present a comprehensive analysis of zonal safety evaluation. First, several criteria are proposed to measure the crash risk at zonal level. Then these criteria are integrated into one measure-average hazard index (AHI, which is used to identify unsafe zones. In addition, the study develops a negative binomial regression model to statistically estimate significant factors for the unsafe zones. The model results indicate that the zonal crash frequency can be associated with several social-economic, demographic, and transportation system factors. The impact of these significant factors on zonal crash is also discussed. The finding of this study suggests that safety evaluation and estimation might benefit engineers and decision makers in identifying high crash locations for potential safety improvements.

  1. Predicting and analyzing the trend of traffic accidents deaths in Iran in 2014 and 2015.

    Science.gov (United States)

    Mehmandar, Mohammadreza; Soori, Hamid; Mehrabi, Yadolah

    2016-01-01

    Predicting the trend in traffic accidents deaths and its analysis can be a useful tool for planning and policy-making, conducting interventions appropriate with death trend, and taking the necessary actions required for controlling and preventing future occurrences. Predicting and analyzing the trend of traffic accidents deaths in Iran in 2014 and 2015. It was a cross-sectional study. All the information related to fatal traffic accidents available in the database of Iran Legal Medicine Organization from 2004 to the end of 2013 were used to determine the change points (multi-variable time series analysis). Using autoregressive integrated moving average (ARIMA) model, traffic accidents death rates were predicted for 2014 and 2015, and a comparison was made between this rate and the predicted value in order to determine the efficiency of the model. From the results, the actual death rate in 2014 was almost similar to that recorded for this year, while in 2015 there was a decrease compared with the previous year (2014) for all the months. A maximum value of 41% was also predicted for the months of January and February, 2015. From the prediction and analysis of the death trends, proper application and continuous use of the intervention conducted in the previous years for road safety improvement, motor vehicle safety improvement, particularly training and culture-fostering interventions, as well as approval and execution of deterrent regulations for changing the organizational behaviors, can significantly decrease the loss caused by traffic accidents.

  2. Monitoring and Predicting Traffic Induced Vertebrate Mortality Near Wetlands

    OpenAIRE

    DeWoody, J. Andrew; Nogle, Jamie M.; Hoover, Melissa; Dunning, Barny

    2010-01-01

    Animal-vehicle collisions are undesirable to the general public, to drivers, to insurance providers, to biologists, and presumably to the animals themselves. However, traffic-induced mortality (―roadkill‖) is difficult to mitigate in large part because scientists lack the empirical data required to understand the patterns and processes associated with roadkill. Roadkill is not randomly distributed in space or in time, but what are the primary determinants of roadkill? And do they differ acros...

  3. Sensitivity Analysis of Wavelet Neural Network Model for Short-Term Traffic Volume Prediction

    Directory of Open Access Journals (Sweden)

    Jinxing Shen

    2013-01-01

    Full Text Available In order to achieve a more accurate and robust traffic volume prediction model, the sensitivity of wavelet neural network model (WNNM is analyzed in this study. Based on real loop detector data which is provided by traffic police detachment of Maanshan, WNNM is discussed with different numbers of input neurons, different number of hidden neurons, and traffic volume for different time intervals. The test results show that the performance of WNNM depends heavily on network parameters and time interval of traffic volume. In addition, the WNNM with 4 input neurons and 6 hidden neurons is the optimal predictor with more accuracy, stability, and adaptability. At the same time, a much better prediction record will be achieved with the time interval of traffic volume are 15 minutes. In addition, the optimized WNNM is compared with the widely used back-propagation neural network (BPNN. The comparison results indicated that WNNM produce much lower values of MAE, MAPE, and VAPE than BPNN, which proves that WNNM performs better on short-term traffic volume prediction.

  4. Day-to-day origin-destination tuple estimation and prediction with hierarchical bayesian networks using multiple data sources

    NARCIS (Netherlands)

    Ma, Y.; Kuik, R.; Van Zuylen, H.J.

    2013-01-01

    Prediction of traffic demand is essential, either for an understanding of the future traffic state or so necessary measures can be taken to alleviate congestion. Usually, an origin-destination (O-D) matrix is used to represent traffic demand between two zones in transportation planning. Vehicles are

  5. USAF Enlisted Air Traffic Controller Selection: Examination of the Predictive Validity of the FAA Air Traffic Selection and Training Battery versus Training Performance

    National Research Council Canada - National Science Library

    Carretta, Thomas R; King, Raymond E

    2008-01-01

    .... The current study examined the utility of the FAA Air Traffic Selection and Training (AT-SAT) battery for incrementing the predictiveness of the ASVAB versus several enlisted ATC training criteria...

  6. 3D Markov Process for Traffic Flow Prediction in Real-Time

    Directory of Open Access Journals (Sweden)

    Eunjeong Ko

    2016-01-01

    Full Text Available Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1 a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2 the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further.

  7. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Zhaosheng Yang

    2014-01-01

    Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

  8. Predictive control strategies for energy saving of hybrid electric vehicles based on traffic light information

    Directory of Open Access Journals (Sweden)

    Kaijiang YU

    2015-10-01

    Full Text Available As the conventional control method for hybrid electric vehicle doesn’t consider the effect of known traffic light information on the vehicle energy management, this paper proposes a model predictive control intelligent optimization strategies based on traffic light information for hybrid electric vehicles. By building the simplified model of the hybrid electric vehicle and adopting the continuation/generalized minimum residual method, the model prediction problem is solved. The simulation is conducted by using MATLAB/Simulink platform. The simulation results show the effectiveness of the proposed model of the traffic light information, and that the proposed model predictive control method can improve fuel economy and the real-time control performance significantly. The research conclusions show that the proposed control strategy can achieve optimal control of the vehicle trajectory, significantly improving fuel economy of the vehicle, and meet the system requirements for the real-time optimal control.

  9. Phase diagram distortion from traffic parameter averaging.

    NARCIS (Netherlands)

    Stipdonk, H. Toorenburg, J. van & Postema, M.

    2010-01-01

    Motorway traffic congestion is a major bottleneck for economic growth. Therefore, research of traffic behaviour is carried out in many countries. Although well describing the undersaturated free flow phase as an almost straight line in a (k,q)-phase diagram, congested traffic observations and

  10. Estimating Value of Congestion and of Reliability from Observation of Route Choice Behavior of Car Drivers

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Rasmussen, Thomas Kjær; Nielsen, Otto Anker

    2014-01-01

    In recent years, a consensus has been reached about the relevance of calculating the value of congestion and the value of reliability for better understanding and therefore better prediction of travel behavior. The current study proposed a revealed preference approach that used a large amount...... both congestion and reliability terms. Results illustrated that the value of time and the value of congestion were significantly higher in the peak period because of possible higher penalties for drivers being late and consequently possible higher time pressure. Moreover, results showed...... that the marginal rate of substitution between travel time reliability and total travel time did not vary across periods and traffic conditions, with the obvious caveat that the absolute values were significantly higher for the peak period. Last, results showed the immense potential of exploiting the growing...

  11. Statewide planning scenario synthesis : transportation congestion measurement and management.

    Science.gov (United States)

    2005-09-01

    This study is a review of current practices in 13 states to: (1) measure traffic congestion and its costs; and (2) manage congestion with programs and techniques that do not involve the building of new highway capacity. In regard to the measures of c...

  12. Give or take? Rewards versus charges for a congested bottleneck

    NARCIS (Netherlands)

    Rouwendal, J.; Verhoef, E.T.; Knockaert, J.

    2012-01-01

    This paper analyzes the possibilities to relieve traffic congestion using subsidies instead of Pigouvian taxes, as well as revenue-neutral combinations of rewards and taxes ('feebates'). The model considers a Vickrey-ADL model of bottleneck congestion with endogenous scheduling. With inelastic

  13. SAE for the prediction of road traffic status from taxicab operating data and bus smart card data

    Science.gov (United States)

    Zhengfeng, Huang; Pengjun, Zheng; Wenjun, Xu; Gang, Ren

    Road traffic status is significant for trip decision and traffic management, and thus should be predicted accurately. A contribution is that we consider multi-modal data for traffic status prediction than only using single source data. With the substantial data from Ningbo Passenger Transport Management Sector (NPTMS), we wished to determine whether it was possible to develop Stacked Autoencoders (SAEs) for accurately predicting road traffic status from taxicab operating data and bus smart card data. We show that SAE performed better than linear regression model and Back Propagation (BP) neural network for determining the relationship between road traffic status and those factors. In a 26-month data experiment using SAE, we show that it is possible to develop highly accurate predictions (91% test accuracy) of road traffic status from daily taxicab operating data and bus smart card data.

  14. Understanding congested travel in urban areas

    Science.gov (United States)

    Çolak, Serdar; Lima, Antonio; González, Marta C.

    2016-03-01

    Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings.

  15. The five-point Likert scale for dyspnea can properly assess the degree of pulmonary congestion and predict adverse events in heart failure outpatients

    Directory of Open Access Journals (Sweden)

    Cristina K. Weber

    2014-01-01

    Full Text Available OBJECTIVES: Proper assessment of dyspnea is important in patients with heart failure. Our aim was to evaluate the use of the 5-point Likert scale for dyspnea to assess the degree of pulmonary congestion and to determine the prognostic value of this scale for predicting adverse events in heart failure outpatients. METHODS: We undertook a prospective study of outpatients with moderate to severe heart failure. The 5-point Likert scale was applied during regular outpatient visits, along with clinical assessments. Lung ultrasound with ≥15 B-lines and an amino-terminal portion of pro-B-type natriuretic peptide (NT-proBNP level >1000 pg/mL were used as a reference for pulmonary congestion. The patients were then assessed every 30 days during follow-up to identify adverse clinical outcomes. RESULTS: We included 58 patients (65.5% male, age 43.5±11 years with a mean left ventricular ejection fraction of 27±6%. In total, 29.3% of these patients had heart failure with ischemic etiology. Additionally, pulmonary congestion, as diagnosed by lung ultrasound, was present in 58% of patients. A higher degree of dyspnea (3 or 4 points on the 5-point Likert scale was significantly correlated with a higher number of B-lines (p = 0.016. Patients stratified into Likert = 3-4 were at increased risk of admission compared with those in class 1-2 after adjusting for age, left ventricular ejection fraction, New York Heart Association functional class and levels of NT-proBNP >1000 pg/mL (HR = 4.9, 95% CI 1.33-18.64, p = 0.017. CONCLUSION: In our series, higher baseline scores on the 5-point Likert scale were related to pulmonary congestion and were independently associated with adverse events during follow-up. This simple clinical tool can help to identify patients who are more likely to decompensate and whose treatment should be intensified.

  16. Optimal Tradable Credits Scheme and Congestion Pricing with the Efficiency Analysis to Congestion

    Directory of Open Access Journals (Sweden)

    Ge Gao

    2015-01-01

    Full Text Available We allow for three traffic scenarios: the tradable credits scheme, congestion pricing, and no traffic measure. The utility functions of different modes (car, bus, and bicycle are developed by considering the income’s impact on travelers’ behaviors. Their purpose is to analyze the demand distribution of different modes. A social optimization model is built aiming at maximizing the social welfare. The optimal tradable credits scheme (distribution of credits, credits charging, and the credit price, congestion pricing fees, bus frequency, and bus fare are obtained by solving the model. Mode choice behavior under the tradable credits scheme is also studied. Numerical examples are presented to demonstrate the model’s availability and explore the effects of the three schemes on traffic system’s performance. Results show congestion pricing would earn more social welfare than the other traffic measures. However, tradable credits scheme will give travelers more consumer surplus than congestion pricing. Travelers’ consumer surplus with congestion pricing is the minimum, which injures the travelers’ benefits. Tradable credits scheme is considered the best scenario by comparing the three scenarios’ efficiency.

  17. Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment

    Science.gov (United States)

    2017-12-01

    Traffic incidents have long been recognized as the main contributor to congestion in highway networks. Thus, contending with non-recurrent congestion has been a priority task for most highway agencies over the past decades. Under most incident scenar...

  18. Method for predicting future developments of traffic noise in urban areas in Europe

    NARCIS (Netherlands)

    Salomons, E.; Hout, D. van den; Janssen, S.; Kugler, U.; MacA, V.

    2010-01-01

    Traffic noise in urban areas in Europe is a major environmental stressor. In this study we present a method for predicting how environmental noise can be expected to develop in the future. In the project HEIMTSA scenarios were developed for all relevant environmental stressors to health, for all

  19. Endogenous scheduling preferences and congestion

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Small, Kenneth

    2010-01-01

    and leisure, but agglomeration economies at home and at work lead to scheduling preferences forming endogenously. Using bottleneck congestion technology, we obtain an equilibrium queuing pattern consistent with a general version of the Vickrey bottleneck model. However, the policy implications are different....... Compared to the predictions of an analyst observing untolled equilibrium and taking scheduling preferences as exogenous, we find that both the optimal capacity and the marginal external cost of congestion have changed. The benefits of tolling are greater, and the optimal time varying toll is different....

  20. Prediction of traffic fatalities and prospects for mobility becoming ...

    Indian Academy of Sciences (India)

    edge transfer from developed countries. Four prediction ...... also depends on the average vehicle speed by the dependence of crash avoidance (reaction time, braking .... and political priority of road safety actions. ..... It is a man-made problem.

  1. Congestive index of portal vein

    International Nuclear Information System (INIS)

    Kim, Won Ho; Kim, H. K.; Lee, S. C.; Han, S. H.; Han, K. H.; Chung, J. B.; Choi, H. J.

    1989-01-01

    In patients with portal hypertension, the blood flow volume is maintained despite decreased blood flow velocity due to enlargement of the vascular cross sectional area. Thus, the 'congestion index' of the portal vein, which is the ratio between the cross sectional area (cm2) and the blood flow velocity (cm/sec) determined by a Doppler ultrasonography, may be a sensitive index by which to assess portal hypertension. We performed Doppler ultrasonography on 24 normal subjects, 14 patients with biopsy proved chronic active hepatitis and 55 patients with liver cirrhosis in order to assess the diagnostic value of the congestion index. The cross sectional area of the portal vein was significantly enlarged and the mean blood flow velocity was significantly reduced in patients with liver cirrhosis compared with controls. However, the blood flow volume was no difference. The congestion index of the portal vein was significantly increased in patients with liver cirrhosis (0.113+0.035) compared with patients with chronic active hepatitis(0.078+0.029) (p<0.001) and controls (0.053+0.016) (p<0.001). The sensitivity, specificity and predictability of the congestion index for detection of patients with the cirrhosis of the liver were 76.4%, 100% and 100% respectively, when the normal range was set at mean+2SD. The results suggest that the congestion index of the portal vein may pla a significant role in diagnosis of portal hypertensive patients

  2. Internet congestion control

    CERN Document Server

    Varma, Subir

    2015-01-01

    Internet Congestion Control provides a description of some of the most important topics in the area of congestion control in computer networks, with special emphasis on the analytical modeling of congestion control algorithms. The field of congestion control has seen many notable advances in recent years and the purpose of this book, which is targeted towards the advanced and intermediate reader, is to inform about the most important developments in this area. The book should enable the reader to gain a good understanding of the application of congestion control theory to a number of applic

  3. Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

    Science.gov (United States)

    Mercer, Joey; Hunt-Espinosa, Sarah; Bienert, Nancy; Laraway, Sean

    2016-01-01

    A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

  4. Self-organized natural roads for predicting traffic flow: a sensitivity study

    International Nuclear Information System (INIS)

    Jiang, Bin; Zhao, Sijian; Yin, Junjun

    2008-01-01

    In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a sensitivity study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both annual average daily traffic (AADT) and global positioning system (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our great surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial light on the understanding of road networks and their traffic from the perspective of complex networks

  5. Analysis of Intra-Urban Traffic Problems in Nigeria: A Study of Lagos Metropolis

    Directory of Open Access Journals (Sweden)

    A. Raji Bashiru

    2013-07-01

    local government areas. However, the observed spatial and temporal pattern o.l vehicular traffic congestion enabled us to suggest possible measures for the reduction of traffic congestion within the metropolis.

  6. Using mobile probes to inform and measure the effectiveness of traffic control strategies on urban networks.

    Science.gov (United States)

    2015-07-01

    Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this : congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work ha...

  7. Measuring accessibility and congestion in Accra

    DEFF Research Database (Denmark)

    Møller-Jensen, Lasse; Kofie, Richard Y.; Allotey, Albert N.M.

    2012-01-01

    Based on extensive gps-measurements, the paper addresses the level of intra-urban accessibility and provides indications of the level of congestion in Accra, Ghana. Traffic flows within the urban area are analyzed with respect to speed, time-of-day, direction, road type and land cover type. The s...... and less during off-peak hours. Delays are frequently found within the inner fringe areas. The paper discusses the methodological potentials and barriers for applying gps tracklog points for analysing traffic flows within an urban road network........ The speed information is extrapolated to cover the total mapped urban road net¬work with time- and direction-specific data. A series of time-distance maps are created using network analysis to illustrate the level of accessibility at different times of the day and at different directions relative...... to the city centre. Peak hour traffic speeds are compared with off-peak levels and theoretical free-flow estimations to provide an indica-tion of the level of congestion. It is found that the core areas are somewhat congested during the day period, while the fringe areas are more congested during peak hours...

  8. Vehicle routing under time-dependent travel times: the impact of congestion avoidance

    NARCIS (Netherlands)

    Kok, A.L.; Hans, Elias W.; Schutten, Johannes M.J.

    2009-01-01

    Daily traffic congestions form major problems for businesses such as logistical service providers and distribution firms. They cause late arrivals at customers and additional hiring costs for the truck drivers. The additional costs of traffic congestions can be reduced by taking into account and

  9. Modelling and experimental study for automated congestion driving

    NARCIS (Netherlands)

    Urhahne, Joseph; Piastowski, P.; van der Voort, Mascha C.; Bebis, G; Boyle, R.; Parvin, B.; Koracin, D.; Pavlidis, I.; Feris, R.; McGraw, T.; Elendt, M.; Kopper, R.; Ragan, E.; Ye, Z.; Weber, G.

    2015-01-01

    Taking a collaborative approach in automated congestion driving with a Traffic Jam Assist system requires the driver to take over control in certain traffic situations. In order to warn the driver appropriately, warnings are issued (“pay attention” vs. “take action”) due to a control transition

  10. Bottleneck congestion and distribution of work start times: The economics of staggered work hours revisited

    OpenAIRE

    Takayama, Yuki

    2014-01-01

    Since the seminal work of Henderson (1981), a number of studies examined the effect of staggered work hours by analyzing models of work start time choice that consider the trade-off between negative congestion externalities and positive production externalities. However, these studies described traffic congestion using flow congestion models. This study develops a model of work start time choice with bottleneck congestion and discloses the intrinsic properties of the model. To this end, this ...

  11. An empirical model to predict road dust emissions based on pavement and traffic characteristics.

    Science.gov (United States)

    Padoan, Elio; Ajmone-Marsan, Franco; Querol, Xavier; Amato, Fulvio

    2018-06-01

    The relative impact of non-exhaust sources (i.e. road dust, tire wear, road wear and brake wear particles) on urban air quality is increasing. Among them, road dust resuspension has generally the highest impact on PM concentrations but its spatio-temporal variability has been rarely studied and modeled. Some recent studies attempted to observe and describe the time-variability but, as it is driven by traffic and meteorology, uncertainty remains on the seasonality of emissions. The knowledge gap on spatial variability is much wider, as several factors have been pointed out as responsible for road dust build-up: pavement characteristics, traffic intensity and speed, fleet composition, proximity to traffic lights, but also the presence of external sources. However, no parameterization is available as a function of these variables. We investigated mobile road dust smaller than 10 μm (MF10) in two cities with different climatic and traffic conditions (Barcelona and Turin), to explore MF10 seasonal variability and the relationship between MF10 and site characteristics (pavement macrotexture, traffic intensity and proximity to braking zone). Moreover, we provide the first estimates of emission factors in the Po Valley both in summer and winter conditions. Our results showed a good inverse relationship between MF10 and macro-texture, traffic intensity and distance from the nearest braking zone. We also found a clear seasonal effect of road dust emissions, with higher emission in summer, likely due to the lower pavement moisture. These results allowed building a simple empirical mode, predicting maximal dust loadings and, consequently, emission potential, based on the aforementioned data. This model will need to be scaled for meteorological effect, using methods accounting for weather and pavement moisture. This can significantly improve bottom-up emission inventory for spatial allocation of emissions and air quality management, to select those roads with higher emissions

  12. Increased NT-proANP predicts risk of congestive heart failure in Cavalier King Charles spaniels with mitral regurgitation caused by myxomatous valve disease.

    Science.gov (United States)

    Eriksson, Anders S; Häggström, Jens; Pedersen, Henrik Duelund; Hansson, Kerstin; Järvinen, Anna-Kaisa; Haukka, Jari; Kvart, Clarence

    2014-09-01

    To evaluate the predictive value of plasma N-terminal pro-atrial natriuretic peptide (NT-proANP) and nitric oxide end-products (NOx) as markers for progression of mitral regurgitation caused by myxomatous mitral valve disease. Seventy-eight privately owned Cavalier King Charles spaniels with naturally occurring myxomatous mitral valve disease. Prospective longitudinal study comprising 312 measurements over a 4.5 year period. Clinical values were recorded, NT-proANP concentrations were measured by radioimmunoassay, and NOx were analyzed colorimetrically. To predict congestive heart failure (CHF), Cox proportional hazards models with time-varying covariates were constructed. The hazard ratio for NT-proANP (per 1000 pmol/l increase) to predict future CHF was 6.7 (95% confidence interval, 3.6-12.5; p 1000 pmol/l was 11 months (95% confidence interval, 5.6-12.6 months), compared to 54 months (46 - infinity) for dogs with concentrations ≤ 1000 pmol/l (p 130 beats per minute) and grade of murmur (≥ 3/6). The risk of CHF due to mitral regurgitation is increased in dogs with blood NT-proANP concentrations above 1000 pmol/l. Measurement of NT-proANP can be a valuable tool to identify dogs that may develop CHF within months. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Trajectory Based Traffic Analysis

    DEFF Research Database (Denmark)

    Krogh, Benjamin Bjerre; Andersen, Ove; Lewis-Kelham, Edwin

    2013-01-01

    We present the INTRA system for interactive path-based traffic analysis. The analyses are developed in collaboration with traffic researchers and provide novel insights into conditions such as congestion, travel-time, choice of route, and traffic-flow. INTRA supports interactive point-and-click a......We present the INTRA system for interactive path-based traffic analysis. The analyses are developed in collaboration with traffic researchers and provide novel insights into conditions such as congestion, travel-time, choice of route, and traffic-flow. INTRA supports interactive point......-and-click analysis, due to a novel and efficient indexing structure. With the web-site daisy.aau.dk/its/spqdemo/we will demonstrate several analyses, using a very large real-world data set consisting of 1.9 billion GPS records (1.5 million trajectories) recorded from more than 13000 vehicles, and touching most...

  14. International scale implementation of the CNOSSOS-EU road traffic noise prediction model for epidemiological studies

    International Nuclear Information System (INIS)

    Morley, D.W.; Hoogh, K. de; Fecht, D.; Fabbri, F.; Bell, M.; Goodman, P.S.; Elliott, P.; Hodgson, S.; Hansell, A.L.; Gulliver, J.

    2015-01-01

    The EU-FP7-funded BioSHaRE project is using individual-level data pooled from several national cohort studies in Europe to investigate the relationship of road traffic noise and health. The detailed input data (land cover and traffic characteristics) required for noise exposure modelling are not always available over whole countries while data that are comparable in spatial resolution between different countries is needed for harmonised exposure assessment. Here, we assess the feasibility using the CNOSSOS-EU road traffic noise prediction model with coarser input data in terms of model performance. Starting with a model using the highest resolution datasets, we progressively introduced lower resolution data over five further model runs and compared noise level estimates to measurements. We conclude that a low resolution noise model should provide adequate performance for exposure ranking (Spearman's rank = 0.75; p < 0.001), but with relatively large errors in predicted noise levels (RMSE = 4.46 dB(A)). - Highlights: • The first implementation of CNOSSOS-EU for national scale noise exposure assessment. • Road traffic noise model performance with varying resolution of inputs is assessed. • Model performance is good with low resolution inputs (r_s = 0.75). • This model will be applied in epidemiological studies of European cohorts. - The CNOSSOS-EU road traffic noise model estimates can be used for international scale exposure assessment when parameterised with freely available low resolution covering a large geographic area.

  15. Adaptive traffic signal control with actor-critic methods in a real-world traffic network with different traffic disruption events

    NARCIS (Netherlands)

    Aslani, Mohammad; Mesgari, Mohammad Saadi; Wiering, Marco

    2017-01-01

    The transportation demand is rapidly growing in metropolises, resulting in chronic traffic con-gestions in dense downtown areas. Adaptive traffic signal control as the principle part of in-telligent transportation systems has a primary role to effectively reduce traffic congestion by making a

  16. Congestion, air pollution, and road safety in urban areas

    Energy Technology Data Exchange (ETDEWEB)

    Shefer, Daniel [Department of Urban and Regional Economics and Transport, Technion-Israel Institute of Technology, Haifa (Israel)

    1993-06-01

    The continuous rapid growth in Vehicle Miles Travelled (VMT), coupled with the rapid increase in traffic congestion on highways of virtually every large urban area, explain a major portion of the observed deterioration of urban air quality. To halt this deterioration process and to secure safe and healthy environments and improve the quality of life in our cities, it is paramount to initiate and implement programs which jointly treat traffic congestion, air quality, and road safety. A host of market-based strategies, driven by price mechanisms, have been proposed as the best and most efficient way to decrease traffic congestion and to reduce vehicle emission. Congestion pricing, emission fees, reducing emissions of high polluting vehicles, and introducing more efficient vehicle and/or fuel technologies are not mutually exclusive strategies and therefore they can, and perhaps should, be employed jointly within an overall strategy. In view of the conflicting objectives which may exist between improving urban air quality and reducing road fatalities and traffic congestion, it is of great importance to thoroughly investigate these functional relationships. The results of such studies will help decision makers identify the `socially optimal level of congestion` which will yield the highest net social benefit. 2 figs., 43 refs.

  17. Congestion with incidents

    DEFF Research Database (Denmark)

    Fosgerau, Mogens

    2010-01-01

    This paper considers the impact of random delays during a repeatedly occurring demand peak in a congested facility, such as an airport or an urban road. Congestion is described in the form of a dynamic queue using the Vickrey bottleneck model and assuming Nash equilibrium in departure times. Ever...

  18. Incremental Validity of Biographical Data in the Prediction of En Route Air Traffic Control Specialist Technical Skills

    Science.gov (United States)

    2012-07-01

    Previous research demonstrated that an empirically-keyed, response-option scored biographical data (biodata) : scale predicted supervisory ratings of air traffic control specialist (ATCS) job performance (Dean & Broach, : 2011). This research f...

  19. Big data analytics : predicting traffic flow regimes from simulated connected vehicle messages using data analytics and machine learning.

    Science.gov (United States)

    2016-12-25

    The key objectives of this study were to: 1. Develop advanced analytical techniques that make use of a dynamically configurable connected vehicle message protocol to predict traffic flow regimes in near-real time in a virtual environment and examine ...

  20. Differential Prediction of FAA Academy Performance on the Basis of Race and Written Air Traffic Control Specialist Aptitude Test Scores

    National Research Council Canada - National Science Library

    Broach, Dana

    1999-01-01

    The written air traffic control specialist (ATCS) aptitude test battery was evaluated for evidence of predictive bias within the framework of the Uniform Guidelines on Employee Selection Procedures (29 CFR 1607...

  1. Combined Prediction Model of Death Toll for Road Traffic Accidents Based on Independent and Dependent Variables

    Directory of Open Access Journals (Sweden)

    Feng Zhong-xiang

    2014-01-01

    Full Text Available In order to build a combined model which can meet the variation rule of death toll data for road traffic accidents and can reflect the influence of multiple factors on traffic accidents and improve prediction accuracy for accidents, the Verhulst model was built based on the number of death tolls for road traffic accidents in China from 2002 to 2011; and car ownership, population, GDP, highway freight volume, highway passenger transportation volume, and highway mileage were chosen as the factors to build the death toll multivariate linear regression model. Then the two models were combined to be a combined prediction model which has weight coefficient. Shapley value method was applied to calculate the weight coefficient by assessing contributions. Finally, the combined model was used to recalculate the number of death tolls from 2002 to 2011, and the combined model was compared with the Verhulst and multivariate linear regression models. The results showed that the new model could not only characterize the death toll data characteristics but also quantify the degree of influence to the death toll by each influencing factor and had high accuracy as well as strong practicability.

  2. Combined prediction model of death toll for road traffic accidents based on independent and dependent variables.

    Science.gov (United States)

    Feng, Zhong-xiang; Lu, Shi-sheng; Zhang, Wei-hua; Zhang, Nan-nan

    2014-01-01

    In order to build a combined model which can meet the variation rule of death toll data for road traffic accidents and can reflect the influence of multiple factors on traffic accidents and improve prediction accuracy for accidents, the Verhulst model was built based on the number of death tolls for road traffic accidents in China from 2002 to 2011; and car ownership, population, GDP, highway freight volume, highway passenger transportation volume, and highway mileage were chosen as the factors to build the death toll multivariate linear regression model. Then the two models were combined to be a combined prediction model which has weight coefficient. Shapley value method was applied to calculate the weight coefficient by assessing contributions. Finally, the combined model was used to recalculate the number of death tolls from 2002 to 2011, and the combined model was compared with the Verhulst and multivariate linear regression models. The results showed that the new model could not only characterize the death toll data characteristics but also quantify the degree of influence to the death toll by each influencing factor and had high accuracy as well as strong practicability.

  3. A Two-Stage Fuzzy Logic Control Method of Traffic Signal Based on Traffic Urgency Degree

    OpenAIRE

    Yan Ge

    2014-01-01

    City intersection traffic signal control is an important method to improve the efficiency of road network and alleviate traffic congestion. This paper researches traffic signal fuzzy control method on a single intersection. A two-stage traffic signal control method based on traffic urgency degree is proposed according to two-stage fuzzy inference on single intersection. At the first stage, calculate traffic urgency degree for all red phases using traffic urgency evaluation module and select t...

  4. Problems in air traffic management. VII., Job training performance of air traffic control specialists - measurement, structure, and prediction.

    Science.gov (United States)

    1965-07-01

    A statistical study of training- and job-performance measures of several hundred Air Traffic Control Specialists (ATCS) representing Enroute, Terminal, and Flight Service Station specialties revealed that training-performance measures reflected: : 1....

  5. Using mobile probes to inform and measure the effectiveness of macroscopic traffic control strategies on urban networks.

    Science.gov (United States)

    2015-06-01

    Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this : congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work ha...

  6. A Model for Traffic Accidents Prediction Based on Driver Personality Traits Assessment

    Directory of Open Access Journals (Sweden)

    Marjana Čubranić-Dobrodolac

    2017-12-01

    Full Text Available The model proposed in this paper uses four psychological instruments for assessing driver behaviour and personality traits aiming to find a relationship between the considered constructs and the occurrence of traffic accidents. A Barratt Impulsiveness Scale (BIS-11 was used for the assessment of impulsivity, Aggressive Driving Behaviour Questionnaire (ADBQ for assessing the aggressiveness while driving, Manchester Driver Attitude Questionnaire (DAQ and the Questionnaire for self-assessment of driving ability. Besides these instruments, the participants filled out an extensive demographic survey. Within the statistical analysis, in addition to the descriptive indicators, correlation coefficients were calculated and four hierarchical regression analyses were performed to determine the predictive power of personality traits on the occurrence of traffic accidents. Further, to confirm the results and to obtain additional information about the relationship between the considered variables, the structural equation modelling and binary logistic regression have been implemented. A sample of this research covered 305 drivers, of which there were 100 bus drivers and 102 truck drivers, as well as 103 drivers of privately owned vehicles. The results indicate that BIS-11 and ADBQ questionnaires show the best predictive power which means that impulsivity and aggressiveness as personality traits have the greatest influence on the occurrence of traffic accidents. This research could be useful in many fields, such as the design of selection procedures for professional drivers, development of programs for the prevention of traffic accidents and violations of law, rehabilitation of drivers who have been deprived of the driving license, etc.

  7. Intelligent traffic lights based on MATLAB

    Science.gov (United States)

    Nie, Ying

    2018-04-01

    In this paper, I describes the traffic lights system and it has some. Through analysis, I used MATLAB technology, transformed the camera photographs into digital signals. Than divided the road vehicle is into three methods: very congestion, congestion, a little congestion. Through the MCU programming, solved the different roads have different delay time, and Used this method, saving time and resources, so as to reduce road congestion.

  8. Efficiency of Roundabouts as Compared to Traffic Light Controlled ...

    African Journals Online (AJOL)

    Comparison is made between roundabouts with traffic light and without traffic light and signalized intersections on the basis of their performance to simplify traffic congestion. Computer simulations are used to propose critical arrival rates to separate between the three mentioned modes to decrease congestion at intersection ...

  9. Developing Policy for Urban Autonomous Vehicles: Impact on Congestion

    Directory of Open Access Journals (Sweden)

    David Metz

    2018-04-01

    Full Text Available An important problem for surface transport is road traffic congestion, which is ubiquitous and difficult to mitigate. Accordingly, a question for policymakers is the possible impact on congestion of autonomous vehicles. It seems likely that the main impact of vehicle automation will not be seen until driverless vehicles are sufficiently safe for use amid general traffic on urban streets. Shared use driverless vehicles could reduce the cost of taxis and a wider range of public transport vehicles could be economic. Individually owned autonomous vehicles would have the ability to travel unoccupied and may need to be regulated where this might add to congestion. It is possible that autonomous vehicles could provide mobility services at lower cost and wider scope, such that private car use in urban areas could decline and congestion reduce. City authorities should be alert to these possibilities in developing transport policy.

  10. Software-Defined Congestion Control Algorithm for IP Networks

    Directory of Open Access Journals (Sweden)

    Yao Hu

    2017-01-01

    Full Text Available The rapid evolution of computer networks, increase in the number of Internet users, and popularity of multimedia applications have exacerbated the congestion control problem. Congestion control is a key factor in ensuring network stability and robustness. When the underlying network and flow information are unknown, the transmission control protocol (TCP must increase or reduce the size of the congestion window to adjust to the changes of traffic in the Internet Protocol (IP network. However, it is possible that a software-defined approach can relieve the network congestion problem more efficiently. This approach has the characteristic of centralized control and can obtain a global topology for unified network management. In this paper, we propose a software-defined congestion control (SDCC algorithm for an IP network. We consider the difference between TCP and the user datagram protocol (UDP and propose a new method to judge node congestion. We initially apply the congestion control mechanism in the congested nodes and then optimize the link utilization to control network congestion.

  11. How Smog Awareness Influences Public Acceptance of Congestion Charge Policies

    OpenAIRE

    Lingyi Zhou; Yixin Dai

    2017-01-01

    Although various studies have investigated public acceptance of congestion charge policies, most of them have focused on behavioral and policy-related factors, and did not consider the moderating influence that individual concern about smog and perceived smog risk may have on public acceptance. This paper takes the congestion charge policy in China, targeted at smog and traffic control, and checks how smog awareness—including smog concerns and perceived smog risks, besides behavioral and poli...

  12. Comparative Study on New AQM Mechanisms for Congestion Control

    Directory of Open Access Journals (Sweden)

    Ramakrishna B B

    2013-09-01

    Full Text Available As usage of network goes increasing day by day, managing network traffic becomes a very difficult task. It is important to avoid high packet loss rates in the Internet. Congestion is the one of the major issue in the present networks. Congestion Control is one of the solutions adopted to solve the congestion issue and to control it. Numbers of queue management algorithms are proposed for congestion control and to reduce high packet loss rates. Active Queue Management (AQM is one such mechanism which provides better control over congestion. In this paper a study is made on recent load based AQM techniques that are proposed and its merits and shortfall is presented.

  13. An LTE implementation based on a road traffic density model

    OpenAIRE

    Attaullah, Muhammad

    2013-01-01

    The increase in vehicular traffic has created new challenges in determining the behavior of performance of data and safety measures in traffic. Hence, traffic signals on intersection used as cost effective and time saving tools for traffic management in urban areas. But on the other hand the signalized intersections in congested urban areas are the key source of high traffic density and slow traffic. High traffic density causes the slow network traffic data rate between vehicle to vehicle and...

  14. Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models

    Directory of Open Access Journals (Sweden)

    Cheng Xu

    2015-01-01

    Full Text Available Free flow speed is a fundamental measure of traffic performance and has been found to affect the severity of crash risk. However, the previous studies lack analysis and modelling of impact factors on bicycles’ free flow speed. The main focus of this study is to develop multilayer back propagation artificial neural network (BPANN models for the prediction of free flow speed and crash risk on the separated bicycle path. Four different models with considering different combinations of input variables (e.g., path width, traffic condition, bicycle type, and cyclists’ characteristics were developed. 459 field data samples were collected from eleven bicycle paths in Hangzhou, China, and 70% of total samples were used for training, 15% for validation, and 15% for testing. The results show that considering the input variables of bicycle types and characteristics of cyclists will effectively improve the accuracy of the prediction models. Meanwhile, the parameters of bicycle types have more significant effect on predicting free flow speed of bicycle compared to those of cyclists’ characteristics. The findings could contribute for evaluation, planning, and management of bicycle safety.

  15. A comprehensive model for the prediction of vibrations due to underground railway traffic: formulation and validation

    International Nuclear Information System (INIS)

    Costa, Pedro Alvares; Cardoso Silva, Antonio; Calçada, Rui; Lopes, Patricia; Fernandez, Jesus

    2016-01-01

    n this communication, a numerical approach for the prediction of vibrations induced in buildings due to railway traffic in tunnels is presented. The numerical model is based on the concept of dynamic sub structuring, being composed by three autonomous models to simulate the following main parts of the problem: i) generation of vibrations (train-track interaction); ii) propagation of vibrations (track - tunnel-ground system); iii) reception of vibrations (building coupled to the ground). The methodology proposed allows dealing with the three-dimensional characteristics of the problem with a reasonable computational effort [ 1 , 2 ] . After the brief description of the model, its experimental validation is performed. For that, a case study about vibrations inside of a building close to a shallow railway tunnel in Madrid are simulated and the experimental data [ 3 ] is compared with the predicted results [ 4 ]. Finally, the communication finishes with some insights about the potentialities and challenges of this numerical modelling approach on the prediction of the behavior of ancient structures subjected to vibrations induced by human sources (railway and road traffic, pile driving, etc)

  16. Traffic Incident Clearance Time and Arrival Time Prediction Based on Hazard Models

    Directory of Open Access Journals (Sweden)

    Yang beibei Ji

    2014-01-01

    Full Text Available Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an effective input for travel time prediction. In this paper, the hazard based prediction models are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

  17. Intelligent Traffic Quantification System

    Science.gov (United States)

    Mohanty, Anita; Bhanja, Urmila; Mahapatra, Sudipta

    2017-08-01

    Currently, city traffic monitoring and controlling is a big issue in almost all cities worldwide. Vehicular ad-hoc Network (VANET) technique is an efficient tool to minimize this problem. Usually, different types of on board sensors are installed in vehicles to generate messages characterized by different vehicle parameters. In this work, an intelligent system based on fuzzy clustering technique is developed to reduce the number of individual messages by extracting important features from the messages of a vehicle. Therefore, the proposed fuzzy clustering technique reduces the traffic load of the network. The technique also reduces congestion and quantifies congestion.

  18. Traffic light control by multiagent reinforcement learning systems

    NARCIS (Netherlands)

    Bakker, B.; Whiteson, S.; Kester, L.; Groen, F.C.A.; Babuška, R.; Groen, F.C.A.

    2010-01-01

    Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of

  19. Traffic Light Control by Multiagent Reinforcement Learning Systems

    NARCIS (Netherlands)

    Bakker, B.; Whiteson, S.; Kester, L.J.H.M.; Groen, F.C.A.

    2010-01-01

    Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of

  20. Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

    Directory of Open Access Journals (Sweden)

    Laisen Nie

    2018-01-01

    Full Text Available Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low-pass component. Otherwise, for the remaining high-pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

  1. Desk Congest Desktop Congesting Software for Desktop Clutter Congestion

    Directory of Open Access Journals (Sweden)

    Solomon A. Adepoju

    2015-06-01

    Full Text Available Abstract The computer desktop environment is a working environment which can be likened unto a users desk in homes and offices. Often times the computer desktop get cluttered with files either as shortcuts used for quick links files stored temporarily to be accessed later or just being dumped there for no vivid reasons. However previous researches have shown that cluttered desktop affects users productivity and getting these files organized is a laborious task for most users. To be able to conveniently alleviate the effect clutters have on users performances and productivity there is need for third party software that will help get the desktop environment organized in a logical and efficient manner. It is to this end that desktop decongesting software is being designed and implemented to help curb clutter problems which existing tools have only partially addressed. The system is designed using Visual Basic .Net and it proves to be effective in tackling desktop congestion problem.

  2. Influence of Traffic Vehicles Against Ground Fundamental Frequency Prediction using Ambient Vibration Technique

    Science.gov (United States)

    Kamarudin, A. F.; Noh, M. S. Md; Mokhatar, S. N.; Anuar, M. A. Mohd; Ibrahim, A.; Ibrahim, Z.; Daud, M. E.

    2018-04-01

    Ambient vibration (AV) technique is widely used nowadays for ground fundamental frequency prediction. This technique is easy, quick, non-destructive, less operator required and reliable result. The input motions of ambient vibration are originally collected from surrounding natural and artificial excitations. But, careful data acquisition controlled must be implemented to reduce the intrusion of short period noise that could imply the quality of frequency prediction of an investigated site. In this study, investigation on the primary noise intrusion under peak (morning, afternoon and evening) and off peak (early morning) traffic flows (only 8 meter from sensor to road shoulder) against the stability and quality of ground fundamental frequency prediction were carried out. None of specific standard is available for AV data acquisition and processing. Thus, some field and processing parameters recommended by previous studies and guideline were considered. Two units of 1 Hz tri-axial seismometer sensor were closely positioned in front of the main entrance Universiti Tun Hussein Onn Malaysia. 15 minutes of recording length were taken during peak and off peak periods of traffic flows. All passing vehicles were counted and grouped into four classes. Three components of ambient vibration time series recorded in the North-South: NS, East-West: EW and vertical: UD directions were automatically computed into Horizontal to Vertical Spectral Ratio (HVSR), by using open source software of GEOPSY for fundamental ground frequency, Fo determination. Single sharp peak pattern of HVSR curves have been obtained at peak frequencies between 1.33 to 1.38 Hz which classified under soft to dense soil classification. Even identical HVSR curves pattern with close frequencies prediction were obtained under both periods of AV measurement, however the total numbers of stable and quality windows selected for HVSR computation were significantly different but both have satisfied the requirement

  3. Research on Urban Road Congestion Pricing Strategy Considering Carbon Dioxide Emissions

    Directory of Open Access Journals (Sweden)

    Yitian Wang

    2015-08-01

    Full Text Available Congestion pricing strategy has been recognized as an effective countermeasure in the practical field of urban traffic congestion mitigation. In this paper, a bi-level programming model considering carbon dioxide emission is proposed to mitigate traffic congestion and reduce carbon dioxide emissions. The objective function of the upper level model is to minimize the sum of travel costs and the carbon dioxide emissions costs. The lower level is a multi-modal transportation network equilibrium model. To solve the model, the method of successive averages (MSA and the shuffled frog leaping algorithm (SFLA are introduced. The proposed method and algorithm are tested through the numerical example. The results show that the proposed congestion pricing strategy can mitigate traffic congestion and reduce carbon emissions effectively.

  4. A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    Full Text Available Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS. Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM is proposed based on singular spectrum analysis (SSA and kernel extreme learning machine (KELM. SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

  5. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

    Science.gov (United States)

    Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

    2017-04-10

    This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

  6. Accurate Traffic Flow Prediction in Heterogeneous Vehicular Networks in an Intelligent Transport System Using a Supervised Non-Parametric Classifier

    Directory of Open Access Journals (Sweden)

    Hesham El-Sayed

    2018-05-01

    Full Text Available Heterogeneous vehicular networks (HETVNETs evolve from vehicular ad hoc networks (VANETs, which allow vehicles to always be connected so as to obtain safety services within intelligent transportation systems (ITSs. The services and data provided by HETVNETs should be neither interrupted nor delayed. Therefore, Quality of Service (QoS improvement of HETVNETs is one of the topics attracting the attention of researchers and the manufacturing community. Several methodologies and frameworks have been devised by researchers to address QoS-prediction service issues. In this paper, to improve QoS, we evaluate various traffic characteristics of HETVNETs and propose a new supervised learning model to capture knowledge on all possible traffic patterns. This model is a refinement of support vector machine (SVM kernels with a radial basis function (RBF. The proposed model produces better results than SVMs, and outperforms other prediction methods used in a traffic context, as it has lower computational complexity and higher prediction accuracy.

  7. Prediction based active ramp metering control strategy with mobility and safety assessment

    Science.gov (United States)

    Fang, Jie; Tu, Lili

    2018-04-01

    Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

  8. Local empathy provides global minimization of congestion in communication networks

    Science.gov (United States)

    Meloni, Sandro; Gómez-Gardeñes, Jesús

    2010-11-01

    We present a mechanism to avoid congestion in complex networks based on a local knowledge of traffic conditions and the ability of routers to self-coordinate their dynamical behavior. In particular, routers make use of local information about traffic conditions to either reject or accept information packets from their neighbors. We show that when nodes are only aware of their own congestion state they self-organize into a hierarchical configuration that delays remarkably the onset of congestion although leading to a sharp first-order-like congestion transition. We also consider the case when nodes are aware of the congestion state of their neighbors. In this case, we show that empathy between nodes is strongly beneficial to the overall performance of the system and it is possible to achieve larger values for the critical load together with a smooth, second-order-like, transition. Finally, we show how local empathy minimize the impact of congestion as much as global minimization. Therefore, here we present an outstanding example of how local dynamical rules can optimize the system’s functioning up to the levels reached using global knowledge.

  9. Congestion Quantification Using the National Performance Management Research Data Set

    Directory of Open Access Journals (Sweden)

    Virginia P. Sisiopiku

    2017-11-01

    Full Text Available Monitoring of transportation system performance is a key element of any transportation operation and planning strategy. Estimation of dependable performance measures relies on analysis of large amounts of traffic data, which are often expensive and difficult to gather. National databases can assist in this regard, but challenges still remain with respect to data management, accuracy, storage, and use for performance monitoring. In an effort to address such challenges, this paper showcases a process that utilizes the National Performance Management Research Data Set (NPMRDS for generating performance measures for congestion monitoring applications in the Birmingham region. The capabilities of the relational database management system (RDBMS are employed to manage the large amounts of NPMRDS data. Powerful visual maps are developed using GIS software and used to illustrate congestion location, extent and severity. Travel time reliability indices are calculated and utilized to quantify congestion, and congestion intensity measures are developed and employed to rank and prioritize congested segments in the study area. The process for managing and using big traffic data described in the Birmingham case study is a great example that can be replicated by small and mid-size Metropolitan Planning Organizations to generate performance-based measures and monitor congestion in their jurisdictions.

  10. A NEW CONGESTION MANAGEMENT MECHANISM FOR NEXT GENERATION ROUTERS

    Directory of Open Access Journals (Sweden)

    MOHAMMED M. KADHUM

    2008-12-01

    Full Text Available While computer networks go towards dealing with varied traffic types with different service requirements, there is a necessity for modern network control mechanisms that can control the network traffic to meet the users' service requirements. Optimizing the network utilization by improving the network performance can help to accommodate more users and thus increase operators’ profits. Controlling the congestion at the gateway leads to better performance of the network. Sending congestion signal sooner can be of great benefit to the TCP connection. In this paper, we propose Fast Congestion Notification (FCN mechanism which is a new method for managing the gateway queues and fast sending of congestion signal to the sender. We tested our mechanism on Explicit Congestion Notification (ECN packets which have higher priority; we achieved good results in terms of faster congestion signal propagation and better network utilization. Our analysis and simulations results show that the use of FCN over TCP connections sharing one bottleneck can improve the throughput, having less loss, less delay time, and better network utilization.

  11. Development of a Traffic Management Decision Support Tool for Freeway Incident Traffic Management (FITM) Plan Deployment : Research Summary

    Science.gov (United States)

    2017-12-01

    In designing an effective traffic management plan for non-recurrent congestion, it is critical for responsible highway agencies to have some vital information, such as estimated incident duration, resulting traffic queues, and the expected delays. Ov...

  12. Characterizing the tradeoffs and costs associated with transportation congestion in supply chains.

    Science.gov (United States)

    2010-01-21

    We consider distribution and location-planning models for supply chains that explicitly : account for traffic congestion effects. The majority of facility location and transportation : planning models in the operations research literature consider fa...

  13. Alleviate Cellular Congestion Through Opportunistic Trough Filling

    Directory of Open Access Journals (Sweden)

    Yichuan Wang

    2014-04-01

    Full Text Available The demand for cellular data service has been skyrocketing since the debut of data-intensive smart phones and touchpads. However, not all data are created equal. Many popular applications on mobile devices, such as email synchronization and social network updates, are delay tolerant. In addition, cellular load varies significantly in both large and small time scales. To alleviate network congestion and improve network performance, we present a set of opportunistic trough filling schemes that leverage the time-variation of network congestion and delay-tolerance of certain traffic in this paper. We consider average delay, deadline, and clearance time as the performance metrics. Simulation results show promising performance improvement over the standard schemes. The work shed lights on addressing the pressing issue of cellular overload.

  14. Performance of FHWA model for predicting traffic noise: a case study of metropolitan city, Lucknow (India

    Directory of Open Access Journals (Sweden)

    J. B. Srivastava

    2009-09-01

    Full Text Available Industrial and transport activities are the two major sources of noise pollution in any metropolitan city. Lucknow city, the capital of the largest populated state Uttar Pradesh in India has an area of 310 sq. km and is rapidly growing as a commercial, industrial and trading centre of northern India. The population of Lucknow city as per census 2001 is 22.45 Lacs. It is expected that by the year 2021 it will make 45 Lacs. The total vehicle population in Lucknow city on 31 March 2008, was nearly 1 million with almost 80% two wheelers, 12% cars, 1.36% three wheelers, 0.45% buses etc. A study was carried out to assess the existing status of noise levels and its impacts on the environment with a possibility of further expansion of the city. Ambient noise levels were measured at different locations selected on the basis of land use such as silence, heavy traffic and residential and commercial zones. It was found that noise levels at all selected locations were much higher (75–90 dB than the prescribed limits. The observed traffic volume and data on road geometry were used to predict noise levels using Federal Highway Administration Agency (FHWA model and the calculated noise levels were compared with the observed levels for checking the suitability of this model for predicting the future levels. It was established that the results obtained by FHWA model were very close to the observed noise levels and that the model was suitable to be used for other similar metropolitan cities in India.

  15. Mathematic Modeling and Performance Analysis of an Adaptive Congestion Control in Intelligent Transportation Systems

    OpenAIRE

    Naja, Rola; Université de Versailles

    2015-01-01

    In this paper, we develop a preventive congestion control mechanism applied at highway entrances and devised for Intelligent Transportation Systems (ITS). The proposed mechanism provides a vehicular admission control, regulates input traffic and performs vehicular traffic shaping. Our congestion control mechanism includes two classes of vehicles and is based on a specific priority ticket pool scheme with queue-length threshold scheduling policy, tailored to vehicular networks. In an attempt t...

  16. Performance analysis of SS7 congestion controls under sustained overload

    Science.gov (United States)

    Manfield, David R.; Millsteed, Gregory K.; Zukerman, Moshe

    1994-04-01

    Congestion controls are a key factor in achieving the robust performance required of common channel signaling (CCS) networks in the face of partial network failures and extreme traffic loads, especially as networks become large and carry high traffic volume. The CCITT recommendations define a number of types of congestion control, and the parameters of the controls must be well set in order to ensure their efficacy under transient and sustained signalling network overload. The objective of this paper is to present a modeling approach to the determination of the network parameters that govern the performance of the SS7 congestion controls under sustained overload. Results of the investigation by simulation are presented and discussed.

  17. Indicators for traffic safety assessment and prediction and their application in micro-simulation modelling : a study of urban and suburban intersections

    OpenAIRE

    Archer, Jeffery

    2005-01-01

    In order to achieve sustainable long-term transport infrastructure development, there is a growing need for fast, reliable and effective methods to evaluate and predict the impact of traffic safety measures. Recognising this need, and the need for an active traffic safety approach, this thesis focuses on traffic safety assessment and prediction based on the use of safety indicators that measure the spatial and/or temporal proximity of safety critical events. The main advantage of such measure...

  18. CONGESTION AS A RESULT OF SCHOOL AND SHOPPING CENTER ACTIVITY

    Directory of Open Access Journals (Sweden)

    Meike Kumaat

    2015-12-01

    Full Text Available Development of land use in public facilities such as shopping center and school gives an impact on transportation problem in Manado City, North Sulawesi.  To determine factors which have causal relationship with congestion  as a result of school and shopping center activity then it need to be assessed and studied.  Descriptive study with observational survey was used in this study. The study ran Structural Equation Modelling (SEM by using AMOS program. Estimated method was used to calculate sample size then found 300 repondents, comprised : visitors and mall managers, school visitors, parents, school managers, Public Works department, and urban planning department .The study yielded a statistically significant correlation between  school and shopping center activity with congestion s. The result  indicated that school activity was positively related to congestion with p value  at p=0,000 (p ≤ 0,05. Shopping center activity was positively related to congestion with p value  at p=0,000 (p ≤ 0,05. The closer proximity from school to shooping center will causes severe traffic congestion. The relationship between school facility with proximity was found in p value at  p=0,000 (p ≤ 0,05 . The relationship between shopping center facility with proximity was found in p value at  p= 0,020 (p ≤ 0,05. While, the relationship between proximity with congestion was p= 0,008 (p ≤ 0,05. Monastery school and Mega Mall activity were affecting congestion because a closer proximity of two facilities. This indicates that the occurence of traffic congestion in Monastery School  may be dependent on existence of  Piere Tendean road link

  19. Controlling chaos in Internet congestion control model

    International Nuclear Information System (INIS)

    Chen Liang; Wang Xiaofan; Han Zhengzhi

    2004-01-01

    The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which may create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we propose a time-dependent delayed feedback control algorithm to control chaos in the system by perturbing the accessible RED parameter p max . This method is able to stabilized a router queue occupancy at a level without knowing the exact knowledge of the network. Further, we study the situation of the presence of the UDP traffic

  20. Controlling chaos in Internet congestion control model

    Energy Technology Data Exchange (ETDEWEB)

    Chen Liang E-mail: chenmoon110@yahoo.com.cn; Wang Xiaofan; Han Zhengzhi

    2004-07-01

    The TCP end-to-end congestion control plus RED router queue management can be modeled as a discrete-time dynamical system, which may create complex bifurcating and chaotic behavior. Based on the basic features of the TCP-RED model, we propose a time-dependent delayed feedback control algorithm to control chaos in the system by perturbing the accessible RED parameter p{sub max}. This method is able to stabilized a router queue occupancy at a level without knowing the exact knowledge of the network. Further, we study the situation of the presence of the UDP traffic.

  1. Predicting long-term average concentrations of traffic-related air pollutants using GIS-based information

    Science.gov (United States)

    Hochadel, Matthias; Heinrich, Joachim; Gehring, Ulrike; Morgenstern, Verena; Kuhlbusch, Thomas; Link, Elke; Wichmann, H.-Erich; Krämer, Ursula

    Global regression models were developed to estimate individual levels of long-term exposure to traffic-related air pollutants. The models are based on data of a one-year measurement programme including geographic data on traffic and population densities. This investigation is part of a cohort study on the impact of traffic-related air pollution on respiratory health, conducted at the westerly end of the Ruhr-area in North-Rhine Westphalia, Germany. Concentrations of NO 2, fine particle mass (PM 2.5) and filter absorbance of PM 2.5 as a marker for soot were measured at 40 sites spread throughout the study region. Fourteen-day samples were taken between March 2002 and March 2003 for each season and site. Annual average concentrations for the sites were determined after adjustment for temporal variation. Information on traffic counts in major roads, building densities and community population figures were collected in a geographical information system (GIS). This information was used to calculate different potential traffic-based predictors: (a) daily traffic flow and maximum traffic intensity of buffers with radii from 50 to 10 000 m and (b) distances to main roads and highways. NO 2 concentration and PM 2.5 absorbance were strongly correlated with the traffic-based variables. Linear regression prediction models, which involved predictors with radii of 50 to 1000 m, were developed for the Wesel region where most of the cohort members lived. They reached a model fit ( R2) of 0.81 and 0.65 for NO 2 and PM 2.5 absorbance, respectively. Regression models for the whole area required larger spatial scales and reached R2=0.90 and 0.82. Comparison of predicted values with NO 2 measurements at independent public monitoring stations showed a satisfactory association ( r=0.66). PM 2.5 concentration, however, was only slightly correlated and thus poorly predictable by traffic-based variables ( rGIS-based regression models offer a promising approach to assess individual levels of

  2. From Goods to Traffic:First Steps Toward an Auction-based Traffic Signal Controller

    OpenAIRE

    Raphael, Jeffery; Maskell, Simon; Sklar, Elizabeth Ida

    2015-01-01

    Traffic congestion is a major issue that plagues many urban road networks large and small. Traffic engineers are now leaning towards Intelligent Traffic Systems as many physical changes to road networks are costly or infeasible. Multi-Agent Systems (MAS) have become a popular paradigm for intelligent solutions to traffic management problems. There are many MAS approaches to traffic management that utilise market mechanisms. In market-based approaches, drivers “pay” to use the roadways. Howeve...

  3. A study of modelling simplifications in ground vibration predictions for railway traffic at grade

    Science.gov (United States)

    Germonpré, M.; Degrande, G.; Lombaert, G.

    2017-10-01

    Accurate computational models are required to predict ground-borne vibration due to railway traffic. Such models generally require a substantial computational effort. Therefore, much research has focused on developing computationally efficient methods, by either exploiting the regularity of the problem geometry in the direction along the track or assuming a simplified track structure. This paper investigates the modelling errors caused by commonly made simplifications of the track geometry. A case study is presented investigating a ballasted track in an excavation. The soil underneath the ballast is stiffened by a lime treatment. First, periodic track models with different cross sections are analyzed, revealing that a prediction of the rail receptance only requires an accurate representation of the soil layering directly underneath the ballast. A much more detailed representation of the cross sectional geometry is required, however, to calculate vibration transfer from track to free field. Second, simplifications in the longitudinal track direction are investigated by comparing 2.5D and periodic track models. This comparison shows that the 2.5D model slightly overestimates the track stiffness, while the transfer functions between track and free field are well predicted. Using a 2.5D model to predict the response during a train passage leads to an overestimation of both train-track interaction forces and free field vibrations. A combined periodic/2.5D approach is therefore proposed in this paper. First, the dynamic axle loads are computed by solving the train-track interaction problem with a periodic model. Next, the vibration transfer to the free field is computed with a 2.5D model. This combined periodic/2.5D approach only introduces small modelling errors compared to an approach in which a periodic model is used in both steps, while significantly reducing the computational cost.

  4. Congestion-Aware Warehouse Flow Analysis and Optimization

    KAUST Repository

    AlHalawani, Sawsan

    2015-12-18

    Generating realistic configurations of urban models is a vital part of the modeling process, especially if these models are used for evaluation and analysis. In this work, we address the problem of assigning objects to their storage locations inside a warehouse which has a great impact on the quality of operations within a warehouse. Existing storage policies aim to improve the efficiency by minimizing travel time or by classifying the items based on some features. We go beyond existing methods as we analyze warehouse layout network in an attempt to understand the factors that affect traffic within the warehouse. We use simulated annealing based sampling to assign items to their storage locations while reducing traffic congestion and enhancing the speed of order picking processes. The proposed method enables a range of applications including efficient storage assignment, warehouse reliability evaluation and traffic congestion estimation.

  5. Congestion-Aware Warehouse Flow Analysis and Optimization

    KAUST Repository

    AlHalawani, Sawsan; Mitra, Niloy J.

    2015-01-01

    Generating realistic configurations of urban models is a vital part of the modeling process, especially if these models are used for evaluation and analysis. In this work, we address the problem of assigning objects to their storage locations inside a warehouse which has a great impact on the quality of operations within a warehouse. Existing storage policies aim to improve the efficiency by minimizing travel time or by classifying the items based on some features. We go beyond existing methods as we analyze warehouse layout network in an attempt to understand the factors that affect traffic within the warehouse. We use simulated annealing based sampling to assign items to their storage locations while reducing traffic congestion and enhancing the speed of order picking processes. The proposed method enables a range of applications including efficient storage assignment, warehouse reliability evaluation and traffic congestion estimation.

  6. Congestion control in wireless links based on selective delivery of erroneous packets

    DEFF Research Database (Denmark)

    Korhonen, Jari; Perkis, Andrew; Reiter, Ulrich

    2011-01-01

    Traditionally, congestion control in packet networks is performed by reducing the transmission rate when congestion is detected, in order to cut down the traffic that overwhelms the capacity of the network. However, if the bottleneck is a wireless link, congestion is often cumulated because...... the performance of the proposed mechanism against traditional congestion control with a simulation study. The results show that the proposed approach can improve the overall performance both by increasing the throughput over the wireless and improving the video quality in terms of peak signal-to-noise ratio (PSNR...

  7. Dynamic traffic assignment : genetic algorithms approach

    Science.gov (United States)

    1997-01-01

    Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...

  8. Signal Control for Reducing Vehicle NOx and CO2 Emissions Based on Prediction of Arrival Traffic Flows at Intersections

    Science.gov (United States)

    Oda, Toshihiko

    Nitrogen oxide (NOx) and carbon dioxide (CO2) emissions from vehicles have been increasing every year because of the growing number of vehicles, and they cause serious environmental problems such as air pollution and global warming. To alleviate these problems, this paper proposes a new traffic signal control method for reducing vehicle NOx and CO2 emissions on arterial roads. To this end, we first model the amount of vehicle emissions as a function of the traffic delay and the number of stops at intersections. This step is necessary because it is difficult to obtain the amount of emissions directly using traffic control systems. Second, we introduce a signal control model in which the control parameters are continuously updated on the basis of predictions of arrival traffic flows at intersections. The signal timings are calculated in such a manner so as to minimize the weighted sum of the two emissions, which depend on the traffic flow. To evaluate the validity of this method, simulation experiments are carried out on an arterial road. The experiments show that the proposed method significantly outperforms existing methods in reducing both the emissions and travel time.

  9. Decisions of hypermarkets location in dense urban area – effects on streets network congestion in the Bucharest case

    Directory of Open Access Journals (Sweden)

    Eugen ROSCA

    2008-01-01

    Full Text Available The paper represents some partial results of the research carried out by the Transportation, Traffic and Logistics Department - University POLITEHNICA of Bucharest, funded by the Romanian Ministry of Research and Education through the National University Research Council. In this paper we provide: a brief description of the interrelation between the life style changes of Romanian people during the last decades and the car traffic congestion in large cities; the streets network modelling of a radial-circular urban structure (the characteristic of a historically developed city as Bucharest city is, in case of car traffic congestion; the assessment model of the additional car traffic congestion for certain locations with large attractivity. Having an important effect on the entire lifestyle of urban people, the decision of a hypermarket location might be a complex one, taking into consideration the new leisure and shopping tendencies but also the additional car traffic congestion caused by the chosen location.

  10. Visual Analysis of Air Traffic Data

    Science.gov (United States)

    Albrecht, George Hans; Pang, Alex

    2012-01-01

    In this paper, we present visual analysis tools to help study the impact of policy changes on air traffic congestion. The tools support visualization of time-varying air traffic density over an area of interest using different time granularity. We use this visual analysis platform to investigate how changing the aircraft separation volume can reduce congestion while maintaining key safety requirements. The same platform can also be used as a decision aid for processing requests for unmanned aerial vehicle operations.

  11. Traffic Responsive Control of Intersections with Predicted Arrival Times: A Markovian Approach

    NARCIS (Netherlands)

    Haijema, R.; Hendrix, E.M.T.

    2014-01-01

    The dynamic adaptive control of traffic lights can be formulated as a Markov decision problem (MDP). This framework is hardly used, as solving an MDP can be very time-consuming and is only possible for simple infrastructures with a small number of traffic flows. Nevertheless, we show that the MDP

  12. An Adaptive Traffic Signal Control in a Connected Vehicle Environment: A Systematic Review

    OpenAIRE

    Peng Jing; Hao Huang; Long Chen

    2017-01-01

    In the last few years, traffic congestion has become a growing concern due to increasing vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic signal control systems cannot adjust the timing pattern depending on road traffic demand. This results in excessive delays for road users. Adaptive traffic signal control in a connected vehicle environment has shown a powerful ability to effectively alleviate u...

  13. Predicting traffic volumes and estimating the effects of shocks in massive transportation systems.

    Science.gov (United States)

    Silva, Ricardo; Kang, Soong Moon; Airoldi, Edoardo M

    2015-05-05

    Public transportation systems are an essential component of major cities. The widespread use of smart cards for automated fare collection in these systems offers a unique opportunity to understand passenger behavior at a massive scale. In this study, we use network-wide data obtained from smart cards in the London transport system to predict future traffic volumes, and to estimate the effects of disruptions due to unplanned closures of stations or lines. Disruptions, or shocks, force passengers to make different decisions concerning which stations to enter or exit. We describe how these changes in passenger behavior lead to possible overcrowding and model how stations will be affected by given disruptions. This information can then be used to mitigate the effects of these shocks because transport authorities may prepare in advance alternative solutions such as additional buses near the most affected stations. We describe statistical methods that leverage the large amount of smart-card data collected under the natural state of the system, where no shocks take place, as variables that are indicative of behavior under disruptions. We find that features extracted from the natural regime data can be successfully exploited to describe different disruption regimes, and that our framework can be used as a general tool for any similar complex transportation system.

  14. Adaptive Traffic Signal Control: Deep Reinforcement Learning Algorithm with Experience Replay and Target Network

    OpenAIRE

    Gao, Juntao; Shen, Yulong; Liu, Jia; Ito, Minoru; Shiratori, Norio

    2017-01-01

    Adaptive traffic signal control, which adjusts traffic signal timing according to real-time traffic, has been shown to be an effective method to reduce traffic congestion. Available works on adaptive traffic signal control make responsive traffic signal control decisions based on human-crafted features (e.g. vehicle queue length). However, human-crafted features are abstractions of raw traffic data (e.g., position and speed of vehicles), which ignore some useful traffic information and lead t...

  15. A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads.

    Directory of Open Access Journals (Sweden)

    Junqing Tang

    Full Text Available Traffic congestion brings not only delay and inconvenience, but other associated national concerns, such as greenhouse gases, air pollutants, road safety issues and risks. Identification, measurement, tracking, and control of urban recurrent congestion are vital for building a livable and smart community. A considerable amount of works has made contributions to tackle the problem. Several methods, such as time-based approaches and level of service, can be effective for characterizing congestion on urban streets. However, studies with systemic perspectives have been minor in congestion quantification. Resilience, on the other hand, is an emerging concept that focuses on comprehensive systemic performance and characterizes the ability of a system to cope with disturbance and to recover its functionality. In this paper, we symbolized recurrent congestion as internal disturbance and proposed a modified metric inspired by the well-applied "R4" resilience-triangle framework. We constructed the metric with generic dimensions from both resilience engineering and transport science to quantify recurrent congestion based on spatial-temporal traffic patterns and made the comparison with other two approaches in freeway and signal-controlled arterial cases. Results showed that the metric can effectively capture congestion patterns in the study area and provides a quantitative benchmark for comparison. Also, it suggested not only a good comparative performance in measuring strength of proposed metric, but also its capability of considering the discharging process in congestion. The sensitivity tests showed that proposed metric possesses robustness against parameter perturbation in Robustness Range (RR, but the number of identified congestion patterns can be influenced by the existence of ϵ. In addition, the Elasticity Threshold (ET and the spatial dimension of cell-based platform differ the congestion results significantly on both the detected number and

  16. Exploiting Spatial Abstraction in Predictive Analytics of Vehicle Traffic

    Directory of Open Access Journals (Sweden)

    Natalia Andrienko

    2015-04-01

    Full Text Available By applying visual analytics techniques to vehicle traffic data, we found a way to visualize and study the relationships between the traffic intensity and movement speed on links of a spatially abstracted transportation network. We observed that the traffic intensities and speeds in an abstracted network are interrelated in the same way as they are in a detailed street network at the level of street segments. We developed interactive visual interfaces that support representing these interdependencies by mathematical models. To test the possibility of utilizing them for performing traffic simulations on the basis of abstracted transportation networks, we devised a prototypical simulation algorithm employing these dependency models. The algorithm is embedded in an interactive visual environment for defining traffic scenarios, running simulations, and exploring their results. Our research demonstrates a principal possibility of performing traffic simulations on the basis of spatially abstracted transportation networks using dependency models derived from real traffic data. This possibility needs to be comprehensively investigated and tested in collaboration with transportation domain specialists.

  17. Bridging the gap between traffic generated health stressors in urban areas: Predicting xylene levels in EU cities

    International Nuclear Information System (INIS)

    Vlachokostas, Ch.; Michailidou, A.V.; Spyridi, D.; Moussiopoulos, N.

    2013-01-01

    Many citizens live, work, commute, or visit traffic intensive spaces and are exposed to high levels of chemical health stressors. However, urban conurbations worldwide present monitoring “shortage” – due to economical and/or practical constraints – for toxic stressors such as xylene isomers, which can pose human health risks. This “shortage” may be covered by the establishment of associations between rarely monitored substances such as xylenes and more frequently monitored (i.e. benzene) or usually monitored (i.e. CO). Regression analysis is used and strong statistical relationships are detected. The adopted models are applied to EU cities and comparison between measurements and predictions depicts their representativeness. The analysis provides transferability insights in an effort to bridge the gap between traffic-related stressors. Strong associations between substances of the air pollution mixture may be influential to interpret the complexity of the causal chain, especially if a synergetic exposure assessment in traffic intensive spaces is considered. -- Highlights: •EU cities present monitoring shortage for health stressors such as xylenes. •The multi-stressor multi-city stepwise regression modelling approach is presented. •Strong linear relationships between xylenes and toluene, benzene, CO are detected. •Modelling results are in good agreement with the respective available measurements. •Toluene seems the optimal marker to predict xylene trends in traffic environments. -- The multi-stressor, multi-city stepwise regression modelling approach develops reliable statistical associations which capture m,p-xylene and o-xylene trends in EU traffic intensive environments

  18. Congestion management in Alberta

    International Nuclear Information System (INIS)

    Way, R.

    2002-01-01

    The challenges facing Alberta regarding electricity market design and congestion management were described. The electricity market in the province consists of a central power pool, an open access transmission network, and a single pool price, unlike many other jurisdictions in North America which have adopted a location margin price (LMP) design with significant price differences between various locations within the power network. Alberta's transmission network is regulated and provides carrier functions. Power moves freely throughout Alberta's power pool network with no congestion, therefore the common pool price signals market participants throughout the entire network with no segregation into zones. Alberta is currently at a cross road in choosing between a single pool price model or a nodal price model. In the first instance, the province would have to strengthen the transmission network to maintain the market at a reasonable size. The alternative would permit Alberta to use market-based techniques to deal with the evolution of many smaller markets in the province, but these would be very small by North American standards and their ability to compete would be questionable

  19. Can the traffic locus of control (T-LOC) scale be successfully used to predict Swedish drivers' speeding behaviour?

    Science.gov (United States)

    Warner, Henriette Wallén; Ozkan, Türker; Lajunen, Timo

    2010-07-01

    The first aim of the present study was to examine the factor structure of the traffic locus of control (T-LOC) scale in a Swedish sample of drivers. The second aim was to examine if this scale can be used to predict drivers' speeding behaviour. A sample of Swedish car owners (N=223) completed a questionnaire including questions based on the traffic locus of control (T-LOC) scale as well as questions about their speeding behaviour. The results showed a five factor solution including own skills, own behaviour, other drivers, vehicle/environment and fate. Own behaviour and vehicle/environment could be used to predict drivers' speeding behaviour on roads with a 90 km/h speed limit while none of the variables included in the traffic locus of control (T-LOC) scale could be used to predict drivers' speeding behaviour on roads with a 50 km/h speed limit. On 90 km/h roads own behaviour was positively related to drivers' speeding behaviour while vehicle/environment was negatively related to their speeding behaviour. Copyright 2010 Elsevier Ltd. All rights reserved.

  20. Traveler oriented traffic performance metrics using real time traffic data from the Midtown-in-Motion (MIM) project in Manhattan, NY.

    Science.gov (United States)

    2013-10-01

    In a congested urban street network the average traffic speed is an inadequate metric for measuring : speed changes that drivers can perceive from changes in traffic control strategies. : A driver oriented metric is needed. Stop frequency distrib...

  1. Slot allocation on congested motorways : An alternative to congestion pricing

    NARCIS (Netherlands)

    Koolstra, K.

    1999-01-01

    With respect to the prevailing congestion problems in the more urbanised regions of the European Union, transportation planners and policymakers are facing a dilemma. Supply-side measures, i.e. increasing the capacities, might shorten the congestion duration, especially if bottlenecks can be

  2. A hierarchical framework for air traffic control

    Science.gov (United States)

    Roy, Kaushik

    in NextGen will affect the overall performance of air traffic control. The dissertation also provides solutions to several key estimation problems that support corresponding control tasks. Throughout the development of these estimation algorithms, aircraft motion is modeled using hybrid systems, which encapsulate both the discrete flight mode of an aircraft and the evolution of continuous states such as position and velocity. The target-tracking problem is posed as one of hybrid state estimation, and two new algorithms are developed to exploit structure specific to aircraft motion, especially near airports. First, discrete mode evolution is modeled using state-dependent transitions, in which the likelihood of changing flight modes is dependent on aircraft state. Second, an estimator is designed for systems with limited mode changes, including arrival aircraft. Improved target tracking facilitates increased safety in collision avoidance and trajectory design problems. A multiple-target tracking and identity management algorithm is developed to improve situational awareness for controllers about multiple maneuvering targets in a congested region. Finally, tracking algorithms are extended to predict aircraft landing times; estimated time of arrival prediction is one example of important decision support information for air traffic control.

  3. V2X application-reliability analysis of data-rate and message-rate congestion control algorithms

    NARCIS (Netherlands)

    Math, C. Belagal; Li, H.; Heemstra de Groot, S.M.; Niemegeers, I.G.M.M.

    2017-01-01

    Intelligent Transportation Systems (ITS) require Vehicle-to-Everything (V2X) communication. In dense traffic, the communication channel may become congested, impairing the reliability of the ITS safety applications. Therefore, European Telecommunications Standard Institute (ETSI) demands

  4. Traffic Accident Propagation Properties and Control Measures for Urban Links Based on Cellular Automata

    Directory of Open Access Journals (Sweden)

    Xian-sheng Li

    2013-01-01

    Full Text Available With the rapid development of urban transport and the sharp increase in vehicle population, traffic accidents form one of the most important causes of urban traffic congestion other than the imbalance between traffic supply and demand. Traffic congestion causes severe problems, such as environment contamination and energy dissipation. Therefore, it would be useful to analyze the congestion propagation characteristics after traffic accidents. Numerical analysis and computer simulation were two of the typical methods used at present to study the traffic congestion propagation properties. The latter was more widespread as it is more consistent with the actual traffic flow and more visual than the former. In this paper, an improved cellular automata (CA model was presented to analyze traffic congestion propagation properties and to evaluate control strategies. In order to apply them to urban traffic flow simulation, the CA models have been improved and expanded on. Computer simulations were built for congestion not only extending to the upstream intersection, but also the upstream intersection and the entire road network, respectively. Congestion propagation characteristics after road traffic accidents were obtained, and controls of different severities and durations were analyzed. The results provide the theoretical foundation and practical means for the control of congestion.

  5. COMPARISON OF TREND PROJECTION METHODS AND BACKPROPAGATION PROJECTIONS METHODS TREND IN PREDICTING THE NUMBER OF VICTIMS DIED IN TRAFFIC ACCIDENT IN TIMOR TENGAH REGENCY, NUSA TENGGARA

    Directory of Open Access Journals (Sweden)

    Aleksius Madu

    2016-10-01

    Full Text Available The purpose of this study is to predict the number of traffic accident victims who died in Timor Tengah Regency with Trend Projection method and Backpropagation method, and compare the two methods based on the degree of guilt and predict the number traffic accident victims in the Timor Tengah Regency for the coming year. This research was conducted in Timor Tengah Regency where data used in this study was obtained from Police Unit in Timor Tengah Regency. The data is on the number of traffic accidents in Timor Tengah Regency from 2000 – 2013, which is obtained by a quantitative analysis with Trend Projection and Backpropagation method. The results of the data analysis predicting the number of traffic accidents victims using Trend Projection method obtained the best model which is the quadratic trend model with equation Yk = 39.786 + (3.297 X + (0.13 X2. Whereas by using back propagation method, it is obtained the optimum network that consists of 2 inputs, 3 hidden screens, and 1 output. Based on the error rates obtained, Back propagation method is better than the Trend Projection method which means that the predicting accuracy with Back propagation method is the best method to predict the number of traffic accidents victims in Timor Tengah Regency. Thus obtained predicting the numbers of traffic accident victims for the next 5 years (Years 2014-2018 respectively - are 106 person, 115 person, 115 person, 119 person and 120 person.   Keywords: Trend Projection, Back propagation, Predicting.

  6. Intelligent Packet Shaper to Avoid Network Congestion for Improved Streaming Video Quality at Clients

    DEFF Research Database (Denmark)

    Kaul, Manohar; Khosla, Rajiv; Mitsukura, Y

    2003-01-01

    of this intelligent traffic-shaping algorithm on the underlying network real time packet traffic and the eradication of unwanted abruption in the streaming video qualiy. This paper concluded from the end results of the simulation that neural networks are a very superior means of modeling real-time traffic......This paper proposes a traffic shaping algorithm based on neural networks, which adapts to a network over which streaming video is being transmitted. The purpose of this intelligent shaper is to eradicate all traffic congestion and improve the end-user's video quality. It possesses the capability...

  7. Congestion control and routing over satellite networks

    Science.gov (United States)

    Cao, Jinhua

    Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE

  8. Weighted congestion coefficient feedback in intelligent transportation systems

    International Nuclear Information System (INIS)

    Dong Chuanfei; Ma Xu; Wang Binghong

    2010-01-01

    In traffic systems, a reasonable information feedback can improve road capacity. In this Letter, we study dynamics of traffic flow with real-time information. And the influence of a feedback strategy named Weighted Congestion Coefficient Feedback Strategy (WCCFS) is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux.

  9. Ant colony optimization algorithm for signal coordination of oversaturated traffic networks.

    Science.gov (United States)

    2010-05-01

    Traffic congestion is a daily and growing problem of the modern era in mostly all major cities in the world. : Increasing traffic demand strains the existing transportation system, leading to oversaturated network : conditions, especially at peak hou...

  10. The use of a transport simulation system (AIMSUN to determine the environmental effects of pedestrianization and traffic management in the center of Thessaloniki

    Directory of Open Access Journals (Sweden)

    Evangelos Mintsis

    2016-06-01

    Full Text Available Traffic congestion in urban areas results in increased energy consumption and vehicle emissions. Traffic management that alleviates traffic congestion also mitigates the environmental effects of vehicular traffic. This study uses the transport simulation model AIMSUN to evaluate the environmental effect of a set of traffic management and pedestrianization schemes. The effects of the pedestrianization of specific sections of roads, converting two-way roads into one-way roads for traffic and changing the direction of flow of traffic along one-way roads were simulated for different areas of Thessaloniki’s city centre network. The assessment of the environmental effect was done by determining the predicted fuel consumption and emissions of greenhouse gases (GHG and air pollutants. Fuel consumption and the environmental indicators were quantified directly using the fuel consumption and emissions model in AIMSUN. A typical weekday morning peak period, between 09:00am–10:00am, was simulated and the demand data obtained using a macroscopic traffic assignment model previously developed for the wider area of Thessaloniki. The results presented in this paper are for network-wide simulation statistics (i.e. fuel consumed, carbon dioxide (CO2, nitrogen oxides (NOx and particulate matter (PM.

  11. Predicting drunk driving: contribution of alcohol use and related problems, traffic behaviour, personality and platelet monoamine oxidase (MAO) activity.

    Science.gov (United States)

    Eensoo, Diva; Paaver, Marika; Harro, Maarike; Harro, Jaanus

    2005-01-01

    The aim of the study was to characterize the predictive value of socio-economic data, alcohol consumption measures, smoking, platelet monoamine oxidase (MAO) activity, traffic behaviour habits and impulsivity measures for actual drunk driving. Data were collected from 203 male drunk driving offenders and 211 control subjects using self-reported questionnaires, and blood samples were obtained from the two groups. We identified the combination of variables, which predicted correctly, approximately 80% of the subjects' belonging to the drunk driving and control groups. Significant independent discriminators in the final model were, among the health-behaviour measures, alcohol-related problems, frequency of using alcohol, the amount of alcohol consumed and smoking. Predictive traffic behaviour measures were seat belt use and paying for parking. Among the impulsivity measures, dysfunctional impulsivity was the best predictor; platelet MAO activity and age also had an independent predictive value. Our results support the notion that drunk driving is the result of a combination of various behavioural, biological and personality-related risk factors.

  12. Green Eco-Driving Effects in Non-Congested Cities

    Directory of Open Access Journals (Sweden)

    Juan Francisco Coloma

    2017-12-01

    Full Text Available Despite technological advances in engines and fuels, the transportation sector is still one of the largest emitters of greenhouse gas (GHG. Driving patterns, including eco-driving techniques, are a complementary measure for saving GHG emissions. Most eco-driving studies so far have been conducted in large cities suffering chronic congestion problems. The aim of this research is therefore to analyse the potential of driver behaviour for reducing emissions in a small non-congested city. Driver performance parameters such as travel speeds, number of stops, revolutions per minute, and maximum acceleration-deceleration are also studied. The methodology is designed to measure the effect of both eco-driving and eco-routing under real traffic conditions. A campaign was carried out in the city of Caceres (Spain to collect data on various types of roads under different traffic conditions. This research concludes that eco-driving leads to CO2 savings on all routes and road types of 17% in gasoline engines and 21% in diesel, although travel times are increased by 7.5% on average. The shortest route is also the most ecological, regardless of the traffic volume and characteristics, implying that consumption in non-congested cities depends mainly on distance travelled rather than driving patterns in terms of number of stops, speed and acceleration.

  13. [Reduction of automobile traffic: urgent health promotion policy].

    Science.gov (United States)

    Tapia Granados, J A

    1998-03-01

    During the last few decades, traffic injuries have become one of the leading causes of death and disability in the world. In urban areas, traffic congestion, noise, and emissions from motor vehicles produce subjective disturbances and detectable pathological effects. More than one billion people are exposed to harmful levels of environmental pollution. Because its combustion engine generates carbon dioxide (CO2), the automobile is one of the chief sources of the gases that are causing the greenhouse effect. The latter has already caused a rise in the average ambient temperature, and over the next decades it will predictable cause significant climatic changes whose consequences, though uncertain, are likely to be harmful and possibly catastrophic. Aside from the greenhouse effect, the relentless growth of parking zones, traffic, and the roadway infrastructure in urban and rural areas is currently one of the leading causes of environmental degradation. Urban development, which is nearly always "planned" around traffic instead of people, leads to a significant deterioration in the quality of life, while it also destroys the social fabric. Unlike the private automobile, public transportation, bicycles, and walking help reduce pollution, congestion, and traffic volume, as well as the morbidity and mortality resulting from injuries and ailments related to pollution. Non-automobile transportation also encourages physical activity--with its positive effect on general health--and helps reduce the greenhouse effect. The drop in traffic volume and the increased use of alternate means of transportation are thus an integrated health promotion policy which should become an inherent part of the movement for the promotion of healthy cities and of transportation policies and economic policy in general.

  14. Flight safety measurements of UAVs in congested airspace

    Directory of Open Access Journals (Sweden)

    Xiang Jinwu

    2016-10-01

    Full Text Available Describing spatial safety status is crucial for high-density air traffic involving multiple unmanned aerial vehicles (UAVs in a complex environment. A probabilistic approach is proposed to measure safety situation in congested airspace. The occupancy distribution of the airspace is represented with conflict probability between spatial positions and UAV. The concept of a safety envelope related to flight performance and response time is presented first instead of the conventional fixed-size protected zones around aircraft. Consequently, the conflict probability is performance-dependent, and effects of various UAVs on safety can be distinguished. The uncertainty of a UAV future position is explicitly accounted for as Brownian motion. An analytic approximate algorithm for the conflict probability is developed to decrease the computational consumption. The relationship between safety and flight performance are discussed for different response times and prediction intervals. To illustrate the applications of the approach, an experiment of three UAVs in formation flight is performed. In addition, an example of trajectory planning is simulated for one UAV flying over airspace where five UAVs exist. The validation of the approach shows its potential in guaranteeing flight safety in highly dynamic environment.

  15. The predictive validity of personality tests in air traffic controller selection

    NARCIS (Netherlands)

    Roe, R.A.; Oprins, E.A.P.B.; Geven, E.

    2012-01-01

    A brief historical review of test methods used for selecting air traffic controllers (ATCOs) shows that in contrast to e.g. ability tests and job samples, personality tests have been used rather infrequently. The lesser popularity of personality tests may be explained from the belief that

  16. Vehicle-class Specific Route-guidance of Freeway Traffic by Model-predictive Control

    NARCIS (Netherlands)

    Schreiter, T.; Landman, R.L.; Van Lint, J.W.C.; Hegyi, A.; Hoogendoorn, S.P.

    2012-01-01

    Few Active Traffic Management measures proposed in the past consider the distinction of different vehicle classes. Examples of vehicle-class specific measures are truck lanes and high-occupancy/toll (HOT) lanes. We propose that the distinction of different vehicle classes, with different flow

  17. Use of a Phase Transition Concept for Traffic Flow Condition Estimation

    Directory of Open Access Journals (Sweden)

    Larin Oleg N.

    2014-12-01

    Full Text Available The article covers the main models of traffic flow conditions, analyzes the condition estimation criteria, and provides the classification of models. The article provides the grounds for the use of the phase transition concept for traffic flow condition estimation. The models of the aggregate condition of free and congested traffic have been developed, the phase boundaries between free and congested traffic have been defined. Applicability conditions for the models of the aggregate condition of have been analyzed.

  18. The development of area wide traffic management scenarios

    NARCIS (Netherlands)

    Van Zuylen, H.J.; Lu, S.; Li, J.; Yusen, C.

    2014-01-01

    Traffic management in cities with congestion is a big challenge with still unused opportunities. Intersection control is a corner stone but this should be done in an area-wide context. The dominant traffic process on urban roads is the traffic flow on the intersections. Spill back is a most

  19. Stochastic control of traffic patterns

    DEFF Research Database (Denmark)

    Gaididei, Yuri B.; Gorria, Carlos; Berkemer, Rainer

    2013-01-01

    A stochastic modulation of the safety distance can reduce traffic jams. It is found that the effect of random modulation on congestive flow formation depends on the spatial correlation of the noise. Jam creation is suppressed for highly correlated noise. The results demonstrate the advantage of h...

  20. A Survey of Congestion Control Techniques and Data Link Protocols in Satellite Networks

    OpenAIRE

    Fahmy, Sonia; Jain, Raj; Lu, Fang; Kalyanaraman, Shivkumar

    1998-01-01

    Satellite communication systems are the means of realizing a global broadband integrated services digital network. Due to the statistical nature of the integrated services traffic, the resulting rate fluctuations and burstiness render congestion control a complicated, yet indispensable function. The long propagation delay of the earth-satellite link further imposes severe demands and constraints on the congestion control schemes, as well as the media access control techniques and retransmissi...

  1. Probabilistic description of traffic flow

    International Nuclear Information System (INIS)

    Mahnke, R.; Kaupuzs, J.; Lubashevsky, I.

    2005-01-01

    A stochastic description of traffic flow, called probabilistic traffic flow theory, is developed. The general master equation is applied to relatively simple models to describe the formation and dissolution of traffic congestions. Our approach is mainly based on spatially homogeneous systems like periodically closed circular rings without on- and off-ramps. We consider a stochastic one-step process of growth or shrinkage of a car cluster (jam). As generalization we discuss the coexistence of several car clusters of different sizes. The basic problem is to find a physically motivated ansatz for the transition rates of the attachment and detachment of individual cars to a car cluster consistent with the empirical observations in real traffic. The emphasis is put on the analogy with first-order phase transitions and nucleation phenomena in physical systems like supersaturated vapour. The results are summarized in the flux-density relation, the so-called fundamental diagram of traffic flow, and compared with empirical data. Different regimes of traffic flow are discussed: free flow, congested mode as stop-and-go regime, and heavy viscous traffic. The traffic breakdown is studied based on the master equation as well as the Fokker-Planck approximation to calculate mean first passage times or escape rates. Generalizations are developed to allow for on-ramp effects. The calculated flux-density relation and characteristic breakdown times coincide with empirical data measured on highways. Finally, a brief summary of the stochastic cellular automata approach is given

  2. Congestion Management System Process Report

    Science.gov (United States)

    1996-03-01

    In January 1995, the Indianapolis Metropolitan Planning Organization with the help of an interagency Study Review Committee began the process of developing a Congestion Management System (CMS) Plan resulting in this report. This report documents the ...

  3. Road traffic emissions - predictions of future contributions to regional ozone levels in Europe

    International Nuclear Information System (INIS)

    Reis, S.; Friedrich, R.; Obermeier, A.; Unger, S.

    2000-01-01

    As part of the European Commission research project 'Assessment of policy instruments for efficient ozone abatement strategies in Europe,' detailed emission projections have been developed for the year 2010 based upon currently adopted measures, and feasible reductions. For road-traffic emissions this projection considers passenger cars, light- and heavy-duty vehicles, mopeds and motorcycles. Here we present model calculations made with the EMEP 3-D Eulerian model to illustrate the relative contribution of each of these road-traffic sectors to ozone concentrations across Europe. The model is run for a six-month period, April-September 1996. The model results clearly suggest that further reduction in road-traffic emissions beyond currently planned measures would be beneficial in reducing ozone over Europe, particularly in the case of heavy-duty vehicles and evaporative emissions. These results do of course depend on the estimated emissions in each sector for the year 2010, and we show that this is a major source of uncertainty in such scenario calculations. (author)

  4. Estimates of CO2 traffic emissions from mobile concentration measurements

    Science.gov (United States)

    Maness, H. L.; Thurlow, M. E.; McDonald, B. C.; Harley, R. A.

    2015-03-01

    We present data from a new mobile system intended to aid in the design of upcoming urban CO2-monitoring networks. Our collected data include GPS probe data, video-derived traffic density, and accurate CO2 concentration measurements. The method described here is economical, scalable, and self-contained, allowing for potential future deployment in locations without existing traffic infrastructure or vehicle fleet information. Using a test data set collected on California Highway 24 over a 2 week period, we observe that on-road CO2 concentrations are elevated by a factor of 2 in congestion compared to free-flow conditions. This result is found to be consistent with a model including vehicle-induced turbulence and standard engine physics. In contrast to surface concentrations, surface emissions are found to be relatively insensitive to congestion. We next use our model for CO2 concentration together with our data to independently derive vehicle emission rate parameters. Parameters scaling the leading four emission rate terms are found to be within 25% of those expected for a typical passenger car fleet, enabling us to derive instantaneous emission rates directly from our data that compare generally favorably to predictive models presented in the literature. The present results highlight the importance of high spatial and temporal resolution traffic data for interpreting on- and near-road concentration measurements. Future work will focus on transport and the integration of mobile platforms into existing stationary network designs.

  5. Traffic Flow Condition Classification for Short Sections Using Single Microwave Sensor

    Directory of Open Access Journals (Sweden)

    Memiş Kemal

    2010-01-01

    Full Text Available Daily observed traffic flow can show different characteristics varying with the times of the day. They are caused by traffic incidents such as accidents, disabled cars, construction activities and other unusual events. Three different major traffic conditions can be occurred: "Flow," "Dense" and "Congested". Objective of this research is to identify the current traffic condition by examining the traffic measurement parameters. The earlier researches have dealt only with speed and volume by ignoring occupancy. In our study, the occupancy is another important parameter of classification. The previous works have used multiple sensors to classify traffic condition whereas our work uses only single microwave sensor. We have extended Multiple Linear Regression classification with our new approach of Estimating with Error Prediction. We present novel algorithms of Multiclassification with One-Against-All Method and Multiclassification with Binary Comparison for multiple SVM architecture. Finaly, a non-linear model of backpropagation neural network is introduced for classification. This combination has not been reported on previous studies. Training data are obtained from the Corsim based microscopic traffic simulator TSIS 5.1. All performances are compared using this data set. Our methods are currently installed and running at traffic management center of 2.Ring Road in Istanbul.

  6. Traffic theory

    National Research Council Canada - National Science Library

    Gazis, Denos C

    2002-01-01

    ... of traffic signal settings The vehicle-actuated traffic signal 87 89 77 CHAPTER 3. TRAFFIC CONTROL 101 Objectives of Traffic Control 103 Single, Isolated Intersection 105 Synchronization Scheme...

  7. Predicting Crashes Using Traffic Offences. A Meta-Analysis that Examines Potential Bias between Self-Report and Archival Data

    Science.gov (United States)

    af Wåhlberg, Anders; Freeman, James; Watson, Barry; Watson, Angela

    2016-01-01

    Background Traffic offences have been considered an important predictor of crash involvement, and have often been used as a proxy safety variable for crashes. However the association between crashes and offences has never been meta-analysed and the population effect size never established. Research is yet to determine the extent to which this relationship may be spuriously inflated through systematic measurement error, with obvious implications for researchers endeavouring to accurately identify salient factors predictive of crashes. Methodology and Principal Findings Studies yielding a correlation between crashes and traffic offences were collated and a meta-analysis of 144 effects drawn from 99 road safety studies conducted. Potential impact of factors such as age, time period, crash and offence rates, crash severity and data type, sourced from either self-report surveys or archival records, were considered and discussed. After weighting for sample size, an average correlation of r = .18 was observed over the mean time period of 3.2 years. Evidence emerged suggesting the strength of this correlation is decreasing over time. Stronger correlations between crashes and offences were generally found in studies involving younger drivers. Consistent with common method variance effects, a within country analysis found stronger effect sizes in self-reported data even controlling for crash mean. Significance The effectiveness of traffic offences as a proxy for crashes may be limited. Inclusion of elements such as independently validated crash and offence histories or accurate measures of exposure to the road would facilitate a better understanding of the factors that influence crash involvement. PMID:27128093

  8. A Traffic Restriction Scheme for Enhancing Carpooling

    Directory of Open Access Journals (Sweden)

    Dong Ding

    2017-01-01

    Full Text Available For the purpose of alleviating traffic congestion, this paper proposes a scheme to encourage travelers to carpool by traffic restriction. By a variational inequity we describe travelers’ mode (solo driving and carpooling and route choice under user equilibrium principle in the context of fixed demand and detect the performance of a simple network with various restriction links, restriction proportions, and carpooling costs. Then the optimal traffic restriction scheme aiming at minimal total travel cost is designed through a bilevel program and applied to a Sioux Fall network example with genetic algorithm. According to various requirements, optimal restriction regions and proportions for restricted automobiles are captured. From the results it is found that traffic restriction scheme is possible to enhance carpooling and alleviate congestion. However, higher carpooling demand is not always helpful to the whole network. The topology of network, OD demand, and carpooling cost are included in the factors influencing the performance of the traffic system.

  9. Using Automated Planning for Traffic Signals Control

    Directory of Open Access Journals (Sweden)

    Matija Gulić

    2016-08-01

    Full Text Available Solving traffic congestions represents a high priority issue in many big cities. Traditional traffic control systems are mainly based on pre-programmed, reactive and local techniques. This paper presents an autonomic system that uses automated planning techniques instead. These techniques are easily configurable and modified, and can reason about the future implications of actions that change the default traffic lights behaviour. The proposed implemented system includes some autonomic properties, since it monitors the current traffic state, detects if the system is degrading its performance, sets up new sets of goals to be achieved by the planner, triggers the planner that generates plans with control actions, and executes the selected courses of actions. The obtained results in several artificial and real world data-based simulation scenarios show that the proposed system can efficiently solve traffic congestion.

  10. New method for probabilistic traffic demand predictions for en route sectors based on uncertain predictions of individual flight events.

    Science.gov (United States)

    2011-06-14

    This paper presents a novel analytical approach to and techniques for translating characteristics of uncertainty in predicting sector entry times and times in sector for individual flights into characteristics of uncertainty in predicting one-minute ...

  11. In-hospital and long-term outcomes of congestive heart failure: Predictive value of B-type and amino-terminal pro-B-type natriuretic peptides and their ratio.

    Science.gov (United States)

    Dai, Yuxiang; Yang, Jun; Takagi, Atsutoshi; Konishi, Hakuoh; Miyazaki, Tetsuro; Masuda, Hiroshi; Shimada, Kazunori; Miyauchi, Katsumi; Daida, Hiroyuki

    2017-08-01

    Relative changes in B-type natriuretic peptide (BNP) and amino terminal pro-BNP (NT-proBNP) levels may help to assess the risk of congestive heart failure (CHF). However, whether these levels at the time of admission enable the prediction of outcomes with acute exacerbation remains unknown. The current study determined the abilities of BNP, NT-proBNP and their ratio to predict in-hospital and long-term outcomes of patients with CHF. Patients who were admitted to the cardiac care unit of Juntendo University Hospital (Tokyo, Japan) with acute CHF onset were consecutively enrolled into the present observational study. Serum levels of BNP and NT-proBNP were immediately measured on admission, and other biomarkers and clinical data were also investigated. Of 195 enrolled patients, 16 (8.2%) succumbed to CHF in hospital and 124 (69.3%) reached the endpoint of mortality or readmission following a median follow-up of 14 months. Multiple linear regression analysis revealed body mass index, low density lipoprotein cholesterol, hemoglobin, estimated glomerular filtration rate and C-reactive protein as independent predictors of the NT-proBNP/BNP ratio. BNP, NT-proBNP and their ratio were significantly higher among those who succumbed to CHF than in those who remained alive in hospital (P<0.05). Logistic regression analysis indicated that the ratio was an independent predictor for in-hospital mortality and long-term outcomes. In conclusion, the ratio of NT-proBNP to BNP more effectively predicts in-hospital outcomes than either factor alone and it may also help to predict outcomes among patients with acute exacerbation of HF.

  12. CHADS2 and modified CHA2DS2-VASc scores for the prediction of congestive heart failure in patients with nonvalvular atrial fibrillation

    Directory of Open Access Journals (Sweden)

    Yorihiko Koeda

    2017-10-01

    Conclusion: Calculation of the CHADS2 and mCHA2DS2-VASc scores in order to evaluate the risk of systemic thromboembolism was useful to predict the onset of CHF, but not all-cause death, in patients with NVAF.

  13. Fuzzy Multiobjective Traffic Light Signal Optimization

    Directory of Open Access Journals (Sweden)

    N. Shahsavari Pour

    2013-01-01

    Full Text Available Traffic congestion is a major concern for many cities throughout the world. In a general traffic light controller, the traffic lights change at a constant cycle time. Hence it does not provide an optimal solution. Many traffic light controllers in current use are based on the “time-of-the-day” scheme, which use a limited number of predetermined traffic light patterns and implement these patterns depending upon the time of the day. These automated systems do not provide an optimal control for fluctuating traffic volumes. In this paper, the fuzzy traffic light controller is used to optimize the control of fluctuating traffic volumes such as oversaturated or unusual load conditions. The problem is solved by genetic algorithm, and a new defuzzification method is introduced. The performance of the new defuzzification method (NDM is compared with the centroid point defuzzification method (CPDM by using ANOVA. Finally, an illustrative example is presented to show the competency of proposed algorithm.

  14. Air congestion delay: a review

    Directory of Open Access Journals (Sweden)

    Daniel Alberto Pamplona

    2016-04-01

    Full Text Available This article is a literature review of the air congestion delay and its costs. Air congestion is a worldwide problem. Its existence brings costs for airlines and discomfort for passengers. With the increasing demand for air transport, the study of air congestion has attracted the attention of many researchers around the world. The cause for the delays is erroneously attributed only to the lack of infrastructure investments. The literature review shows that other factors such as population growth, increasing standards of living, lack of operational planning and environmental issues exercise decisive influence. Several studies have been conducted in order to analyze and propose solutions to this problem that affects society as a whole.

  15. Endogenous scheduling preferences and congestion

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Small, Kenneth

    2017-01-01

    We consider the timing of activities through a dynamic model of commuting with congestion, in which workers care solely about leisure and consumption. Implicit preferences for the timing of the commute form endogenously due to temporal agglomeration economies. Equilibrium exists uniquely and is i......We consider the timing of activities through a dynamic model of commuting with congestion, in which workers care solely about leisure and consumption. Implicit preferences for the timing of the commute form endogenously due to temporal agglomeration economies. Equilibrium exists uniquely...... and is indistinguishable from that of a generalized version of the classical Vickrey bottleneck model, based on exogenous trip-timing preferences, but optimal policies differ: the Vickrey model will misstate the benefits of a capacity increase, it will underpredict the benefits of congestion pricing, and pricing may make...

  16. The effects of redundancy and information manipulation on traffic networks

    OpenAIRE

    Özel, Berk; Ozel, Berk

    2014-01-01

    Traffic congestion is one of the most frequently encountered problems in real life. It is not only a scientific concern of scholars, but also an inevitable issue for most of the individuals living in urban areas. Since every driver in traffic networks tries to minimize own journey length, and volume of the traffic prevents coordination between individuals, a cooperative behavior will not be provided spontaneously in order to decrease the total cost of the network and the time spent on traffic...

  17. CONSIDERING TRAVEL TIME RELIABILITY AND SAFETY FOR EVALUATION OF CONGESTION RELIEF SCHEMES ON EXPRESSWAY SEGMENTS

    Directory of Open Access Journals (Sweden)

    Babak MEHRAN

    2009-01-01

    Full Text Available Evaluation of the efficiency of congestion relief schemes on expressways has generally been based on average travel time analysis. However, road authorities are much more interested in knowing the possible impacts of improvement schemes on safety and travel time reliability prior to implementing them in real conditions. A methodology is presented to estimate travel time reliability based on modeling travel time variations as a function of demand, capacity and weather conditions. For a subject expressway segment, patterns of demand and capacity were generated for each 5-minute interval over a year by using the Monte-Carlo simulation technique, and accidents were generated randomly according to traffic conditions. A whole year analysis was performed by comparing demand and available capacity for each scenario and shockwave analysis was used to estimate the queue length at each time interval. Travel times were estimated from refined speed-flow relationships and buffer time index was estimated as a measure of travel time reliability. it was shown that the estimated reliability measures and predicted number of accidents are very close to observed values through empirical data. After validation, the methodology was applied to assess the impact of two alternative congestion relief schemes on a subject expressway segment. one alternative was to open the hard shoulder to traffic during the peak period, while the other was to reduce the peak period demand by 15%. The extent of improvements in travel conditions and safety, likewise the reduction in road users' costs after implementing each improvement scheme were estimated. it was shown that both strategies can result in up to 23% reduction in the number of occurred accidents and significant improvements in travel time reliability. Finally, the advantages and challenging issues of selecting each improvement scheme were discussed.

  18. Line grouping using perceptual saliency and structure prediction for car detection in traffic scenes

    Science.gov (United States)

    Denasi, Sandra; Quaglia, Giorgio

    1993-08-01

    Autonomous and guide assisted vehicles make a heavy use of computer vision techniques to perceive the environment where they move. In this context, the European PROMETHEUS program is carrying on activities in order to develop autonomous vehicle monitoring that assists people to achieve safer driving. Car detection is one of the topics that are faced by the program. Our contribution proposes the development of this task in two stages: the localization of areas of interest and the formulation of object hypotheses. In particular, the present paper proposes a new approach that builds structural descriptions of objects from edge segmentations by using geometrical organization. This approach has been applied to the detection of cars in traffic scenes. We have analyzed images taken from a moving vehicle in order to formulate obstacle hypotheses: preliminary results confirm the efficiency of the method.

  19. Criterion for traffic phases in single vehicle data and empirical test of a microscopic three-phase traffic theory

    International Nuclear Information System (INIS)

    Kerner, Boris S; Klenov, Sergey L; Hiller, Andreas

    2006-01-01

    Based on empirical and numerical microscopic analyses, the physical nature of a qualitatively different behaviour of the wide moving jam phase in comparison with the synchronized flow phase-microscopic traffic flow interruption within the wide moving jam phase-is found. A microscopic criterion for distinguishing the synchronized flow and wide moving jam phases in single vehicle data measured at a single freeway location is presented. Based on this criterion, empirical microscopic classification of different local congested traffic states is performed. Simulations made show that the microscopic criterion and macroscopic spatiotemporal objective criteria lead to the same identification of the synchronized flow and wide moving jam phases in congested traffic. Microscopic models in the context of three-phase traffic theory have been tested based on the microscopic criterion for the phases in congested traffic. It is found that microscopic three-phase traffic models can explain both microscopic and macroscopic empirical congested pattern features. It is obtained that microscopic frequency distributions for vehicle speed difference as well as fundamental diagrams and speed correlation functions can depend on the spatial co-ordinate considerably. It turns out that microscopic optimal velocity (OV) functions and time headway distributions are not necessarily qualitatively different, even if local congested traffic states are qualitatively different. The reason for this is that important spatiotemporal features of congested traffic patterns are lost in these as well as in many other macroscopic and microscopic traffic characteristics, which are widely used as the empirical basis for a test of traffic flow models, specifically, cellular automata traffic flow models

  20. Transit Station Congestion Index Research Based on Pedestrian Simulation and Gray Clustering Evaluation

    Directory of Open Access Journals (Sweden)

    Shu-wei Wang

    2013-01-01

    Full Text Available A congestion phenomenon in a transit station could lead to low transfer efficiency as well as a hidden danger. Effective management of congestion phenomenon shall help to reduce the efficiency decline and danger risk. However, due to the difficulty in acquiring microcosmic pedestrian density, existing researches lack quantitative indicators to reflect congestion degree. This paper aims to solve this problem. Firstly, platform, stair, transfer tunnel, auto fare collection (AFC machine, and security check machine were chosen as key traffic facilities through large amounts of field investigation. Key facilities could be used to reflect the passenger density of a whole station. Secondly, the pedestrian density change law of each key traffic facility was analyzed using pedestrian simulation, and the load degree calculating method of each facility was defined, respectively, afterwards. Taking pedestrian density as basic data and gray clustering evaluation as algorithm, an index called Transit Station Congestion Index (TSCI was constructed to reflect the congestion degree of transit stations. Finally, an evaluation demonstration was carried out with five typical transit transfer stations in Beijing, and the evaluation results show that TSCI can objectively reflect the congestion degree of transit stations.

  1. A State-of-the-Art Review of the Sensor Location, Flow Observability, Estimation, and Prediction Problems in Traffic Networks

    Directory of Open Access Journals (Sweden)

    Enrique Castillo

    2015-01-01

    Full Text Available A state-of-the-art review of flow observability, estimation, and prediction problems in traffic networks is performed. Since mathematical optimization provides a general framework for all of them, an integrated approach is used to perform the analysis of these problems and consider them as different optimization problems whose data, variables, constraints, and objective functions are the main elements that characterize the problems proposed by different authors. For example, counted, scanned or “a priori” data are the most common data sources; conservation laws, flow nonnegativity, link capacity, flow definition, observation, flow propagation, and specific model requirements form the most common constraints; and least squares, likelihood, possible relative error, mean absolute relative error, and so forth constitute the bases for the objective functions or metrics. The high number of possible combinations of these elements justifies the existence of a wide collection of methods for analyzing static and dynamic situations.

  2. Short-term traffic flow prediction model using particle swarm optimization–based combined kernel function-least squares support vector machine combined with chaos theory

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    2016-08-01

    Full Text Available Short-term traffic flow prediction is an important part of intelligent transportation systems research and applications. For further improving the accuracy of short-time traffic flow prediction, a novel hybrid prediction model (multivariate phase space reconstruction–combined kernel function-least squares support vector machine based on multivariate phase space reconstruction and combined kernel function-least squares support vector machine is proposed. The C-C method is used to determine the optimal time delay and the optimal embedding dimension of traffic variables’ (flow, speed, and occupancy time series for phase space reconstruction. The G-P method is selected to calculate the correlation dimension of attractor which is an important index for judging chaotic characteristics of the traffic variables’ series. The optimal input form of combined kernel function-least squares support vector machine model is determined by multivariate phase space reconstruction, and the model’s parameters are optimized by particle swarm optimization algorithm. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. The experimental results suggest that the new proposed model yields better predictions compared with similar models (combined kernel function-least squares support vector machine, multivariate phase space reconstruction–generalized kernel function-least squares support vector machine, and phase space reconstruction–combined kernel function-least squares support vector machine, which indicates that the new proposed model exhibits stronger prediction ability and robustness.

  3. Optimal topology to minimizing congestion in connected communication complex network

    Science.gov (United States)

    Benyoussef, M.; Ez-Zahraouy, H.; Benyoussef, A.

    In this paper, a new model of the interdependent complex network is proposed, based on two assumptions that (i) the capacity of a node depends on its degree, and (ii) the traffic load depends on the distribution of the links in the network. Based on these assumptions, the presented model proposes a method of connection not based on the node having a higher degree but on the region containing hubs. It is found that the final network exhibits two kinds of degree distribution behavior, depending on the kind and the way of the connection. This study reveals a direct relation between network structure and traffic flow. It is found that pc the point of transition between the free flow and the congested phase depends on the network structure and the degree distribution. Moreover, this new model provides an improvement in the traffic compared to the results found in a single network. The same behavior of degree distribution found in a BA network and observed in the real world is obtained; except for this model, the transition point between the free phase and congested phase is much higher than the one observed in a network of BA, for both static and dynamic protocols.

  4. Congestion and residential moving behaviour

    DEFF Research Database (Denmark)

    Larsen, Morten Marott; Pilegaard, Ninette; Van Ommeren, Jos

    2008-01-01

    to congestion. We focus on the equilibrium in which some workers currently living in one region accept jobs in the other, with a fraction of them choosing to commute from their current residence to the new job in the other region and the remainder choosing to move to the region in which the new job is located...

  5. Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

    Science.gov (United States)

    Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

    2017-03-01

    Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.

  6. Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model.

    Science.gov (United States)

    Kim, Dae-Hwan; Ramjan, Lucie M; Mak, Kwok-Kei

    2016-01-01

    Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea. A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience. Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes. Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.

  7. OPTIMAL CONGESTION CHARGES IN GENERAL EQUILIBRIUM

    Directory of Open Access Journals (Sweden)

    Dong-Joo MOON, Ph.D.

    2002-01-01

    Another maximization problem involves characterizing the second-best optimal solution. In this problem, it is assumed to impose the congestion toll only on a single highway link. This problem yields the second-best congestion toll different from the first-best one. This second-best optimal congestion toll has the structure to reflect its impact on other highway links exempt from the congestion charge program.

  8. Question of road traffic congestion and de-congestion in the Greater Johannesburg area: some perspectives

    CSIR Research Space (South Africa)

    Chakwizira, J

    2007-07-01

    Full Text Available Transit Systems Sustainable Around the World: Getting Many Birds with one Bus, Transportation Research Board, Washington DC, USA, ISBN - 0309077176 Fouracre P & Turner J, 1995. Women and Transport in Developing Countries, Transport Reviews, Volume... in the transportation equation and matrix. Insook Kang (2006:5) argues that women’s experience in urban built environment is different from men’s. Gender differentiated transport needs in GJA are intensified by the impacts of gendered economic processes...

  9. Development and Evaluation of a Control System for Regional Traffic Management

    Directory of Open Access Journals (Sweden)

    John L. McLin

    2011-01-01

    Full Text Available Traffic congestion is a worsening problem in metropolitan areas which will require integrated regional traffic control systems to improve traffic conditions. This paper presents a regional traffic control system which can detect incident conditions and provide integrated traffic management during nonrecurrent congestion events. The system combines advanced artificial intelligence techniques with a traffic performance model based on HCM equations. Preliminary evaluation of the control system using traffic microsimulation demonstrates that it has the potential to improve system conditions during traffic incidents. In addition, several enhancements were identified which will make the system more robust in a real traffic control setting. An assessment of the control system elements indicates that there are no substantial technical barriers in implementing this system in a large traffic network.

  10. busy hour traffic congestion analysis in mobile macrocells

    African Journals Online (AJOL)

    HOD

    *Corresponding author tel: + 234 – 803 – 054 – 7650. BUSY HOUR ... demand, radio frequency (RF) optimization teams use the KPIs to ... In practice, the performance can be monitored at ..... [8] I. Kennedy, Lost Call Theory, Lecture Notes,.

  11. Air quality impact of traffic congestion in midtown Manhattan.

    Science.gov (United States)

    2014-01-01

    Exposure to fine particle pollution can cause premature death and harmful cardiovascular effects such as heart : attacks and strokes, and is linked to a variety of other significant health problem. A pilot project was : commissioned by the University...

  12. Public bus services versus congestion and pollution in Lima and Callao

    OpenAIRE

    Martínez Espinal, Manuel

    2017-01-01

    This study measures the influence of public bus services on traffic congestion and environmental pollution in Lima and Callao. The effect of the flow of buses on the transportation network is measured by way of a dynamic traffic assignment program, Dynasmart. The database is constructed on the basis of the 2005-2025 Master Plan. To this end, the transportation network is verified using Google Earth, and field measurements of capacity, speed, and volume- relay functions to describe traffic con...

  13. Signalling and obfuscation for congestion control

    Science.gov (United States)

    Mareček, Jakub; Shorten, Robert; Yu, Jia Yuan

    2015-10-01

    We aim to reduce the social cost of congestion in many smart city applications. In our model of congestion, agents interact over limited resources after receiving signals from a central agent that observes the state of congestion in real time. Under natural models of agent populations, we develop new signalling schemes and show that by introducing a non-trivial amount of uncertainty in the signals, we reduce the social cost of congestion, i.e., improve social welfare. The signalling schemes are efficient in terms of both communication and computation, and are consistent with past observations of the congestion. Moreover, the resulting population dynamics converge under reasonable assumptions.

  14. FOUR-YEAR-OLD NAMSAN TUNNEL CONGESTION PRICING SCHEME IN SEOUL

    Directory of Open Access Journals (Sweden)

    Bongsoo SON, Ph. D.

    2002-01-01

    Full Text Available The purpose of this paper is to evaluate the effectiveness of the congestion pricing scheme at Namsan #1 and #3 tunnels in downtown Seoul four years after its implementation. The effectiveness of the scheme was measured by the changes of various traffic impacts. The traffic volume of the two tunnels was reduced by up to 25% for the first month. After that time, the traffic volume started to increase again and then exceeded the previous volume level. However, average travel speed of the two tunnel corridors improved by up to 74%. The overall traffic volume of the four alternative routes was increased; nevertheless, their average travel speed increased as well. The number of carpool vehicles occupied by 3 or more persons including the driver during the peak periods was remarkably increased. Before the congestion fee charging, toll-charged vehicles amounted to 68.5% of the total traffic volume of the two tunnels, and then the share dropped to 29% afterwards. The empirical analysis results for the effectiveness of the congestion pricing scheme are very promising.

  15. Autonomic urban traffic optimization using data analytics

    OpenAIRE

    Garriga Porqueras, Albert

    2017-01-01

    This work focuses on a smart mobility use case where real-time data analytics on traffic measures is used to improve mobility in the event of a perturbation causing congestion in a local urban area. The data monitored is analysed in order to identify patterns that are used to properly reconfigure traffic lights. The monitoring and data analytics infrastructure is based on a hierarchical distributed architecture that allows placing data analytics processes such as machine learning close to the...

  16. Vehicle-class Specific Control of Freeway Traffic

    NARCIS (Netherlands)

    Schreiter, T.

    2013-01-01

    The increase of mobility of the past decades has led to substantial congestion on the freeways. Traffic jams emerge both on a daily basis at the same location, as well as during accidents when a part of the freeways is temporarily blocked. In those cases, traffic management centers intervene into

  17. Traffic Flow at Sags : Theory, Modeling and Control

    NARCIS (Netherlands)

    Goni-Ros, B.

    2016-01-01

    Sag vertical curves (sags) are roadway sections along which the gradient increases gradually in the direction of traffic. Empirical observations show that, on freeways, traffic congestion often occurs at sags; actually, in some countries (e.g., Japan), sags are one of the most common types of

  18. Traffic control and intelligent vehicle highway systems: a survey

    NARCIS (Netherlands)

    Baskar, L.D.; Schutter, B. de; Hellendoorn, J.; Papp, Z.

    2011-01-01

    Traffic congestion in highway networks is one of the main issues to be addressed by today's traffic management schemes. Automation combined with the increasing market penetration of on-line communication, navigation and advanced driver assistance systems will ultimately result in intelligent vehicle

  19. Day-ahead tariffs for the alleviation of distribution grid congestion from electric vehicles

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Wu, Qiuwei; Østergaard, Jacob

    2012-01-01

    An economically efficient day-ahead tariff (DT) is proposed with the purpose of preventing the distribution grid congestion resulting from electric vehicle (EV) charging scheduled on a dayahead basis. The DT concept developed herein is derived from the locational marginal price (LMP), in particular...... the congestion cost component of the LMP. A step-wise congestion management structure has been developed whereby the distribution system operator (DSO) predicts congestion for the coming day and publishes DTs prior to the clearing of the day-ahead market. EV fleet operators (FOs) optimize their EV charging...... schedules with respect to the predicted day-ahead prices and the published DTs, thereby avoiding congestion while still minimizing the charging cost. A Danish 400V distribution network is used to carry out case studies to illustrate the effectiveness of the developed concept for the prevention...

  20. Congestion Control in Data Transmission Networks Sliding Mode and Other Designs

    CERN Document Server

    Ignaciuk, Przemysław

    2013-01-01

    Congestion Control in Data Transmission Networks details the modeling and control of data traffic in communication networks. It shows how various networking phenomena can be represented in a consistent mathematical framework suitable for rigorous formal analysis. The monograph differentiates between fluid-flow continuous-time traffic models, discrete-time processes with constant sampling rates, and sampled-data systems with variable discretization periods. The authors address a number of difficult real-life problems, such as: • optimal control of flows with disparate, time-varying delay; • the existence of source and channel nonlinearities; • the balancing of quality of service and fairness requirements; and • the incorporation of variable rate allocation policies. Appropriate control mechanisms which can handle congestion and guarantee high throughput in various traffic scenarios (with different networking phenomena being considered) are proposed. Systematic design procedures using sound control-theo...

  1. Avoiding congestion in recommender systems

    International Nuclear Information System (INIS)

    Ren, Xiaolong; Lü, Linyuan; Liu, Runran; Zhang, Jianlin

    2014-01-01

    Recommender systems use the historical activities and personal profiles of users to uncover their preferences and recommend objects. Most of the previous methods are based on objects’ (and/or users’) similarity rather than on their difference. Such approaches are subject to a high risk of increasingly exposing users to a narrowing band of popular objects. As a result, a few objects may be recommended to an enormous number of users, resulting in the problem of recommendation congestion, which is to be avoided, especially when the recommended objects are limited resources. In order to quantitatively measure a recommendation algorithm's ability to avoid congestion, we proposed a new metric inspired by the Gini index, which is used to measure the inequality of the individual wealth distribution in an economy. Besides this, a new recommendation method called directed weighted conduction (DWC) was developed by considering the heat conduction process on a user–object bipartite network with different thermal conductivities. Experimental results obtained for three benchmark data sets showed that the DWC algorithm can effectively avoid system congestion, and greatly improve the novelty and diversity, while retaining relatively high accuracy, in comparison with the state-of-the-art methods. (paper)

  2. CONTROLLING TRAFFIC FLOW IN MULTILANE-ISOLATED INTERSECTION USING ANFIS APPROACH TECHNIQUES

    OpenAIRE

    G. R. LAI; A. CHE SOH; H. MD. SARKAN; R. Z. ABDUL RAHMAN; M. K. HASSAN

    2015-01-01

    Many controllers have applied the Adaptive Neural-Fuzzy Inference System (ANFIS) concept for optimizing the controller performance. However, there are less traffic signal controllers developed using the ANFIS concept. ANFIS traffic signal controller with its fuzzy rule base and its ability to learn from a set of sample data could improve the performance of Existing traffic signal controlling system to reduce traffic congestions at most of the busy traffic intersections in city such as Kuala L...

  3. Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.

    Science.gov (United States)

    Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe

    2017-10-01

    Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.

  4. Adaptive Traffic Control Systems in a medium-sized Scandinavian city

    DEFF Research Database (Denmark)

    Agerholm, Niels; Olesen, Anne Vingaard

    2018-01-01

    Adaptive Traffic Control Systems (ATCS) are aimed at reducing congestion. ATCS adapt to approaching traffic to continuously optimise the traffic flows in question. ATCS have been implemented in many locations, including the Scandinavian countries, with various effects. Due to congestion problems......, and GPS data from a range of cars driving on the ring road formed the basis for the study. The result of ATCS implementation was a significant 17% reduction in transportation time on the ring road in the most congested period, the afternoon peak. Less significant effects were found regarding the morning...

  5. The Effect of Queueing Strategy on Network Traffic

    International Nuclear Information System (INIS)

    Zhang Xue-Jun; Guan Xiang-Min; Sun Deng-Feng; Tang Shao-Ting

    2013-01-01

    In recent years, the transportation system has been faced by increasing challenge in congestion and inefficiency, and research in traffic network has become a significant area of interest. In this paper, we introduce a dynamic-information-based (DIB) queueing strategy into network traffic model under the efficient routing strategy. DIB makes a packet with higher priority to be delivered if there are less packets travelling along its path from the current node to the destination. It is found that, compared with the traditional first-in-first-out (FIFO) queueing strategy, DIB can effectively balance the traffic load of the system via delaying packets to be delivered to congested nodes. Although the network capacity has no obvious changes, some other indexes which reflect transportation efficiency are efficiently improved in the congestion state. Besides, extensive simulation results and discussions are provided to explain the phenomena. The results may provide novel insights for research on traffic systems. (condensed matter: structural, mechanical, and thermal properties)

  6. Understanding how roadside concentrations of NOx are influenced by the background levels, traffic density, and meteorological conditions using Boosted Regression Trees

    Science.gov (United States)

    Sayegh, Arwa; Tate, James E.; Ropkins, Karl

    2016-02-01

    Oxides of Nitrogen (NOx) is a major component of photochemical smog and its constituents are considered principal traffic-related pollutants affecting human health. This study investigates the influence of background concentrations of NOx, traffic density, and prevailing meteorological conditions on roadside concentrations of NOx at UK urban, open motorway, and motorway tunnel sites using the statistical approach Boosted Regression Trees (BRT). BRT models have been fitted using hourly concentration, traffic, and meteorological data for each site. The models predict, rank, and visualise the relationship between model variables and roadside NOx concentrations. A strong relationship between roadside NOx and monitored local background concentrations is demonstrated. Relationships between roadside NOx and other model variables have been shown to be strongly influenced by the quality and resolution of background concentrations of NOx, i.e. if it were based on monitored data or modelled prediction. The paper proposes a direct method of using site-specific fundamental diagrams for splitting traffic data into four traffic states: free-flow, busy-flow, congested, and severely congested. Using BRT models, the density of traffic (vehicles per kilometre) was observed to have a proportional influence on the concentrations of roadside NOx, with different fitted regression line slopes for the different traffic states. When other influences are conditioned out, the relationship between roadside concentrations and ambient air temperature suggests NOx concentrations reach a minimum at around 22 °C with high concentrations at low ambient air temperatures which could be associated to restricted atmospheric dispersion and/or to changes in road traffic exhaust emission characteristics at low ambient air temperatures. This paper uses BRT models to study how different critical factors, and their relative importance, influence the variation of roadside NOx concentrations. The paper

  7. Congestion patterns of electric vehicles with limited battery capacity

    Science.gov (United States)

    2018-01-01

    The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm. PMID:29543875

  8. Congestion patterns of electric vehicles with limited battery capacity.

    Science.gov (United States)

    Jing, Wentao; Ramezani, Mohsen; An, Kun; Kim, Inhi

    2018-01-01

    The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm.

  9. MOE-Analysis for Oversaturated Flow with Interrupted Facility and Heterogeneous Traffic for Urban Roads

    Directory of Open Access Journals (Sweden)

    Hemant Kumar Sharma

    2012-09-01

    Full Text Available Speed-flow functions have been developed by several transportation experts to predict accurately the speed of urban road networks. HCM Speed-Flow Curve, BPR Curve, MTC Speed-Flow Curve, Akçelik Speed-Flow Curve are some extraordinary efforts to define the shape of speed-flow curves. However, the complexity of driver's behaviour, interactions among different type of vehicles, lateral clearance, co-relation of driver's psychology with vehicular characteristics and interdependence of various variables of traffic has led to continuous development and refinement of speed-flow curves. The problem gets more difficult in the case of urban roads with heterogeneous traffic, oversaturated flow and signalized network (which includes some unsignalized intersections as well. This paper presents analysis for various measures of effectiveness (MOE for urban roads with interrupted flow comprising heterogeneous traffic. Model has been developed for heterogeneous traffic under constraints of roadway geometry, vehicle characteristics, driving behaviour and traffic controls. The model developed in this paper predicts speed, delay, average queue and maximum queue estimates for urban roads and quantifies congestion for oversaturated conditions. The investigation details the oversaturated portion of flow in particular.

  10. Design, Implementation and Evaluation of Congestion Control Mechanism for Video Streaming

    OpenAIRE

    Hiroshi Noborio; Hiroyuki Hisamatsu; Hiroki Oda

    2011-01-01

    In recent years, video streaming services over TCP, such as YouTube, have become more and more popular. TCP NewReno, the current TCP standard, performs greedy congestion control, which increases the congestion window size until packet loss occurs. Therefore, because TCP transmits data at a much higher rate than the video playback rate, the probability of packet loss in the network increases, which in turn takes bandwidth from other network traffic. In this paper, we propose a new transport-la...

  11. Intelligent transportation systems in improving traffic flow in tourism destinations

    OpenAIRE

    Mrnjavac, Edna; Marsanic, Robert

    2007-01-01

    The rapid growth and development of motorisation combined with relatively small investments made to improving transportation infrastructure in cities, as well as in tourism destinations, has led to serious problems in the unobstructed movement of vehicles in public traffic areas. Traffic congestion on roadways, in ferryboat ports and at state borders during the summer months and year-round lines of cars going to or returning from work are a regular presence in traffic in most urban and touris...

  12. Expanding the Scope of Sustainability Planning: Lessons from Stockholm’s Congestion Charging Policy

    Directory of Open Access Journals (Sweden)

    Amy Rader Olsson

    2017-10-01

    Full Text Available In 2007, after years of unresolved debate, the Swedish parliament approved a congestion charge for Stockholm applied to cars crossing the city’s inner boundary. Since its introduction, congestion charging has led to an even more lasting reduction of car trips to the city center, in part because the policy generates revenues for financing new subway extensions and uses these same resources as the basis for negotiating new transit oriented housing in subway extension areas. As such, congestion charging is arguably as much a sustainable housing solution as it is a narrowly defined transit policy for reducing automobile congestion or pollution. This article investigates how and why Stockholm, despite considerable political conflict, technical complexity and negative public opinion, was able to turn a long-standing and controversial debate over moderating automobile traffic via tolls into widespread support for a national congestion tax, which itself laid the groundwork for a more expansive sustainability agenda. It further suggests that only when congestion charging was strategically reframed and widely recognized as addressing the concerns of multiple and competing constituencies, did efforts for its adoption translate into larger sustainability gains.

  13. A Multilevel Congestion-Based Global Router

    Directory of Open Access Journals (Sweden)

    Logan Rakai

    2009-01-01

    Full Text Available Routing in nanometer nodes creates an elevated level of importance for low-congestion routing. At the same time, advances in mathematical programming have increased the power to solve complex problems, such as the routing problem. Hence, new routing methods need to be developed that can combine advanced mathematical programming and modeling techniques to provide low-congestion solutions. In this paper, a hierarchical mathematical programming-based global routing technique that considers congestion is proposed. The main contributions presented in this paper include (i implementation of congestion estimation based on actual routing solutions versus purely probabilistic techniques, (ii development of a congestion-based hierarchy for solving the global routing problem, and (iii generation of a robust framework for solving the routing problem using mathematical programming techniques. Experimental results illustrate that the proposed global router is capable of reducing congestion and overflow by as much as 36% compared to the state-of-the-art mathematical programming models.

  14. The effects of congestions tax on air quality and health

    Science.gov (United States)

    Johansson, Christer; Burman, Lars; Forsberg, Bertil

    The "Stockholm Trial" involved a road pricing system to improve the air quality and reduce traffic congestion. The test period of the trial was January 3-July 31, 2006. Vehicles travelling into and out of the charge cordon were charged for every passage during weekdays. The amount due varied during the day and was highest during rush hours (20 SEK = 2.2 EUR, maximum 60 SEK per day). Based on measured and modelled changes in road traffic it was estimated that this system resulted in a 15% reduction in total road use within the charged cordon. Total traffic emissions in this area of NO x and PM10 fell by 8.5% and 13%, respectively. Air quality dispersion modelling was applied to assess the effect of the emission reductions on ambient concentrations and population exposure. For the situations with and without the trial, meteorological conditions and other emissions than from road traffic were kept the same. The calculations show that, with a permanent congestion tax system like the Stockholm Trial, the annual average NO x concentrations would be lower by up to 12% along the most densely trafficked streets. PM10 concentrations would be up to 7% lower. The limit values for both PM10 and NO 2 would still be exceeded along the most densely trafficked streets. The total population exposure of NO x in Greater Stockholm (35 × 35 km with 1.44 million people) is estimated to decrease with a rather modest 0.23 μg m -3. However, based on a long-term epidemiological study, that found an increased mortality risk of 8% per 10 μg m -3 NO x, it is estimated that 27 premature deaths would be avoided every year. According to life-table analysis this would correspond to 206 years of life gained over 10 years per 100 000 people following the trial if the effects on exposures would persist. The effect on mortality is attributed to road traffic emissions (likely vehicle exhaust particles); NO x is merely regarded as an indicator of traffic exposure. This is only the tip of the ice

  15. Congestion management in liberalized market environment

    International Nuclear Information System (INIS)

    2006-01-01

    This paper is based on the survey conducted by WG C5.4 on congestion management. It describes market conditions and institutional arrangements in the 18 countries participating in the survey, and internal and cross-border congestion management. The interaction with the electricity market is discussed, considering allocation of transmission capacity, market schedule, congestion management tools and payment for the costs incurred. The survey shows that there is a tendency towards the use of market-based methods. (author)

  16. Development of a prediction model for crash occurrence by analyzing traffic crash and citation data : final report.

    Science.gov (United States)

    2017-04-30

    It is commonly acknowledged that factors such as human factors, vehicle characteristics, road design and environmental factors highly contribute to the occurrence of traffic crashes (WHO, 2004). Since human factors usually have the most significant i...

  17. Development of a Computational Framework for Big Data-Driven Prediction of Long-Term Bridge Performance and Traffic Flow

    Science.gov (United States)

    2018-04-01

    Consistent efforts with dense sensor deployment and data gathering processes for bridge big data have accumulated profound information regarding bridge performance, associated environments, and traffic flows. However, direct applications of bridge bi...

  18. Over-the-Horizon Awareness for Advanced Driver Assistance Systems: the TrafficFilter and microSlotted 1-Persistence Flooding

    NARCIS (Netherlands)

    van Eenennaam, Martijn; Heijenk, Geert; Karagiannis, Georgios; van Arem, Bart

    2011-01-01

    Vehicle-to-vehicle communications (V2V) is a promising technique for Advanced Driver Assistance Systems to increase traffic safety and efficiency. A proposed system is the Congestion Assistant, which supports drivers when approaching and driving in traffic congestion. Studies have shown great

  19. Characterizing Longitude-Dependent Orbital Debris Congestion in the Geosynchronous Orbit Regime

    Science.gov (United States)

    Anderson, Paul V.

    The geosynchronous orbit (GEO) is a unique commodity of the satellite industry that is becoming increasingly contaminated with orbital debris, but is heavily populated with high-value assets from the civil, commercial, and defense sectors. The GEO arena is home to hundreds of communications, data transmission, and intelligence satellites collectively insured for an estimated 18.3 billion USD. As the lack of natural cleansing mechanisms at the GEO altitude renders the lifetimes of GEO debris essentially infinite, conjunction and risk assessment must be performed to safeguard operational assets from debris collisions. In this thesis, longitude-dependent debris congestion is characterized by predicting the number of near-miss events per day for every longitude slot at GEO, using custom debris propagation tools and a torus intersection metric. Near-miss events with the present-day debris population are assigned risk levels based on GEO-relative position and speed, and this risk information is used to prioritize the population for debris removal target selection. Long-term projections of debris growth under nominal launch traffic, mitigation practices, and fragmentation events are also discussed, and latitudinal synchronization of the GEO debris population is explained via node variations arising from luni-solar gravity. In addition to characterizing localized debris congestion in the GEO ring, this thesis further investigates the conjunction risk to operational satellites or debris removal systems applying low-thrust propulsion to raise orbit altitude at end-of-life to a super-synchronous disposal orbit. Conjunction risks as a function of thrust level, miss distance, longitude, and semi-major axis are evaluated, and a guidance method for evading conjuncting debris with continuous thrust by means of a thrust heading change via single-shooting is developed.

  20. Research on Influence and Prediction Model of Urban Traffic Link Tunnel curvature on Fire Temperature Based on Pyrosim--SPSS Multiple Regression Analysis

    Science.gov (United States)

    Li, Xiao Ju; Yao, Kun; Dai, Jun Yu; Song, Yun Long

    2018-05-01

    The underground space, also known as the “fourth dimension” of the city, reflects the efficient use of urban development intensive. Urban traffic link tunnel is a typical underground limited-length space. Due to the geographical location, the special structure of space and the curvature of the tunnel, high-temperature smoke can easily form the phenomenon of “smoke turning” and the fire risk is extremely high. This paper takes an urban traffic link tunnel as an example to focus on the relationship between curvature and the temperature near the fire source, and use the pyrosim built different curvature fire model to analyze the influence of curvature on the temperature of the fire, then using SPSS Multivariate regression analysis simulate curvature of the tunnel and fire temperature data. Finally, a prediction model of urban traffic link tunnel curvature on fire temperature was proposed. The regression model analysis and test show that the curvature is negatively correlated with the tunnel temperature. This model is feasible and can provide a theoretical reference for the urban traffic link tunnel fire protection design and the preparation of the evacuation plan. And also, it provides some reference for other related curved tunnel curvature design and smoke control measures.

  1. Day-Ahead Congestion Management in Distribution Systems through Household Demand Response and Distribution Congestion Prices

    DEFF Research Database (Denmark)

    Liu, Weijia; Wu, Qiuwei; Wen, Fushuan

    2014-01-01

    into balancing power might challenge the operation of electric distribution systems and cause congestions. This paper presents a distribution congestion price (DCP) based market mechanism to alleviate possible distribution system congestions. By employing the loca- tional marginal pricing (LMP) model...... is proposed. Finally, a practical Danish 60kV/10.5kV distribution system is employed as the test case to verify the proposed method for mitigating congestion....

  2. The Stability of Multi-modal Traffic Network

    International Nuclear Information System (INIS)

    Han Linghui; Sun Huijun; Zhu Chengjuan; Jia Bin; Wu Jianjun

    2013-01-01

    There is an explicit and implicit assumption in multimodal traffic equilibrium models, that is, if the equilibrium exists, then it will also occur. The assumption is very idealized; in fact, it may be shown that the quite contrary could happen, because in multimodal traffic network, especially in mixed traffic conditions the interaction among traffic modes is asymmetric and the asymmetric interaction may result in the instability of traffic system. In this paper, to study the stability of multimodal traffic system, we respectively present the travel cost function in mixed traffic conditions and in traffic network with dedicated bus lanes. Based on a day-to-day dynamical model, we study the evolution of daily route choice of travelers in multimodal traffic network using 10000 random initial values for different cases. From the results of simulation, it can be concluded that the asymmetric interaction between the cars and buses in mixed traffic conditions can lead the traffic system to instability when traffic demand is larger. We also study the effect of travelers' perception error on the stability of multimodal traffic network. Although the larger perception error can alleviate the effect of interaction between cars and buses and improve the stability of traffic system in mixed traffic conditions, the traffic system also become instable when the traffic demand is larger than a number. For all cases simulated in this study, with the same parameters, traffic system with dedicated bus lane has better stability for traffic demand than that in mixed traffic conditions. We also find that the network with dedicated bus lane has higher portion of travelers by bus than it of mixed traffic network. So it can be concluded that building dedicated bus lane can improve the stability of traffic system and attract more travelers to choose bus reducing the traffic congestion. (general)

  3. Congestion analysis of unsignalized intersections

    NARCIS (Netherlands)

    Abhishek,; Mandjes, M.R.H.; Boon, M.A.A.; Nunez Queija, R.

    2016-01-01

    This paper considers an unsignalized intersection used by two traffic streams. A stream of cars is using a primary road, and has priority over the other, low-priority, stream. Cars belonging to the latter stream cross the primary road if the gaps between two subsequent cars on the primary road is

  4. A Comparative Analysis and Prediction of Traffic Accident Causalities in the Sultanate of Oman using Artificial Neural Networks and Statistical methods

    Directory of Open Access Journals (Sweden)

    Galal A. Ali

    1998-12-01

    Full Text Available Traffic accidents are among the major causes of death in the Sultanate of Oman This is particularly the case in the age group of I6 to 25. Studies indicate that, in spite of Oman's high population-per-vehicle ratio, its fatality rate per l0,000 vehicles is one of the highest in the world. This alarming Situation underlines the importance of analyzing traffic accident data and predicting accident casualties. Such steps will lead to understanding the underlying causes of traffic accidents, and thereby to devise appropriate measures to reduce the number of car accidents and enhance safety standards. In this paper, a comparative study of car accident casualties in Oman was undertaken. Artificial Neural Networks (ANNs were used to analyze the data and make predictions of the number of accident casualties. The results were compared with those obtained from the analysis and predictions by regression techniques. Both approaches attempted to model accident casualties using historical  data on related factors, such as population, number of cars on the road and so on, covering the period from I976 to 1994. Forecasts for the years 1995 to 2000 were made using ANNs and regression equations. The results from ANNs provided the best fit for the data. However, it was found that ANNs gave lower forecasts relative to those obtained by the regression methods used, indicating that ANNs are suitable for interpolation but their use for extrapolation may be limited. Nevertheless, the study showed that ANNs provide a potentially powerful tool in analyzing and forecasting traffic accidents and casualties.

  5. Simplified web-based decision support method for traffic management and work zone analysis.

    Science.gov (United States)

    2015-06-01

    Traffic congestion mitigation is one of the key challenges that transportation planners and operations engineers face when : planning for construction and maintenance activities. There is a wide variety of approaches and methods that address work : z...

  6. Minnesota urban partnership agreement national evaluation : traffic system data test plan.

    Science.gov (United States)

    2009-11-17

    This report presents the traffic system data test plan for the Minnesota Urban Partnership Agreement (UPA) under the United States Department of Transportation (U.S. DOT) UPA Program. The Minnesota UPA projects focus on reducing congestion by employi...

  7. The indicative effects of inefficient urban traffic flow on fuel cost and exhaust air pollutant emissions

    CSIR Research Space (South Africa)

    Moselakgomo, M

    2015-07-01

    Full Text Available Poor urban traffic management such as poor intersection controls, congestions, illegal roadway blockages and construction works causes “stop-go” driving conditions with excessive idling resulting in wasted fuel and increased air pollutant emissions...

  8. A new casemix adjustment index for hospital mortality among patients with congestive heart failure.

    Science.gov (United States)

    Polanczyk, C A; Rohde, L E; Philbin, E A; Di Salvo, T G

    1998-10-01

    Comparative analysis of hospital outcomes requires reliable adjustment for casemix. Although congestive heart failure is one of the most common indications for hospitalization, congestive heart failure casemix adjustment has not been widely studied. The purposes of this study were (1) to describe and validate a new congestive heart failure-specific casemix adjustment index to predict in-hospital mortality and (2) to compare its performance to the Charlson comorbidity index. Data from all 4,608 admissions to the Massachusetts General Hospital from January 1990 to July 1996 with a principal ICD-9-CM discharge diagnosis of congestive heart failure were evaluated. Massachusetts General Hospital patients were randomly divided in a derivation and a validation set. By logistic regression, odds ratios for in-hospital death were computed and weights were assigned to construct a new predictive index in the derivation set. The performance of the index was tested in an internal Massachusetts General Hospital validation set and in a non-Massachusetts General Hospital external validation set incorporating data from all 1995 New York state hospital discharges with a primary discharge diagnosis of congestive heart failure. Overall in-hospital mortality was 6.4%. Based on the new index, patients were assigned to six categories with incrementally increasing hospital mortality rates ranging from 0.5% to 31%. By logistic regression, "c" statistics of the congestive heart failure-specific index (0.83 and 0.78, derivation and validation set) were significantly superior to the Charlson index (0.66). Similar incrementally increasing hospital mortality rates were observed in the New York database with the congestive heart failure-specific index ("c" statistics 0.75). In an administrative database, this congestive heart failure-specific index may be a more adequate casemix adjustment tool to predict hospital mortality in patients hospitalized for congestive heart failure.

  9. Collective benefits in traffic during mega events via the use of information technologies.

    Science.gov (United States)

    Xu, Yanyan; González, Marta C

    2017-04-01

    Information technologies today can inform each of us about the route with the shortest time, but they do not contain incentives to manage travellers such that we all get collective benefits in travel times. To that end we need travel demand estimates and target strategies to reduce the traffic volume from the congested roads during peak hours in a feasible way. During large events, the traffic inconveniences in large cities are unusually high, yet temporary, and the entire population may be more willing to adopt collective recommendations for collective benefits in traffic. In this paper, we integrate, for the first time, big data resources to estimate the impact of events on traffic and propose target strategies for collective good at the urban scale. In the context of the Olympic Games in Rio de Janeiro, we first predict the expected increase in traffic. To that end, we integrate data from mobile phones, Airbnb, Waze and transit information, with game schedules and expected attendance in each venue. Next, we evaluate different route choice scenarios for drivers during the peak hours. Finally, we gather information on the trips that contribute the most to the global congestion which could be redirected from vehicles to transit. Interestingly, we show that (i) following new route alternatives during the event with individual shortest times can save more collective travel time than keeping the routine routes used before the event, uncovering the positive value of information technologies during events; (ii) with only a small proportion of people selected from specific areas switching from driving to public transport, the collective travel time can be reduced to a great extent. Results are presented online for evaluation by the public and policymakers (www.flows-rio2016.com (last accessed 3 September 2017)). © 2017 The Author(s).

  10. Bisoprolol for congestive heart failure

    DEFF Research Database (Denmark)

    Rosenberg, J.; Gustafsson, F.

    2008-01-01

    Background: beta-Blockers are a cornerstone in the treatment of systolic heart failure treatment, but not all beta-blockers are effective or in this setting. Objective: To define the role of bisoprolol, a highly selective beta(1)-antagonist in congestive heart failure due to systolic dysfunction....... Methods: Using the keywords 'bisoprolol' and 'heart failure' PubMed and BIOSIS databases were searched for information regarding pharmacology and relevant randomised clinical trials. Supplementary publications were acquired by scrutinising reference lists of relevant papers. Additional information...... was obtained from the FDA website. Conclusion: Bisoprolol is an effective and well-tolerated first-line beta-blocker for patients with systolic heart failure. The knowledge is primarily based on study patients with moderate-to-severe heart failure from the three CIBIS trials Udgivelsesdato: 2008/2...

  11. Real time traffic models, decision support for traffic management

    NARCIS (Netherlands)

    Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  12. Real Time Traffic Models, Decision Support for Traffic Management

    NARCIS (Netherlands)

    Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  13. SYSTEM ANALYSIS OF MAJOR TRENDS IN DEVELOPMENT OF ADAPTIVE TRAFFIC FLOW MANAGEMENT METHODS

    Directory of Open Access Journals (Sweden)

    A. N. Klimovich

    2017-01-01

    Full Text Available Adaptive algorithms, which current traffic systems are based on, exist for many decades. Information technologies have developed significantly over this period and it makes more relevant their application in the field of transport. This paper analyses modern trends in the development of adaptive traffic flow control methods. Reviewed the most perspective directions in the field of intelligent transport systems, such as high-speed wireless communication between vehicles and road infrastructure based on such technologies as DSRC and WAVE, traffic jams prediction having such features as traffic flow information, congestion, velocity of vehicles using machine learning, fuzzy logic rules and genetic algorithms, application of driver assistance systems to increase vehicle’s autonomy. Advantages of such technologies in safety, efficiency and usability of transport are shown. Described multi-agent approach, which uses V2I-communication between vehicles and intersection controller to improve efficiency of control due to more complete traffic flow information and possibility to give orders to separate vehicles. Presented number of algorithms which use such approach to create new generation of adaptive transport systems.

  14. A Survey on Urban Traffic Management System Using Wireless Sensor Networks

    Science.gov (United States)

    Nellore, Kapileswar; Hancke, Gerhard P.

    2016-01-01

    Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research. PMID:26828489

  15. Fixed Point Learning Based Intelligent Traffic Control System

    Science.gov (United States)

    Zongyao, Wang; Cong, Sui; Cheng, Shao

    2017-10-01

    Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

  16. Relationship Between Carbon Dioxide Levels and Reported Congestion and Headaches on the International Space Station

    Science.gov (United States)

    Cole, Robert; Wear, Mary; Young, Millennia; Cobel, Christopher; Mason, Sara

    2017-01-01

    Congestion is commonly reported during spaceflight, and most crewmembers have reported using medications for congestion during International Space Station (ISS) missions. Although congestion has been attributed to fluid shifts during spaceflight, fluid status reaches equilibrium during the first week after launch while congestion continues to be reported throughout long duration missions. Congestion complaints have anecdotally been reported in relation to ISS CO2 levels; this evaluation was undertaken to determine whether or not an association exists. METHODS: Reported headaches, congestion symptoms, and CO2 levels were obtained for ISS expeditions 2-31, and time-weighted means and single-point maxima were determined for 24-hour (24hr) and 7-day (7d) periods prior to each weekly private medical conference. Multiple imputation addressed missing data, and logistic regression modeled the relationship between probability of reported event of congestion or headache and CO2 levels, adjusted for possible confounding covariates. The first seven days of spaceflight were not included to control for fluid shifts. Data were evaluated to determine the concentration of CO2 required to maintain the risk of congestion below 1% to allow for direct comparison with a previously published evaluation of CO2 concentrations and headache. RESULTS: This study confirmed a previously identified significant association between CO2 and headache and also found a significant association between CO2 and congestion. For each 1-mm Hg increase in CO2, the odds of a crew member reporting congestion doubled. The average 7-day CO2 would need to be maintained below 1.5 mmHg to keep the risk of congestion below 1%. The predicted probability curves of ISS headache and congestion curves appear parallel when plotted against ppCO2 levels with congestion occurring at approximately 1mmHg lower than a headache would be reported. DISCUSSION: While the cause of congestion is multifactorial, this study showed

  17. Study on the propagation and dissipation of inland ship congestion under different control strategies

    Science.gov (United States)

    Chen, Yanyi; Wu, Hongyu; Wen, Zhe

    2017-05-01

    Inland waterway transportation is an important part of the comprehensive transportation system of sustainable development, and it is also a way of transportation which is restricted by natural conditions greatly. In recent years, the problems of insufficient traffic capacity of The Three Gorges become prominent due to the increasing in the number of ships. And the ship's detention caused by gale, frog, accident and one-way traffic in dry season has occurred, which not only increased the pressure of the navigable waterway but also seriously affected the safety of shipping. Based on the different types of ships, the Arena software was used to simulate the ship traffic flow. The paper analyzed the traffic congestion propagation and dissipation rule of the ship under different navigation control methods, and provided decision reference for the navigation management department to formulate the relevant navigation control strategy.

  18. Managing Recurrent Congestion of Subway Network in Peak Hours with Station Inflow Control

    OpenAIRE

    Qingru Zou; Xiangming Yao; Peng Zhao; Fei Dou; Taoyuan Yang

    2018-01-01

    Station inflow control (SIC) is an important and effective method for reducing recurrent congestion during peak hours in the Beijing, Shanghai, and Guangzhou subway systems. This work proposes a practical and efficient method for establishing a static SIC scheme in normal weekdays for large-scale subway networks. First, a traffic assignment model without capacity constraint is utilized to determine passenger flow distributions on the network. An internal relationship between station inflows a...

  19. A Congestion Control System Based on VANET for Small Length Roads

    Directory of Open Access Journals (Sweden)

    Ruchin Jain

    2018-01-01

    Full Text Available As vehicle population has been increasing on a daily basis, this leads towards increased number of accidents. To overcome this issue, Vehicular Ad Hoc Network (VANET has come up with lot of novel ideas such as vehicular communication, navigation and traffic controlling. In this study, the main focus is on congestion control at the intersections which result from unclear ahead. For this purpose, a city lane and intersection model has been proposed to manage vehicle mobility. It shows the actual vehicle to vehicle and vehicle to traffic infrastructure communication. The experiment was conducted using Network Simulator 2 (NS 2. The implementation required modelling the road side unit, traffic control unit, and on-board unit along the roadside. In the simulation, including traffic volume, the distance between two signals, end-to-end delay, packet delivery ratio, throughput and packet lost were taken into consideration. These parameters ensure efficient communication between the traffic signals. This results in improved congestion control and road safety, since the vehicles will be signalled not to enter the junction box and information about other vehicles.

  20. Congestion and flow control in signaling system no. 7: Impacts of intelligent networks and new services

    Science.gov (United States)

    Zepf, Joachim; Rufa, Gerhard

    1994-04-01

    This paper focuses on the transient performance analysis of the congestion and flow control mechanisms in CCITT Signaling System No. 7 (SS7). Special attention is directed to the impacts of the introduction of intelligent services and new applications, e.g., Freephone, credit card services, user-to-user signaling, etc. In particular, we show that signaling traffic characteristics like signaling scenarios or signaling message length as well as end-to-end signaling capabilities have a significant influence on the congestion and flow control and, therefore, on the real-time signaling performance. One important result of our performance studies is that if, e.g., intelligent services are introduced, the SS7 congestion and flow control does not work correctly. To solve this problem, some reinvestigations into these mechanisms would be necessary. Therefore, some approaches, e.g., modification of the Signaling Connection Control Part (SCCP) congestion control, usage of the SCCP relay function, or a redesign of the MTP flow control procedures are discussed in order to guarantee the efficacy of the congestion and flow control mechanisms also in the future.

  1. Application of economic models to estimate the acceptability of a vehicle congestion charge

    Directory of Open Access Journals (Sweden)

    José Carlos Jiménez Serpa

    2017-07-01

    Full Text Available Introduction: Through the study of the problems generated by vehicular traffic congestion during periods of maximum demand, the negative externality of congestion would be assessed using Multinomial Logit, Mixed and econometric models, and willingness to pay through a Pigouvian rate. Objective: In this article, we propose to implement a congestion charge to manage vehicular demand, through the application of declared preference gages and econometric models. Methodology: The study consists of the execution of 6 steps or stages: Background of the problem, Context of study, Methodological Foundations, Specification and estimation of the model, Estimation of the function average cost user and social marginal cost, Results obtained Discussion and report. Results: Analyzing the models obtained from the 2053 observations made through the declared preference surveys, it was observed that in order to discourage the use of the private car, a rate of COP 7000 per vehicle entering the congestion area or area should be charged, which would decrease the Use of Auto Particular in 68.7%, referring to this behavior we can say that the government policies that set the collection of the congestion charge is a policy that does not fit the perception of the users. Conclusions: This research identified the rate that reflects as closely as possible the marginal social cost and the generalized costs of each trip in terms of the impacts on the others. Now if we consider the marginal cost due to congestion, we have that the current demand is excessive, the users enjoy the benefit at a cost of $ 3,100COP, but impose to others a quota of $22,152COP. Finally, it is necessary to strengthen the legal basis with the regulation and creation of a National Vehicle Electronic Identification System, which will allow, in principle, charges for congestion.

  2. Work Environment, Stress, and Driving Anger: A Structural Equation Model for Predicting Traffic Sanctions of Public Transport Drivers

    Science.gov (United States)

    2018-01-01

    Public transport is an effective and sustainable alternative to private vehicle usage, also helping to reduce the environmental impact of driving. However, the work environment of public transport operators is full of adverse conditions, which, together with their high mileage, may increase the occurrence of negative safety outcomes such as traffic accidents, often preceded by risky road behaviors enhanced by stress, anger, and difficult operating conditions. The aims of this study were, first, to determine the association between work-related psychosocial factors and individual characteristics of public transport drivers and the rate of traffic sanctions they are subject to; and second, to assess the mediation of driving anger in this relationship. A sample of professional drivers (57.4% city bus, 17.6% taxi, and 25% inter-urban bus male operators) was used for this cross-sectional study, responding to a five-section survey including demographic data and driving-related factors, psychosocial work factors including job stress, driving stress, risk predisposition, and driving anger. The results of this study showed significant associations between work-related factors: measures of stress and self-reported rates of traffic fines. Second, it was found that driving anger mediates the associations between driving stress, risk predisposition, and traffic sanctions; and partially mediates the association between driving experience, hourly intensity, and job stress. This study supports the idea that traffic penalties reported by public transport rates are preceded by work-related, personality, and other individual factors that, when combined with driving anger, enhance the occurrence of road misbehavior that may affect overall road safety. PMID:29534530

  3. Work Environment, Stress, and Driving Anger: A Structural Equation Model for Predicting Traffic Sanctions of Public Transport Drivers

    Directory of Open Access Journals (Sweden)

    Luis Montoro

    2018-03-01

    Full Text Available Public transport is an effective and sustainable alternative to private vehicle usage, also helping to reduce the environmental impact of driving. However, the work environment of public transport operators is full of adverse conditions, which, together with their high mileage, may increase the occurrence of negative safety outcomes such as traffic accidents, often preceded by risky road behaviors enhanced by stress, anger, and difficult operating conditions. The aims of this study were, first, to determine the association between work-related psychosocial factors and individual characteristics of public transport drivers and the rate of traffic sanctions they are subject to; and second, to assess the mediation of driving anger in this relationship. A sample of professional drivers (57.4% city bus, 17.6% taxi, and 25% inter-urban bus male operators was used for this cross-sectional study, responding to a five-section survey including demographic data and driving-related factors, psychosocial work factors including job stress, driving stress, risk predisposition, and driving anger. The results of this study showed significant associations between work-related factors: measures of stress and self-reported rates of traffic fines. Second, it was found that driving anger mediates the associations between driving stress, risk predisposition, and traffic sanctions; and partially mediates the association between driving experience, hourly intensity, and job stress. This study supports the idea that traffic penalties reported by public transport rates are preceded by work-related, personality, and other individual factors that, when combined with driving anger, enhance the occurrence of road misbehavior that may affect overall road safety.

  4. Work Environment, Stress, and Driving Anger: A Structural Equation Model for Predicting Traffic Sanctions of Public Transport Drivers.

    Science.gov (United States)

    Montoro, Luis; Useche, Sergio; Alonso, Francisco; Cendales, Boris

    2018-03-12

    Public transport is an effective and sustainable alternative to private vehicle usage, also helping to reduce the environmental impact of driving. However, the work environment of public transport operators is full of adverse conditions, which, together with their high mileage, may increase the occurrence of negative safety outcomes such as traffic accidents, often preceded by risky road behaviors enhanced by stress, anger, and difficult operating conditions. The aims of this study were, first, to determine the association between work-related psychosocial factors and individual characteristics of public transport drivers and the rate of traffic sanctions they are subject to; and second, to assess the mediation of driving anger in this relationship. A sample of professional drivers (57.4% city bus, 17.6% taxi, and 25% inter-urban bus male operators) was used for this cross-sectional study, responding to a five-section survey including demographic data and driving-related factors, psychosocial work factors including job stress, driving stress, risk predisposition, and driving anger. The results of this study showed significant associations between work-related factors: measures of stress and self-reported rates of traffic fines. Second, it was found that driving anger mediates the associations between driving stress, risk predisposition, and traffic sanctions; and partially mediates the association between driving experience, hourly intensity, and job stress. This study supports the idea that traffic penalties reported by public transport rates are preceded by work-related, personality, and other individual factors that, when combined with driving anger, enhance the occurrence of road misbehavior that may affect overall road safety.

  5. FPGA Congestion-Driven Placement Refinement

    Energy Technology Data Exchange (ETDEWEB)

    Vicente de, J.

    2005-07-01

    The routing congestion usually limits the complete proficiency of the FPGA logic resources. A key question can be formulated regarding the benefits of estimating the congestion at placement stage. In the last years, it is gaining acceptance the idea of a detailed placement taking into account congestion. In this paper, we resort to the Thermodynamic Simulated Annealing (TSA) algorithm to perform a congestion-driven placement refinement on the top of the common Bounding-Box pre optimized solution. The adaptive properties of TSA allow the search to preserve the solution quality of the pre optimized solution while improving other fine-grain objectives. Regarding the cost function two approaches have been considered. In the first one Expected Occupation (EO), a detailed probabilistic model to account for channel congestion is evaluated. We show that in spite of the minute detail of EO, the inherent uncertainty of this probabilistic model impedes to relieve congestion beyond the sole application of the Bounding-Box cost function. In the second approach we resort to the fast Rectilinear Steiner Regions algorithm to perform not an estimation but a measurement of the global routing congestion. This second strategy allows us to successfully reduce the requested channel width for a set of benchmark circuits with respect to the widespread Versatile Place and Route (VPR) tool. (Author) 31 refs.

  6. Traffic Management as a Service: The Traffic Flow Pattern Classification Problem

    Directory of Open Access Journals (Sweden)

    Carlos T. Calafate

    2015-01-01

    Full Text Available Intelligent Transportation System (ITS technologies can be implemented to reduce both fuel consumption and the associated emission of greenhouse gases. However, such systems require intelligent and effective route planning solutions to reduce travel time and promote stable traveling speeds. To achieve such goal these systems should account for both estimated and real-time traffic congestion states, but obtaining reliable traffic congestion estimations for all the streets/avenues in a city for the different times of the day, for every day in a year, is a complex task. Modeling such a tremendous amount of data can be time-consuming and, additionally, centralized computation of optimal routes based on such time-dependencies has very high data processing requirements. In this paper we approach this problem through a heuristic to considerably reduce the modeling effort while maintaining the benefits of time-dependent traffic congestion modeling. In particular, we propose grouping streets by taking into account real traces describing the daily traffic pattern. The effectiveness of this heuristic is assessed for the city of Valencia, Spain, and the results obtained show that it is possible to reduce the required number of daily traffic flow patterns by a factor of 4210 while maintaining the essence of time-dependent modeling requirements.

  7. The traffic crisis and a tale of two cities: Traffic and air quality in Bangkok and Mexico City

    Energy Technology Data Exchange (ETDEWEB)

    Pendakur, V.S.; Badami, M.G.

    1995-12-31

    This paper focuses on congestion management techniques, traffic congestion levels and air quality. By using data from Bangkok and Mexico City, it illustrates the need for drastic changes in transportation policy tools and techniques for congestion management and for improving environmental quality. New approaches to investment and regulatory policy analysis and implementation are suggested. This requires the inclusion of all costs and benefits (economic and ecological) in the policy matrix so that investment and regulatory policies act in unison. Megacities are dominant in social, political and economic terms. 30 to 60% of national GDP is typically produced in these cities. Their human and motor vehicle populations have been doubling every 15-20 and 6-10 years respectively. They also have the most severe traffic congestion and air quality problems. They have the nation`s highest incidence of poverty and absolute poverty. Large portions of their populations endure severely unhealthy housing and sanitation conditions. Following are important characteristics of urban transportation systems in the megacities: the city centres are heavily congested with motorized traffic; traffic crawl rates vary from 2 to 10 km/hr; car and motorcycle ownership are increasing at annual rates of 10-12% and 15-20% respectively; significant air pollution with no relief in sight; TDM strategies are primarily creating new supply of road capacity; fairly high transit trips with substantial transit investments; weak air pollution monitoring and enforcement; and fairly cheap fuel and high costs of vehicles.

  8. Long-Range Emergency Preemption of Traffic Lights

    Science.gov (United States)

    Bachelder, Aaron

    2005-01-01

    A forwarding system could prove beneficial as an addition to an electronic communication-and-control system that automatically modifies the switching of traffic lights to give priority to emergency vehicles. A system to which the forwarding system could be added could be any of a variety of emergency traffic-signal-preemption systems: these include systems now used in some municipalities as well as advanced developmental systems described in several NASA Tech Briefs articles in recent years. Because of a variety of physical and design limitations, emergency traffic-signal- preemption systems now in use are often limited in range to only one intersection at a time: in a typical system, only the next, closest intersection is preempted for an emergency vehicle. Simulations of gridlock have shown that such systems offer minimal advantages and can even cause additional delays. In analogy to what happens in fluid dynamics, the forwarding system insures that flow at a given location is sustained by guaranteeing downstream flow along the predicted route (typically a main artery) and intersecting routes (typically, side streets). In simplest terms, the forwarding system starts by taking note of any preemption issued by the preemption system to which it has been added. The forwarding system predicts which other intersections could be encountered by the emergency vehicle downstream of the newly preempted intersection. The system then forwards preemption triggers to those intersections. Beyond affording a right of way for the emergency vehicle at every intersection that lies ahead along any likely route from the current position of the vehicle, the forwarding system also affords the benefit of clearing congested roads far ahead of the vehicle. In a metropolitan environment with heavy road traffic, forwarding of preemption triggers could greatly enhance the performance of a pre-existing preemption system.

  9. Ergodicity of Traffic Flow with Constant Penetration Rate for Traffic Monitoring via Floating Vehicle Technique

    Science.gov (United States)

    Gunawan, Fergyanto E.; Abbas, Bahtiar S.; Atmadja, Wiedjaja; Yoseph Chandra, Fajar; Agung, Alexander AS; Kusnandar, Erwin

    2014-03-01

    Traffic congestion in Asian megacities has become extremely worse, and any means to lessen the congestion level is urgently needed. Building an efficient mass transportation system is clearly necessary. However, implementing Intelligent Transportation Systems (ITS) have also been demonstrated effective in various advanced countries. Recently, the floating vehicle technique (FVT), an ITS implementation, has become cost effective to provide real-time traffic information with proliferation of the smartphones. Although many publications have discussed various issues related to the technique, none of them elaborates the discrepancy of a single floating car data (FCD) and the associated fleet data. This work addresses the issue based on an analysis of Sugiyama et al's experimental data. The results indicate that there is an optimum averaging time interval such that the estimated velocity by the FVT reasonably representing the traffic velocity.

  10. Adaptive mechanism-based congestion control for networked systems

    Science.gov (United States)

    Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

    2013-03-01

    In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

  11. How Smog Awareness Influences Public Acceptance of Congestion Charge Policies

    Directory of Open Access Journals (Sweden)

    Lingyi Zhou

    2017-09-01

    Full Text Available Although various studies have investigated public acceptance of congestion charge policies, most of them have focused on behavioral and policy-related factors, and did not consider the moderating influence that individual concern about smog and perceived smog risk may have on public acceptance. This paper takes the congestion charge policy in China, targeted at smog and traffic control, and checks how smog awareness—including smog concerns and perceived smog risks, besides behavioral and policy-related factors—might influence public acceptance of the policy. In this paper, we found both a direct and moderating causal relationship between smog awareness and public acceptance. Based on a sample of 574 valid questionnaires in Beijing and Shanghai in 2016, an ordered logistic regression modeling approach was used to delineate the causality between smog awareness and public acceptance. We found that both smog concerns, such as perceived smog risk, and willingness to pay (WTP were both directly and indirectly positively correlated with public acceptance. These findings imply that policymakers should increase policy fairness with environmental-oriented policy design and should express potential policy effectiveness of the smog controlling policy to citizens to increase their acceptance level.

  12. Network Congestion and Performance Management

    OpenAIRE

    Shewmaker, Andrew Glenn

    2016-01-01

    We increasingly depend on well-behaved networks in the course of every-day activities for business, community, government, science, and recreation. And with more people demanding a greater variety of services comes sharp disagreement about which needs are most important. Unfortunately, today’s technology is inadequate to guarantee the performance of dynamic and diverse workloads in such a way that we are prevented from hurting each other’s goals.No one likes waiting in traffic, whether on a r...

  13. Evaluation of diversion strategies in the context of advanced traffic management systems (ATMS) for an urban traffic corridor with heterogeneous traffic

    Energy Technology Data Exchange (ETDEWEB)

    Korlapati, D.R.

    2007-07-01

    Due to urbanization and accelerated growth in vehicular traffic, most big cities in India face problems related to traffic management resulting in severe congestion, pollution, and a high rate of accidents during peak hours. Lane blocking incidents on arterials or urban traffic corridors cause major disruption to traffic flow. Peak hour congestion with low average speeds and high accident rates are commonly associated with traffic in major cities in India. The situation is deteriorating further as creation of new facilities are almost impossible, with resource and space constraints. In such scenarios, application of advanced technologies seems to offer hope. One such application area is Advanced Traffic Management Systems (ATMS), a component of intelligent transportation system (ITS). Due to the unique traffic characteristics prevailing in India, the application of such systems needs to first be evaluated before implementation. This paper proposed a research methodology for the evaluation of diversion strategies in the context of ATMS for an urban corridor in India. The evaluation framework combined several relevant modules related to various aspects of traffic control, surveillance and advisory. As part of this study, a simulation model and a simulation optimization model were developed. The simulation model was microscopic in nature and captured the driver behaviour and traffic characteristics realistically by modeling the complex interactions among vehicles traversing a corridor. It was concluded that the results and observations were useful indicators to gauge the potential success of diversion plans. 10 refs., 1 tab., 2 figs.

  14. Congested Aggregation via Newtonian Interaction

    Science.gov (United States)

    Craig, Katy; Kim, Inwon; Yao, Yao

    2018-01-01

    We consider a congested aggregation model that describes the evolution of a density through the competing effects of nonlocal Newtonian attraction and a hard height constraint. This provides a counterpoint to existing literature on repulsive-attractive nonlocal interaction models, where the repulsive effects instead arise from an interaction kernel or the addition of diffusion. We formulate our model as the Wasserstein gradient flow of an interaction energy, with a penalization to enforce the constraint on the height of the density. From this perspective, the problem can be seen as a singular limit of the Keller-Segel equation with degenerate diffusion. Two key properties distinguish our problem from previous work on height constrained equations: nonconvexity of the interaction kernel (which places the model outside the scope of classical gradient flow theory) and nonlocal dependence of the velocity field on the density (which causes the problem to lack a comparison principle). To overcome these obstacles, we combine recent results on gradient flows of nonconvex energies with viscosity solution theory. We characterize the dynamics of patch solutions in terms of a Hele-Shaw type free boundary problem and, using this characterization, show that in two dimensions patch solutions converge to a characteristic function of a disk in the long-time limit, with an explicit rate on the decay of the energy. We believe that a key contribution of the present work is our blended approach, combining energy methods with viscosity solution theory.

  15. Development and validation of a multilevel model for predicting workload under routine and nonroutine conditions in an air traffic management center.

    Science.gov (United States)

    Neal, Andrew; Hannah, Sam; Sanderson, Penelope; Bolland, Scott; Mooij, Martijn; Murphy, Sean

    2014-03-01

    The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions. Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem. A multilevel workload model was developed in Study I with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters.The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator. Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically. The model performed well under both routine and nonroutine conditions and over different patterns of workload variation. Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs.Tactical uses include the dynamic reallocation of resources to meet changes in demand.

  16. Urban emissions hotspots: Quantifying vehicle congestion and air pollution using mobile phone GPS data

    International Nuclear Information System (INIS)

    Gately, Conor K.; Hutyra, Lucy R.; Peterson, Scott; Sue Wing, Ian

    2017-01-01

    On-road emissions vary widely on time scales as short as minutes and length scales as short as tens of meters. Detailed data on emissions at these scales are a prerequisite to accurately quantifying ambient pollution concentrations and identifying hotspots of human exposure within urban areas. We construct a highly resolved inventory of hourly fluxes of CO, NO 2 , NO x , PM 2.5 and CO 2 from road vehicles on 280,000 road segments in eastern Massachusetts for the year 2012. Our inventory integrates a large database of hourly vehicle speeds derived from mobile phone and vehicle GPS data with multiple regional datasets of vehicle flows, fleet characteristics, and local meteorology. We quantify the ‘excess’ emissions from traffic congestion, finding modest congestion enhancement (3–6%) at regional scales, but hundreds of local hotspots with highly elevated annual emissions (up to 75% for individual roadways in key corridors). Congestion-driven reductions in vehicle fuel economy necessitated ‘excess’ consumption of 113 million gallons of motor fuel, worth ∼ $415M, but this accounted for only 3.5% of the total fuel consumed in Massachusetts, as over 80% of vehicle travel occurs in uncongested conditions. Across our study domain, emissions are highly spatially concentrated, with 70% of pollution originating from only 10% of the roads. The 2011 EPA National Emissions Inventory (NEI) understates our aggregate emissions of NO x , PM 2.5 , and CO 2 by 46%, 38%, and 18%, respectively. However, CO emissions agree within 5% for the two inventories, suggesting that the large biases in NO x and PM 2.5 emissions arise from differences in estimates of diesel vehicle activity. By providing fine-scale information on local emission hotspots and regional emissions patterns, our inventory framework supports targeted traffic interventions, transparent benchmarking, and improvements in overall urban air quality. - Highlights: • A high resolution, bottom-up inventory of

  17. Congestion based mechanism for route discovery in a V2I-V2V system applying smart devices and IoT.

    Science.gov (United States)

    Parrado, Natalia; Donoso, Yezid

    2015-03-31

    The Internet of Things is a new paradigm in which objects in a specific context can be integrated into traditional communication networks to actively participate in solving a determined problem. The Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) technologies are specific cases of IoT and key enablers for Intelligent Transportation Systems (ITS). V2V and V2I have been widely used to solve different problems associated with transportation in cities, in which the most important is traffic congestion. A high percentage of congestion is usually presented by the inappropriate use of resources in vehicular infrastructure. In addition, the integration of traffic congestion in decision making for vehicular traffic is a challenge due to its high dynamic behavior. In this paper, an optimization model over the load balancing in the congestion percentage of the streets is formulated. Later, we explore a fully congestion-oriented route discovery mechanism and we make a proposal on the communication infrastructure that should support it based on V2I and V2V communication. The mechanism is also compared with a modified Dijkstra's approach that reacts at congestion states. Finally, we compare the results of the efficiency of the vehicle's trip with the efficiency in the use of the capacity of the vehicular network.

  18. Congestion Based Mechanism for Route Discovery in a V2I-V2V System Applying Smart Devices and IoT

    Directory of Open Access Journals (Sweden)

    Natalia Parrado

    2015-03-01

    Full Text Available The Internet of Things is a new paradigm in which objects in a specific context can be integrated into traditional communication networks to actively participate in solving a determined problem. The Vehicle-to-Vehicle (V2V and Vehicle-to-Infrastructure (V2I technologies are specific cases of IoT and key enablers for Intelligent Transportation Systems (ITS. V2V and V2I have been widely used to solve different problems associated with transportation in cities, in which the most important is traffic congestion. A high percentage of congestion is usually presented by the inappropriate use of resources in vehicular infrastructure. In addition, the integration of traffic congestion in decision making for vehicular traffic is a challenge due to its high dynamic behavior. In this paper, an optimization model over the load balancing in the congestion percentage of the streets is formulated. Later, we explore a fully congestion-oriented route discovery mechanism and we make a proposal on the communication infrastructure that should support it based on V2I and V2V communication. The mechanism is also compared with a modified Dijkstra’s approach that reacts at congestion states. Finally, we compare the results of the efficiency of the vehicle’s trip with the efficiency in the use of the capacity of the vehicular network.

  19. Congestion and cascades in payment systems

    Science.gov (United States)

    Beyeler, Walter E.; Glass, Robert J.; Bech, Morten L.; Soramäki, Kimmo

    2007-10-01

    We develop a parsimonious model of the interbank payment system. The model incorporates an endogenous instruction arrival process, a scale-free topology of payments between banks, a fixed total liquidity which limits banks’ capacity to process arriving instructions, and a global market that distributes liquidity. We find that at low liquidity the system becomes congested and payment settlement loses correlation with payment instruction arrival, becoming coupled across the network. The onset of congestion is evidently related to the relative values of three characteristic times: the time for banks’ net position to return to 0, the time for a bank to exhaust its liquidity endowment, and the liquidity market relaxation time. In the congested regime settlement takes place in cascades having a characteristic length scale. A global liquidity market substantially attenuates congestion, requiring only a small fraction of the payment-induced liquidity flow to achieve strong beneficial effects.

  20. A knowledge-based system for controlling automobile traffic

    Science.gov (United States)

    Maravas, Alexander; Stengel, Robert F.

    1994-01-01

    Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

  1. Treatment of congestion in upper respiratory diseases

    Directory of Open Access Journals (Sweden)

    Eli O Meltzer

    2010-02-01

    Full Text Available Eli O Meltzer1, Fernan Caballero2, Leonard M Fromer3, John H Krouse4, Glenis Scadding51Allergy and Asthma Medical Group and Research Center, San Diego, CA and Department of Pediatrics, University of California, San Diego, USA; 2Allergy and Clinical Immunology Service, Centro Medico-Docente La Trinidad, Caracas, Venezuela; 3David Geffen School of Medicine, University of California, Los Angeles, USA; 4Wayne State University School of Medicine, Detroit, Michigan, USA; 5Department of Allergy and Rhinology, Royal National TNE Hospital, London, UKAbstract: Congestion, as a symptom of upper respiratory tract diseases including seasonal and perennial allergic rhinitis, acute and chronic rhinosinusitis, and nasal polyposis, is principally caused by mucosal inflammation. Though effective pharmacotherapy options exist, no agent is universally efficacious; therapeutic decisions must account for individual patient preferences. Oral H1-antihistamines, though effective for the common symptoms of allergic rhinitis, have modest decongestant action, as do leukotriene receptor antagonists. Intranasal antihistamines appear to improve congestion better than oral forms. Topical decongestants reduce congestion associated with allergic rhinitis, but local adverse effects make them unsuitable for long-term use. Oral decongestants show some efficacy against congestion in allergic rhinitis and the common cold, and can be combined with oral antihistamines. Intranasal corticosteroids have broad anti-inflammatory activities, are the most potent long-term pharmacologic treatment of congestion associated with allergic rhinitis, and show some congestion relief in rhinosinusitis and nasal polyposis. Immunotherapy and surgery may be used in some cases refractory to pharmacotherapy. Steps in congestion management include (1 diagnosis of the cause(s, (2 patient education and monitoring, (3 avoidance of environmental triggers where possible, (4 pharmacotherapy, and (5 immunotherapy

  2. Traveller Information System for Heterogeneous Traffic Condition: A Case Study in Thiruvananthapuram City, India

    Science.gov (United States)

    Satyakumar, M.; Anil, R.; Sreeja, G. S.

    2017-12-01

    Traffic in Kerala has been growing at a rate of 10-11% every year, resulting severe congestion especially in urban areas. Because of the limitation of spaces it is not always possible to construct new roads. Road users rely on travel time information for journey planning and route choice decisions, while road system managers are increasingly viewing travel time as an important network performance indicator. More recently Advanced Traveler Information Systems (ATIS) are being developed to provide real-time information to roadway users. For ATIS various methodologies have been developed for dynamic travel time prediction. For this work the Kalman Filter Algorithm was selected for dynamic travel time prediction of different modes. The travel time data collected using handheld GPS device were used for prediction. Congestion Index were calculated and Range of CI values were determined according to the percentage speed drop. After prediction using Kalman Filter, the predicted values along with the GPS data was integrated to GIS and using Network Analysis of ArcGIS the offline route navigation guide was prepared. Using this database a program for route navigation based on travel time was developed. This system will help the travelers with pre-trip information.

  3. Traffic accidents: an econometric investigation

    OpenAIRE

    Tito Moreira; Adolfo Sachsida; Loureiro Paulo

    2004-01-01

    Based on a sample of drivers in Brasilia's streets, this article investigates whether distraction explains traffic accidents. A probit model is estimated to determine the predictive power of several variables on traffic accidents. The main conclusion drawn from this study is that the proxies used to measure distraction, such as the use of cell phones and cigarette smoking in a moving vehicle, are significant factors in determining traffic accidents.

  4. An Adaptive Traffic Signal Control in a Connected Vehicle Environment: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Peng Jing

    2017-08-01

    Full Text Available In the last few years, traffic congestion has become a growing concern due to increasing vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic signal control systems cannot adjust the timing pattern depending on road traffic demand. This results in excessive delays for road users. Adaptive traffic signal control in a connected vehicle environment has shown a powerful ability to effectively alleviate urban traffic congestions to achieve desirable objectives (e.g., delay minimization. Connected vehicle technology, as an emerging technology, is a mobile data platform that enables the real-time data exchange among vehicles and between vehicles and infrastructure. Although several reviews about traffic signal control or connected vehicles have been written, a systemic review of adaptive traffic signal control in a connected vehicle environment has not been made. Twenty-six eligible studies searched from six databases constitute the review. A quality evaluation was established based on previous research instruments and applied to the current review. The purpose of this paper is to critically review the existing methods of adaptive traffic signal control in a connected vehicle environment and to compare the advantages or disadvantages of those methods. Further, a systematic framework on connected vehicle based adaptive traffic signal control is summarized to support the future research. Future research is needed to develop more efficient and generic adaptive traffic signal control methods in a connected vehicle environment.

  5. Dynamic route guidance strategy in a two-route pedestrian-vehicle mixed traffic flow system

    Science.gov (United States)

    Liu, Mianfang; Xiong, Shengwu; Li, Bixiang

    2016-05-01

    With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached.

  6. Focus on renal congestion in heart failure.

    Science.gov (United States)

    Afsar, Baris; Ortiz, Alberto; Covic, Adrian; Solak, Yalcin; Goldsmith, David; Kanbay, Mehmet

    2016-02-01

    Hospitalizations due to heart failure are increasing steadily despite advances in medicine. Patients hospitalized for worsening heart failure have high mortality in hospital and within the months following discharge. Kidney dysfunction is associated with adverse outcomes in heart failure patients. Recent evidence suggests that both deterioration in kidney function and renal congestion are important prognostic factors in heart failure. Kidney congestion in heart failure results from low cardiac output (forward failure), tubuloglomerular feedback, increased intra-abdominal pressure or increased venous pressure. Regardless of the cause, renal congestion is associated with increased morbidity and mortality in heart failure. The impact on outcomes of renal decongestion strategies that do not compromise renal function should be explored in heart failure. These studies require novel diagnostic markers that identify early renal damage and renal congestion and allow monitoring of treatment responses in order to avoid severe worsening of renal function. In addition, there is an unmet need regarding evidence-based therapeutic management of renal congestion and worsening renal function. In the present review, we summarize the mechanisms, diagnosis, outcomes, prognostic markers and treatment options of renal congestion in heart failure.

  7. Evaluation of pulmonary congestion by computed tomography

    International Nuclear Information System (INIS)

    Morooka, Nobuhiro; Yamamoto, Hironori; Yoshida, Hideo; Watanabe, Shigeru; Nakamura, Mamoru

    1980-01-01

    Pulmonary congestion and pulmonary water distribution of lung fields were evaluated by computed tomography (CT) in 31 patients with congestive heart failure and 19 normal subjects in the supine position. In normal subjects, no difference was noted in the CT value between levels of intercostal spaces as well as between right and left lung fields. CT values were greater in posterior lung fields than in anterior lung fields. A significant increase of CT values at both anterior and posterior lung fields was shown in patients with congestive heart failure compared to normal subjects. In congestive heart failure, pulmonary CT values were correlated with various clinical parameters in the order of chest X-ray findings, NYHA functional classification, venous pressure, right heart catheter findings and circulation time. CT values were decreased with the improvement of parameters by medical treatment. Thus, the increase of pulmonary CT values in patients with congestive heart failure indicated the increase of pulmonary blood content and pulmonary tissue edema in a unit volume. This method was particularly useful for the evaluation of pulmonary congestion and pulmonary water distribution. (author)

  8. Improving pedestrian facilities in congested urban areas: a case study of Chennai city

    Science.gov (United States)

    Subramanyam, B.; Prasanna Kumar, R.

    2017-07-01

    Traffic congestion and lack of public pedestrian space are some problems faced by most urban metropolises. Conventionally walking has been a mode of transportation in Indian cities. The percentage of pedestrians may vary from 16 to 57 depending upon the city. Encounters between vehicular traffic and pedestrian traffic are at its rise currently. Rapid industrialization and urbanization in India has resulted in neglecting of pedestrian facilities. Consequently pedestrian are at greater risk for their safety more especially in the commercial zones of large cities. A change in perspective spotlight will create a sense of awareness that the pedestrian traffic is also vital as the vehicular traffic. Soothing the traffic would moderately cut the driving expediency but the pedestrians will get a much safer and peaceful route to their terminuses. Safety and comfort are the two pans of a balance while considering the pedestrian traffic. Considering these aspects, this study deals a study in improving pedestrian facilities by analysing the existing skeleton of the selected locations. The adequacy of facility is checked based on IRC latest guidelines and counteractive measures are postulated.

  9. Suppressing traffic-driven epidemic spreading by adaptive routing strategy

    International Nuclear Information System (INIS)

    Yang, Han-Xin; Wang, Zhen

    2016-01-01

    The design of routing strategies for traffic-driven epidemic spreading has received increasing attention in recent years. In this paper, we propose an adaptive routing strategy that incorporates topological distance with local epidemic information through a tunable parameter h. In the case where the traffic is free of congestion, there exists an optimal value of routing parameter h, leading to the maximal epidemic threshold. This means that epidemic spreading can be more effectively controlled by adaptive routing, compared to that of the static shortest path routing scheme. Besides, we find that the optimal value of h can greatly relieve the traffic congestion in the case of finite node-delivering capacity. We expect our work to provide new insights into the effects of dynamic routings on traffic-driven epidemic spreading.

  10. From Traffic Flow to Economic System

    Science.gov (United States)

    Bando, M.

    The optimal velocity model which is applied to traffic flow phenomena explains a spontaneous formation of traffic congestion. We discuss why the model works well in describing both free-flow and congested flow states in a unified way. The essential ingredient is that our model takes account of a sort of time delay in reacting to a given stimulus. This causes instability of many-body system, and yields a kind of phase transition above a certain critical density. Especially there appears a limit cycle on the phase space along which individual vehicle moves, and they show cyclic behavior. Once that we recognize the mechanism the same idea can be applied to a variety of phenomena which show cyclic behavior observed in many-body systems. As an example of such applications, we investigate business cycles commonly observed in economic system. We further discuss a possible origin of a kind of cyclic behavior observed in climate change.

  11. Link State Relationships Under Incident Conditions: Using a CTM-Based Linear Programming Dynamic Traffic Assignment Model

    Science.gov (United States)

    2010-03-01

    Urban transportation networks, consisting of numerous links and nodes, experience traffic incidents such as accidents and road maintenance work. A typical consequence of incidents is congestion which results in long queues and causes high travel time...

  12. Link state relationships under incident conditions : using a CTM-based linear programming dynamic traffic assignment model.

    Science.gov (United States)

    2010-03-01

    Urban transportation networks, consisting of numerous links and nodes, experience traffic incidents such as accidents and road : maintenance work. A typical consequence of incidents is congestion which results in long queues and causes high travel ti...

  13. Congestion Control for a Fair Packet Delivery in WSN: From a Complex System Perspective

    Directory of Open Access Journals (Sweden)

    Daniela Aguirre-Guerrero

    2014-01-01

    Full Text Available In this work, we propose that packets travelling across a wireless sensor network (WSN can be seen as the active agents that make up a complex system, just like a bird flock or a fish school, for instance. From this perspective, the tools and models that have been developed to study this kind of systems have been applied. This is in order to create a distributed congestion control based on a set of simple rules programmed at the nodes of the WSN. Our results show that it is possible to adapt the carried traffic to the network capacity, even under stressing conditions. Also, the network performance shows a smooth degradation when the traffic goes beyond a threshold which is settled by the proposed self-organized control. In contrast, without any control, the network collapses before this threshold. The use of the proposed solution provides an effective strategy to address some of the common problems found in WSN deployment by providing a fair packet delivery. In addition, the network congestion is mitigated using adaptive traffic mechanisms based on a satisfaction parameter assessed by each packet which has impact on the global satisfaction of the traffic carried by the WSN.

  14. Dynamic methods of air traffic flow management

    Directory of Open Access Journals (Sweden)

    Jacek SKORUPSKI

    2011-01-01

    Full Text Available Air traffic management is a complex hierarchical system. Hierarchy levels can be defined according to decision making time horizon or to analyze area volume. For medium time horizon and wide analysis area, the air traffic flow management services were established. Their main task is to properly co-ordinate air traffic in European airspace, so as to minimize delays arising in congested sectors. Those services have to assure high safety level at the same time. Thus it is a very complex task, with many goals, many decision variables and many constraints.In the paper review of the methods developed for aiding air traffic flow management services is presented. More detailed description of a dynamic method is given. This method is based on stochastic capacity and scenario analysis. Some problems in utilization of presented methods are also pointed out, so are the next research possibilities.

  15. PASSENGER TRAFFIC MOVEMENT MODELLING BY THE CELLULAR-AUTOMAT APPROACH

    Directory of Open Access Journals (Sweden)

    T. Mikhaylovskaya

    2009-01-01

    Full Text Available The mathematical model of passenger traffic movement developed on the basis of the cellular-automat approach is considered. The program realization of the cellular-automat model of pedastrians streams movement in pedestrian subways at presence of obstacles, at subway structure narrowing is presented. The optimum distances between the obstacles and the angle of subway structure narrowing providing pedastrians stream safe movement and traffic congestion occurance are determined.

  16. Characterization of YouTube Video Streaming Traffic

    OpenAIRE

    Ravattu, Radha; Balasetty, Prudhviraj

    2013-01-01

    Online digital videos have made a revolutionary evolution since the social networking sites such as YouTube and Hulu have emerged. These websites facilitate video accessable and only a click away. Ever increasing internet traffic and a very significant increase in the use of videos in social networking has led to the problem of network congestion. Consequently, it becomes essential and imperative to analyze the traffic flow and comprehend how it is being delivered from the server. If the flow...

  17. Traveling waves in an optimal velocity model of freeway traffic

    Science.gov (United States)

    Berg, Peter; Woods, Andrew

    2001-03-01

    Car-following models provide both a tool to describe traffic flow and algorithms for autonomous cruise control systems. Recently developed optimal velocity models contain a relaxation term that assigns a desirable speed to each headway and a response time over which drivers adjust to optimal velocity conditions. These models predict traffic breakdown phenomena analogous to real traffic instabilities. In order to deepen our understanding of these models, in this paper, we examine the transition from a linear stable stream of cars of one headway into a linear stable stream of a second headway. Numerical results of the governing equations identify a range of transition phenomena, including monotonic and oscillating travelling waves and a time- dependent dispersive adjustment wave. However, for certain conditions, we find that the adjustment takes the form of a nonlinear traveling wave from the upstream headway to a third, intermediate headway, followed by either another traveling wave or a dispersive wave further downstream matching the downstream headway. This intermediate value of the headway is selected such that the nonlinear traveling wave is the fastest stable traveling wave which is observed to develop in the numerical calculations. The development of these nonlinear waves, connecting linear stable flows of two different headways, is somewhat reminiscent of stop-start waves in congested flow on freeways. The different types of adjustments are classified in a phase diagram depending on the upstream and downstream headway and the response time of the model. The results have profound consequences for autonomous cruise control systems. For an autocade of both identical and different vehicles, the control system itself may trigger formations of nonlinear, steep wave transitions. Further information is available [Y. Sugiyama, Traffic and Granular Flow (World Scientific, Singapore, 1995), p. 137].

  18. On the statistical description of the inbound air traffic over Heathrow airport

    NARCIS (Netherlands)

    Caccavale, M.V.; Iovanella, A.; Lancia, C.; Lulli, G.; Scoppola, B.

    2013-01-01

    We present a model to describe the inbound air traffic over a congested hub. We show that this model gives a very accurate description of the traffic by the comparison of our theoretical distribution of the queue with the actual distribution observed over Heathrow airport. We discuss also the

  19. Optimizing traffic flow efficiency by controlling lane changes: collective, group and user optima

    NARCIS (Netherlands)

    Yao, S.; Knoop, V.L.; van Arem, B.

    2017-01-01

    Lane changes can lead to disturbances in traffic flow, whilst the uneven distribution of traffic over different lanes as a result of lane changes can also lead to instabilities and congestion on one specific lane. Therefore, giving advice on lane change can be beneficial for both individual drivers

  20. Metering with Traffic Signal Control : Development and Evaluation of an Algorithm

    NARCIS (Netherlands)

    Taale, H.; Hoogendoorn, S.P.; Legius, P.

    2015-01-01

    For some on-ramps, which cause congestion on the motorway, it is not possible to install a ramp metering system for geometric or other reasons. But sometimes it is possible to meter traffic with the traffic lights of nearby intersections in such a way that the situation on the motorway improves and

  1. 76 FR 39153 - Agency Information Collection; Activity Under OMB Review; Report of Traffic and Capacity...

    Science.gov (United States)

    2011-07-05

    ... responsibilities relating to airline competition and consolidation. Traffic Forecasting The FAA uses traffic... FAA develops ways of increasing airport capacity at congested airports. Airline Industry Status... Seguin, Office of Airline Information, RTS-42, Room E34-418, RITA, BTS, 1200 New Jersey Avenue, SE...

  2. BER and FER Prediction of Control and Traffic Channels for a GSM type of interface

    DEFF Research Database (Denmark)

    Wigard, Jeroen; Nielsen, Thomas Toftegaard; Michaelsen, Per Henrik

    1998-01-01

    in a network simulator, but without having to simulate every single link, since this would be to time consuming. In this paper a method is presented to find the BER and FER from the signal to interference (C/I) values for a GSM type of air-interface, which can be used for integration of link aspects...... in a network simulator. The accuracy is within 0.2 dB in case of the BER and 0.5 for the FER. Both traffic and control channels are studied and the method is independent of hopping sequences and speed...

  3. Passive performance monitoring and traffic characteristics on the SLAC internet border

    International Nuclear Information System (INIS)

    Logg, C.; Cottrell, L.

    2001-01-01

    Understanding how the Internet is used by HEP is critical to optimizing the performance of the inter-lab computing environment. Typically use requirements have been defined by discussions between collaborators. However, later analysis of the actual traffic has show this is often misunderstood and actual use is significantly different to that predicted. Passive monitoring of the real traffic provides insight into the true communications requirements and the performance of a large number of inter-communicating nodes. It may be useful in identifying performance problems that are due to factors other than Internet congestion, especially when compared to other methods such as active monitoring where traffic is generated specifically to measure its performance. Controlled active monitoring between dedicated servers often gives an indication of what can be achieved on a network. Passive monitoring of the real traffic gives a picture of the true performance. The authors will discuss the method and results of collecting and analyzing flows of data obtained from the SLAC Internet border. The insights this has brought to understanding the network will be reviewed and the benefit it can bring to engineering networks will be discussed

  4. Emergent traffic jams

    International Nuclear Information System (INIS)

    Nagel, K.; Paczuski, M.

    1995-01-01

    We study a single-lane traffic model that is based on human driving behavior. The outflow from a traffic jam self-organizes to a critical state of maximum throughput. Small perturbations of the outflow far downstream create emergent traffic jams with a power law distribution P(t)∼t -3/2 of lifetimes t. On varying the vehicle density in a closed system, this critical state separates lamellar and jammed regimes and exhibits 1/f noise in the power spectrum. Using random walk arguments, in conjunction with a cascade equation, we develop a phenomenological theory that predicts the critical exponents for this transition and explains the self-organizing behavior. These predictions are consistent with all of our numerical results

  5. Emergent traffic jams

    Science.gov (United States)

    Nagel, Kai; Paczuski, Maya

    1995-04-01

    We study a single-lane traffic model that is based on human driving behavior. The outflow from a traffic jam self-organizes to a critical state of maximum throughput. Small perturbations of the outflow far downstream create emergent traffic jams with a power law distribution P(t)~t-3/2 of lifetimes t. On varying the vehicle density in a closed system, this critical state separates lamellar and jammed regimes and exhibits 1/f noise in the power spectrum. Using random walk arguments, in conjunction with a cascade equation, we develop a phenomenological theory that predicts the critical exponents for this transition and explains the self-organizing behavior. These predictions are consistent with all of our numerical results.

  6. Particle-based model for skiing traffic.

    Science.gov (United States)

    Holleczek, Thomas; Tröster, Gerhard

    2012-05-01

    We develop and investigate a particle-based model for ski slope traffic. Skiers are modeled as particles with a mass that are exposed to social and physical forces, which define the riding behavior of skiers during their descents on ski slopes. We also report position and speed data of 21 skiers recorded with GPS-equipped cell phones on two ski slopes. A comparison of these data with the trajectories resulting from computer simulations of our model shows a good correspondence. A study of the relationship among the density, speed, and flow of skiers reveals that congestion does not occur even with arrival rates of skiers exceeding the maximum ski lift capacity. In a sensitivity analysis, we identify the kinetic friction coefficient of skis on snow, the skier mass, the range of repelling social forces, and the arrival rate of skiers as the crucial parameters influencing the simulation results. Our model allows for the prediction of speed zones and skier densities on ski slopes, which is important in the prevention of skiing accidents.

  7. Suppressing traffic-driven epidemic spreading by use of the efficient routing protocol

    International Nuclear Information System (INIS)

    Yang, Han-Xin; Wu, Zhi-Xi

    2014-01-01

    Despite extensive work on the interplay between traffic dynamics and epidemic spreading, the control of epidemic spreading by routing strategies has not received adequate attention. In this paper, we study the impact of an efficient routing protocol on epidemic spreading. In the case of infinite node-delivery capacity, where the traffic is free of congestion, we find that that there exist optimal values of routing parameter, leading to the maximal epidemic threshold. This means that epidemic spreading can be effectively controlled by fine tuning the routing scheme. Moreover, we find that an increase in the average network connectivity and the emergence of traffic congestion can suppress the epidemic outbreak. (paper)

  8. Traffic signal synchronization in the saturated high-density grid road network.

    Science.gov (United States)

    Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

    2015-01-01

    Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

  9. Macroscopic discontinuity modeling for multiclass multilane traffic flow operations

    NARCIS (Netherlands)

    Ngoduy, D.

    2006-01-01

    Congestion in traffic networks causes severe problems in and around large cities. It is the source of important economic inefficiencies, both on the level of individual persons and of the society as a whole. However, societal and environmental constraints prohibit large-scale extensions of the

  10. Simulation of traffic capacity of inland waterway network

    NARCIS (Netherlands)

    Chen, L.; Mou, J.; Ligteringen, H.

    2013-01-01

    The inland waterborne transportation is viewed as an economic, safe and environmentally friendly alternative to the congested road network. The traffic capacity are the critical indicator of the inland shipping performance. Actually, interacted under the complicated factors, it is challenging to

  11. Examination of fundamental traffic characteristics and implications to ITS

    Science.gov (United States)

    1998-01-01

    The purpose of this paper is to study and analyze the essential traffic characteristics of a 5.4-mile stretch of I-64-40 located within the St. Louis metropolitan area. The freeway experiences heavy congestion during peak periods attributed to factor...

  12. Air pollution emission inventory along a major traffic route within ...

    African Journals Online (AJOL)

    Increasing road congestion and high traffic volume is often times an indicator of atmospheric air pollution. Ibadan, being the largest metropolitan city in southwestern Nigeria, experiences steady influx of vehicular movement on daily bases. The situation is made worse as a greater number of these vehicles are old and ...

  13. A new intelligent approach for air traffic control using gravitational ...

    Indian Academy of Sciences (India)

    Therefore, poor management of this congestion may lead to a lot of flight delays, increase of operational errors by air traffic control personnel ... the PLT [8–11], and decreasing the duration of scheduling. [12, 13]. Hansen [3], Hu ...... [14] Hu X-B and Paolo E D 2009 An efficient genetic algorithm with uniform crossover for air ...

  14. Online traffic flow model applying dynamic flow-density relation

    International Nuclear Information System (INIS)

    Kim, Y.

    2002-01-01

    This dissertation describes a new approach of the online traffic flow modelling based on the hydrodynamic traffic flow model and an online process to adapt the flow-density relation dynamically. The new modelling approach was tested based on the real traffic situations in various homogeneous motorway sections and a motorway section with ramps and gave encouraging simulation results. This work is composed of two parts: first the analysis of traffic flow characteristics and second the development of a new online traffic flow model applying these characteristics. For homogeneous motorway sections traffic flow is classified into six different traffic states with different characteristics. Delimitation criteria were developed to separate these states. The hysteresis phenomena were analysed during the transitions between these traffic states. The traffic states and the transitions are represented on a states diagram with the flow axis and the density axis. For motorway sections with ramps the complicated traffic flow is simplified and classified into three traffic states depending on the propagation of congestion. The traffic states are represented on a phase diagram with the upstream demand axis and the interaction strength axis which was defined in this research. The states diagram and the phase diagram provide a basis for the development of the dynamic flow-density relation. The first-order hydrodynamic traffic flow model was programmed according to the cell-transmission scheme extended by the modification of flow dependent sending/receiving functions, the classification of cells and the determination strategy for the flow-density relation in the cells. The unreasonable results of macroscopic traffic flow models, which may occur in the first and last cells in certain conditions are alleviated by applying buffer cells between the traffic data and the model. The sending/receiving functions of the cells are determined dynamically based on the classification of the

  15. Road traffic flow and impact on environment in Hyderabad city

    International Nuclear Information System (INIS)

    Memon, Zaheer-ud-Din; Ansari, A.K.; Memon, S.A.

    2000-01-01

    In Hyderabad city due to dramatic increase in traffic intensity on the roads, traffic flow have been much beyond the comfortable limits. High values of traffic flow density have been recorded on Court Road (34.05%), Tilak Road (19.87%), Risala Road (22.91%) and Cafe George (23.14%) of Hyderabad city. Above 80% people are found to be annoyed due to traffic congestion, noise and smoke resulting in health ailments. Slow Moving Vehicles (SMVs) comprising of animal and hand drawn vehicles (rehras) cause serious disruption in the traffic stream on city roads, which are ultimately causing traffic-jam condition resulting a serious impact on environment. No definite parking places exist for public vehicles because of encroachment on roads. Proper foot paths are not available for pedestrian, which results in increase in accidents. (author)

  16. Congestive Heart Failure and Central Sleep Apnea.

    Science.gov (United States)

    Sands, Scott A; Owens, Robert L

    2016-03-01

    Congestive heart failure (CHF) is among the most common causes of admission to hospitals in the United States, especially in those over age 65. Few data exist regarding the prevalence CHF of Cheyne-Stokes respiration (CSR) owing to congestive heart failure in the intensive care unit (ICU). Nevertheless, CSR is expected to be highly prevalent among those with CHF. Treatment should focus on the underlying mechanisms by which CHF increases loop gain and promotes unstable breathing. Few data are available to determine prevalence of CSR in the ICU, or how CSR might affect clinical management and weaning from mechanical ventilation. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Mobile Phone Based RIMS for Traffic Control a Case Study of Tanzania

    OpenAIRE

    Angela-Aida Karugila Runyoro; Jesuk Ko

    2015-01-01

    Vehicles saturation in transportation infrastructure causes traffic congestion, accidents, transportation delays and environment pollution. This problem can be resolved with proper management of traffic flow. Existing traffic management systems are challenged on capturing and processing real-time road data from wide area road networks. The main purpose of this study is to address the gap by implementing a mobile phone based Road Information Management System. The proposed...

  18. Decentralized Traffic Management: A Synchronization-Based Intersection Control --- Extended Version

    OpenAIRE

    Tlig , Mohamed; Buffet , Olivier; Simonin , Olivier

    2014-01-01

    Controlling the vehicle traffic in large networks remains an important challenge in urban environments and transportation systems. Autonomous vehicles are today considered as a promising approach to deal with traffic control. In this paper, we propose a synchronization-based intersection control mechanism to allow the autonomous vehicle-agents to cross without stopping, i.e., in order to avoid congestions (delays) and energy loss. We decentralize the problem by managing the traffic of each in...

  19. Remotely Accessed Vehicle Traffic Management System

    Science.gov (United States)

    Al-Alawi, Raida

    2010-06-01

    The ever increasing number of vehicles in most metropolitan cities around the world and the limitation in altering the transportation infrastructure, led to serious traffic congestion and an increase in the travelling time. In this work we exploit the emergence of novel technologies such as the internet, to design an intelligent Traffic Management System (TMS) that can remotely monitor and control a network of traffic light controllers located at different sites. The system is based on utilizing Embedded Web Servers (EWS) technology to design a web-based TMS. The EWS located at each intersection uses IP technology for communicating remotely with a Central Traffic Management Unit (CTMU) located at the traffic department authority. Friendly GUI software installed at the CTMU will be able to monitor the sequence of operation of the traffic lights and the presence of traffic at each intersection as well as remotely controlling the operation of the signals. The system has been validated by constructing a prototype that resembles the real application.

  20. Lane Changing Control to Reduce Traffic Load Effect on Long-Span Bridges

    OpenAIRE

    Caprani, Colin C; Enright, Bernard; Carey, Colm

    2012-01-01

    Long span bridges are critical parts of a nation’s infrastructure network and congested traffic loading is the governing form of traffic loading. Groups of trucks travelling in conveys are created when fast-er moving vehicles, such as cars, change lane. In this research the authors investigate how the control of these lane-changing events can help reduce the traffic load effects on long span bridges. Real traffic data is used to simulate a traffic stream on a virtual road and bridge using a m...

  1. An intelligent vehicular traffic signal control system with state flow chart design and fpga prototyping

    International Nuclear Information System (INIS)

    Solangi, U.S.; Memon, T.D.; Noonari, A.S.; Ansari, O.A.

    2017-01-01

    The problem of vehicular traffic congestion is a persistent constraint in the socio-economic development of Pakistan. This paper presents design and implementation of an intelligent traffic controller based on FPGA (Field Programmable Gate Array) to provide an efficient traffic management by optimizing functioning of traffic lights which will result in minimizing traffic congestion at intersections. The existent Traffic Signal system in Pakistan is fixed-time based and offers only Open Loop method for Traffic Control. The Intelligent Traffic Controller presented here uses feedback sensors to read the Traffic density present at a four way intersection to provide an efficient alternative for better supervisory Control of Traffic flow. The traffic density based control logic has been developed in a State Flow Chart for improved visualization of State Machine based operation, and implemented as a Subsystem in Simulink and transferred into VHDL (Hardware Description Language) code using HDL Coder for reducing development time and time to market, which are essential to capitalize Embedded Systems Market. The VHDL code is synthesized with Altera QUARTUS, simulated timing waveform is obtained to verify correctness of the algorithm for different Traffic Scenarios. For implementation purpose estimations were obtained for Cyclone-III and Stratix-III. (author)

  2. An Intelligent Vehicular Traffic Signal Control System with State Flow Chart Design and FPGA Prototyping

    Directory of Open Access Journals (Sweden)

    UMAIR SAEEDSOLANGI

    2017-04-01

    Full Text Available The problem of vehicular traffic congestion is a persistent constraint in the socio-economic development of Pakistan. This paper presents design and implementation of an intelligent traffic controller based on FPGA (Field Programmable Gate Array to provide an efficient traffic management by optimizing functioning of traffic lights which will result in minimizing traffic congestion at intersections. The existent Traffic Signal system in Pakistan is fixed-time based and offers only Open Loop method for Traffic Control. The Intelligent Traffic Controller presented here uses feedback sensors to read the Traffic density present at a four way intersection to provide an efficient alternative for better supervisory Control of Traffic flow. The traffic density based control logic has been developed in a State Flow Chart for improved visualization of State Machine based operation, and implemented as a Subsystem in Simulink and transferred into VHDL (Hardware Description Language code using HDL Coder for reducing development time and time to market, which are essential to capitalize Embedded Systems Market. The VHDL code is synthesized with Altera QUARTUS, simulated timing waveform is obtained to verify correctness of the algorithm for different Traffic Scenarios. For implementation purpose estimations were obtained for Cyclone-III and Stratix-III.

  3. ALGORITHMS FOR TRAFFIC MANAGEMENT IN THE INTELLIGENT TRANSPORT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available Traffic jams interfere with the drivers and cost billions of dollars per year and lead to a substantial increase in fuel consumption. In order to avoid such problems the paper describes the algorithms for traffic management in intelligent transportation system, which collects traffic information in real time and is able to detect and manage congestion on the basis of this information. The results show that the proposed algorithms reduce the average travel time, emissions and fuel consumption. In particular, travel time has decreased by about 23%, the average fuel consumption of 9%, and the average emission of 10%.

  4. Battling gridlock : congestion fees are working in Europe and Asia, but its questionable if they will succeed in car-crazy North America

    Energy Technology Data Exchange (ETDEWEB)

    Carnevale, R. [Colleges Integrating Immigrants to Employment, Toronto, ON (Canada); Crawford, E.A. [York Univ., Toronto, ON (Canada). Faculty of Environmental Studies

    2008-07-01

    This article described different traffic congestion schemes that cities around the world have adopted to ease traffic grid-lock. Congestion fees that discourage road use involve assigning a price to a road based on the demand for using that road. A weekday congestion fee which was imposed on drivers in the city of London in 2003 resulted in a 30 per cent drop in vehicular traffic in the city centre. The pricing structure was independent of vehicle type, distance travelled or time of day. The successful scheme is credited with an increase in cycling and public transit ridership as well as a decrease in accidents and air pollution without hindering business within the congestion zone. However, the effectiveness of congestion fees in North America is questionable. Although San Diego's high-occupancy toll lanes have helped reduce congestion and pollution because the revenue raised is invested in public transportation, objections have been raised regarding plans to implement congestion fees in San Francisco and New York city centres because doing so would prevent those with low incomes from driving in the city. London has responded to such challenges by putting all net revenues derived from the fees back into public transportation. Similar measures were taken in Stockholm, Sweden where massive improvements were made to its transit system prior to introducing congestion fees to avert criticism. In order for congestion fees to be effective and gain public approval, there should be clear objectives that include demand management, good transportation alternatives, revenues that go to public transit and a simple pricing system that uses proven technology. The cumulative annual cost of congestion in 9 urban centres in Canada ranged from $2.3 billion to $3.7 billion in 2002 according to Transport Canada. Analysts have cautioned that congestion schemes would be difficult to duplicate in North American cities that are highly dependent on automobiles. However, the authors

  5. Battling gridlock : congestion fees are working in Europe and Asia, but its questionable if they will succeed in car-crazy North America

    International Nuclear Information System (INIS)

    Carnevale, R.; Crawford, E.A.

    2008-01-01

    This article described different traffic congestion schemes that cities around the world have adopted to ease traffic grid-lock. Congestion fees that discourage road use involve assigning a price to a road based on the demand for using that road. A weekday congestion fee which was imposed on drivers in the city of London in 2003 resulted in a 30 per cent drop in vehicular traffic in the city centre. The pricing structure was independent of vehicle type, distance travelled or time of day. The successful scheme is credited with an increase in cycling and public transit ridership as well as a decrease in accidents and air pollution without hindering business within the congestion zone. However, the effectiveness of congestion fees in North America is questionable. Although San Diego's high-occupancy toll lanes have helped reduce congestion and pollution because the revenue raised is invested in public transportation, objections have been raised regarding plans to implement congestion fees in San Francisco and New York city centres because doing so would prevent those with low incomes from driving in the city. London has responded to such challenges by putting all net revenues derived from the fees back into public transportation. Similar measures were taken in Stockholm, Sweden where massive improvements were made to its transit system prior to introducing congestion fees to avert criticism. In order for congestion fees to be effective and gain public approval, there should be clear objectives that include demand management, good transportation alternatives, revenues that go to public transit and a simple pricing system that uses proven technology. The cumulative annual cost of congestion in 9 urban centres in Canada ranged from $2.3 billion to $3.7 billion in 2002 according to Transport Canada. Analysts have cautioned that congestion schemes would be difficult to duplicate in North American cities that are highly dependent on automobiles. However, the authors

  6. Auctions for Congestion Management in Distribution Grids

    NARCIS (Netherlands)

    Philipsen, R.M.; de Weerdt, M.M.; de Vries, L.J.

    2016-01-01

    Large controllable loads, such as electric vehicles, are increasingly penetrating electricity distribution feeders. To avoid local congestion, their consumption behaviour must be steered, for which a real-time price propagated down from the transmission system does not suffice, as it does not

  7. Mean Field Type Control with Congestion

    Energy Technology Data Exchange (ETDEWEB)

    Achdou, Yves, E-mail: achdou@ljll.univ-paris-diderot.fr; Laurière, Mathieu [Univ. Paris Diderot, Sorbonne Paris Cité, Laboratoire Jacques-Louis Lions, UMR 7598, UPMC, CNRS (France)

    2016-06-15

    We analyze some systems of partial differential equations arising in the theory of mean field type control with congestion effects. We look for weak solutions. Our main result is the existence and uniqueness of suitably defined weak solutions, which are characterized as the optima of two optimal control problems in duality.

  8. Update in cardiomyopathies and congestive heart failure

    Directory of Open Access Journals (Sweden)

    The Heart Hospital, London, UK and Monaldi Hospital, Naples, Italy

    2012-05-01

    Full Text Available This abstract book contains four reports and all abstracts presented to the Joint Meeting: Update in cardiomyopathies and congestive heart failure, 22-23 September 2011 - Naples, Italy, endorsed by the Working Group on Myocardial and Pericardial Diseases (WG 21 of the European Society of Cardiology (ESC.

  9. SOME EMPIRICAL RELATIONS BETWEEN TRAVEL SPEED, TRAFFIC VOLUME AND TRAFFIC COMPOSITION IN URBAN ARTERIALS

    Directory of Open Access Journals (Sweden)

    Eleni I. VLAHOGIANNI, Ph.D.

    2007-01-01

    Full Text Available The effects of traffic mix (the percentage of cars, trucks, buses and so on are of particular interest in the speed-volume relationship in urban signalized arterials under various geometric and control characteristics. The paper presents some empirical observations on the relation between travel speed, traffic volume and traffic composition in urban signalized arterials. A methodology based on emerging self-organizing structures of neural networks to identify regions in the speed-volume relationship with respect to traffic composition and Bayesian networks to evaluate the effect of different types of motorized vehicles on prevailing traffic conditions is proposed. Results based on data from a large urban network indicate that the variability in traffic conditions can be described by eight regions in speed-volume relationship with respect to traffic composition. Further evaluation of the effect of motorized vehicles in each region separately indicates that the effect of traffic composition decreases with the onset of congestion. Moreover, taxis and motorcycles are the primary affecting parameter of the form of the speed-volume relationship in urban arterials.

  10. Rate-based congestion control in networks with smart links, revision. B.S. Thesis - May 1988

    Science.gov (United States)

    Heybey, Andrew Tyrrell

    1990-01-01

    The author uses a network simulator to explore rate-based congestion control in networks with smart links that can feed back information to tell senders to adjust their transmission rates. This method differs in a very important way from congestion control in which a congested network component just drops packets - the most commonly used method. It is clearly advantageous for the links in the network to communicate with the end users about the network capacity, rather than the users unilaterally picking a transmission rate. The components in the middle of the network, not the end users, have information about the capacity and traffic in the network. The author experiments with three different algorithms for calculating the control rate to feed back to the users. All of the algorithms exhibit problems in the form of large queues when simulated with a configuration modeling the dynamics of a packet-voice system. However, the problems are not with the algorithms themselves, but with the fact that feedback takes time. If the network steady-state utilization is low enough that it can absorb transients in the traffic through it, then the large queues disappear. If the users are modified to start sending slowly, to allow the network to adapt to a new flow without causing congestion, a greater portion of the network's bandwidth can be used.

  11. Statewide GIS mapping of recurring congestion corridors : final report.

    Science.gov (United States)

    2009-07-01

    Recurring congestion occurs when travel demand reaches or exceeds the available roadway : capacity. This project developed an interactive geographic information system (GIS) map of the : recurring congestion corridors (labeled herein as hotspots) in ...

  12. Congestion control for vehicular delay tolerant network routing protocols

    OpenAIRE

    Oham, Chuka Finbars

    2014-01-01

    The Vehicular Delay Tolerant Network (VDTN) is a special and challenging type of the Delay Tolerant Network because of its high mobility, frequent disconnections and nodal congestion features. These challenging features make it prone to congestion which leads to a considerable amount of message drops in the network. To minimize the impact of congestion in the network, we designed and implemented the Congestion Aware Spray and Wait (CASaW) routing protocol. We varied the buffer sizes of the no...

  13. Modeling Road Traffic Using Service Center

    Directory of Open Access Journals (Sweden)

    HARAGOS, I.-M.

    2012-05-01

    Full Text Available Transport systems have an essential role in modern society because they facilitate access to natural resources and they stimulate trade. Current studies aimed at improving transport networks by developing new methods for optimization. Because of the increase in the global number of cars, one of the most common problems facing the transport network is congestion. By creating traffic models and simulate them, we can avoid this problem and find appropriate solutions. In this paper we propose a new method for modeling traffic. This method considers road intersections as being service centers. A service center represents a set consisting of a queue followed by one or multiple servers. This model was used to simulate real situations in an urban traffic area. Based on this simulation, we have successfully determined the optimal functioning and we have computed the performance measures.

  14. Fuzzy Logic Based Autonomous Traffic Control System

    Directory of Open Access Journals (Sweden)

    Muhammad ABBAS

    2012-01-01

    Full Text Available The aim of this paper is to design and implement fuzzy logic based traffic light Control system to solve the traffic congestion issues. In this system four input parameters: Arrival, Queue, Pedestrian and Emergency Vehicle and two output parameters: Extension in Green and Pedestrian Signals are used. Using Fuzzy Rule Base, the system extends or terminates the Green Signal according to the Traffic situation at the junction. On the presence of emergency vehicle, the system decides which signal(s should be red and how much an extension should be given to Green Signal for Emergency Vehicle. The system also monitors the density of people and makes decisions accordingly. In order to verify the proposed design algorithm MATLAB simulation is adopted and results obtained show concurrency to the calculated values according to the Mamdani Model of the Fuzzy Control System.

  15. Integrated Traffic Flow Management Decision Making

    Science.gov (United States)

    Grabbe, Shon R.; Sridhar, Banavar; Mukherjee, Avijit

    2009-01-01

    A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

  16. Comparative Application of Radial Basis Function and Multilayer Perceptron Neural Networks to Predict Traffic Noise Pollution in Tehran Roads

    Directory of Open Access Journals (Sweden)

    Ali Mansourkhaki

    2018-01-01

    Full Text Available Noise pollution is a level of environmental noise which is considered as a disturbing and annoying phenomenon for human and wildlife. It is one of the environmental problems which has not been considered as harmful as the air and water pollution. Compared with other pollutants, the attempts to control noise pollution have largely been unsuccessful due to the inadequate knowledge of its effectson humans, as well as the lack of clear standards in previous years. However, with an increase of traveling vehicles, the adverse impact of increasing noise pollution on human health is progressively emerging. Hence, investigators all around the world are seeking to findnew approaches for predicting, estimating and controlling this problem and various models have been proposed. Recently, developing learning algorithms such as neural network has led to novel solutions for this challenge. These algorithms provide intelligent performance based on the situations and input data, enabling to obtain the best result for predicting noise level. In this study, two types of neural networks – multilayer perceptron and radial basis function – were developed for predicting equivalent continuous sound level (LA eq by measuring the traffivolume, average speed and percentage of heavy vehicles in some roads in west and northwest of Tehran. Then, their prediction results were compared based on the coefficienof determination (R 2 and the Mean Squared Error (MSE. Although both networks are of high accuracy in prediction of noise level, multilayer perceptron neural network based on selected criteria had a better performance.

  17. Contemporary approaches to congestion pricing : lessons learned from the national evaluation of congestion pricing strategies at six sites.

    Science.gov (United States)

    2015-08-01

    This document represents the final report of the national evaluation of congestion reduction strategies at six sites that received federal funding under the Urban Partnership Agreement (UPA) and Congestion Reduction Demonstration (CRD) programs. The ...

  18. Auctionable fixed transmission rights for congestion management

    Science.gov (United States)

    Alomoush, Muwaffaq Irsheid

    Electric power deregulation has proposed a major change to the regulated utility monopoly. The change manifests the main part of engineers' efforts to reshape three components of today's regulated monopoly: generation, distribution and transmission. In this open access deregulated power market, transmission network plays a major role, and transmission congestion is a major problem that requires further consideration especially when inter-zonal/intra-zonal scheme is implemented. Declaring that engineering studies and experience are the criteria to define zonal boundaries or defining a zone based on the fact that a zone is a densely interconnected area (lake) and paths connecting these densely interconnected areas are inter-zonal lines will render insufficient and fuzzy definitions. Moreover, a congestion problem formulation should take into consideration interactions between intra-zonal and inter-zonal flows and their effects on power systems. In this thesis, we introduce a procedure for minimizing the number of adjustments of preferred schedules to alleviate congestion and apply control schemes to minimize interactions between zones. In addition, we give the zone definition a certain criterion based on the Locational Marginal Price (LMP). This concept will be used to define congestion zonal boundaries and to decide whether any zone should be merged with another zone or split into new zones. The thesis presents a unified scheme that combines zonal and FTR schemes to manage congestion. This combined scheme is utilized with LMPs to define zonal boundaries more appropriately. The presented scheme gains the best features of the FTR scheme, which are providing financial certainty, maximizing the efficient use of the system and making users pay for the actual use of congested paths. LMPs may give an indication of the impact of wheeling transactions, and calculations of and comparisons of LMPs with and without wheeling transactions should be adequate criteria to approve

  19. Planning and managing rural recreational traffic flows: why the future can’t be more like the past

    NARCIS (Netherlands)

    Jaarsma, C.F.; Vries, de J.R.; Beunen, R.

    2009-01-01

    The increasing popularity of rural tourism can cause traffic related problems at certain areas. Traffic congestion and parking problems are likely to occur as the infrastructure at these countryside destinations is seldom capable of dealing with the growing number of cars. Values which make the

  20. An Analysis of Vehicular Traffic Flow Using Langevin Equation

    Directory of Open Access Journals (Sweden)

    Çağlar Koşun

    2015-08-01

    Full Text Available Traffic flow data are stochastic in nature, and an abundance of literature exists thereof. One way to express stochastic data is the Langevin equation. Langevin equation consists of two parts. The first part is known as the deterministic drift term, the other as the stochastic diffusion term. Langevin equation does not only help derive the deterministic and random terms of the selected portion of the city of Istanbul traffic empirically, but also sheds light on the underlying dynamics of the flow. Drift diagrams have shown that slow lane tends to get congested faster when vehicle speeds attain a value of 25 km/h, and it is 20 km/h for the fast lane. Three or four distinct regimes may be discriminated again from the drift diagrams; congested, intermediate, and free-flow regimes. At places, even the intermediate regime may be divided in two, often with readiness to congestion. This has revealed the fact that for the selected portion of the highway, there are two main states of flow, namely, congestion and free-flow, with an intermediate state where the noise-driven traffic flow forces the flow into either of the distinct regimes.

  1. CONTROLLING TRAFFIC FLOW IN MULTILANE-ISOLATED INTERSECTION USING ANFIS APPROACH TECHNIQUES

    Directory of Open Access Journals (Sweden)

    G. R. LAI

    2015-08-01

    Full Text Available Many controllers have applied the Adaptive Neural-Fuzzy Inference System (ANFIS concept for optimizing the controller performance. However, there are less traffic signal controllers developed using the ANFIS concept. ANFIS traffic signal controller with its fuzzy rule base and its ability to learn from a set of sample data could improve the performance of Existing traffic signal controlling system to reduce traffic congestions at most of the busy traffic intersections in city such as Kuala Lumpur, Malaysia. The aim of this research is to develop an ANFIS traffic signals controller for multilane-isolated four approaches intersections in order to ease traffic congestions at traffic intersections. The new concept to generate sample data for ANFIS training is introduced in this research. The sample data is generated based on fuzzy rules and can be analysed using tree diagram. This controller is simulated on multilane-isolated traffic intersection model developed using M/M/1 queuing theory and its performance in terms of average waiting time, queue length and delay time are compared with traditional controllers and fuzzy controller. Simulation result shows that the average waiting time, queue length, and delay time of ANFIS traffic signal controller are the lowest as compared to the other three controllers. In conclusion, the efficiency and performance of ANFIS controller are much better than that of fuzzy and traditional controllers in different traffic volumes.

  2. Variables associated with lung congestion as assessed by chest ultrasound in diabetics undergoing hemodialysis

    Directory of Open Access Journals (Sweden)

    Paulo Roberto Santos

    Full Text Available Abstract Introduction: Ultrasound is an emerging method for assessing lung congestion but is still seldom used. Lung congestion is an important risk of cardiac events and death in end-stage renal disease (ESRD patients on hemodialysis (HD. Objective: We investigated possible variables associated with lung congestion among diabetics with ESRD on HD, using chest ultrasound to detect extracellular lung water. Methods: We studied 73 patients with diabetes as the primary cause of ESRD, undergoing regular HD. Lung congestion was assessed by counting the number of B lines detected by chest ultrasound. Hydration status was assessed by bioimpedance analysis and cardiac function by echocardiography. The collapse index of the inferior vena cava (IVC was measured by ultrasonography. All patients were classified according to NYHA score. Correlations of the number of B lines with continuous variables and comparisons regarding the number of B lines according to categorical variables were performed. Multivariate linear regression was used to test the variables as independent predictors of the number of B lines. Results: None of the variables related to hydration status and cardiac function were associated with the number of B lines. In the multivariate analysis, only the IVC collapse index (b = 45.038; p < 0.001 and NYHA classes (b = 13.995; p = 0.006 were independent predictors of the number of B lines. Conclusion: Clinical evaluation based on NYHA score and measurement of the collapsed IVC index were found to be more reliable than bioimpedance analysis to predict lung congestion.

  3. Competitive Traffic Assignment in Road Networks

    Directory of Open Access Journals (Sweden)

    Krylatov Alexander Y.

    2016-09-01

    Full Text Available Recently in-vehicle route guidance and information systems are rapidly developing. Such systems are expected to reduce congestion in an urban traffic area. This social benefit is believed to be reached by imposing the route choices on the network users that lead to the system optimum traffic assignment. However, guidance service could be offered by different competitive business companies. Then route choices of different mutually independent groups of users may reject traffic assignment from the system optimum state. In this paper, a game theoretic approach is shown to be very efficient to formalize competitive traffic assignment problem with various groups of users in the form of non-cooperative network game with the Nash equilibrium search. The relationships between the Wardrop’s system optimum associated with the traffic assignment problem and the Nash equilibrium associated with the competitive traffic assignment problem are investigated. Moreover, some related aspects of the Nash equilibrium and the Wardrop’s user equilibrium assignments are also discussed.

  4. Traffic Perturbation

    CERN Multimedia

    C. Colloca TS/FM

    2004-01-01

    TS/FM group informs you that, for the progress of the works at the Prévessin site entrance, some perturbation of the traffic may occur during the week between the 14th and 18th of June for a short duration. Access will be assured at any time. For more information, please contact 160239. C. Colloca TS/FM

  5. Assessment of traffic noise levels in urban areas using different soft computing techniques.

    Science.gov (United States)

    Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D

    2016-10-01

    Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.

  6. Traffic networks as information systems a viability approach

    CERN Document Server

    Aubin, Jean-Pierre

    2017-01-01

    This authored monograph covers a viability to approach to traffic management by advising to vehicles circulated on the network the velocity they should follow for satisfying global traffic conditions;. It presents an investigation of three structural innovations: The objective is to broadcast at each instant and at each position the advised celerity to vehicles, which could be read by auxiliary speedometers or used by cruise control devices. Namely, 1. Construct regulation feedback providing at each time and position advised velocities (celerities) for minimizing congestion or other requirements. 2. Taking into account traffic constraints of different type, the first one being to remain on the roads, to stop at junctions, etc. 3. Use information provided by the probe vehicles equipped with GPS to the traffic regulator; 4. Use other global traffic measures of vehicles provided by different types of sensors; These results are based on convex analysis, intertemporal optimization and viability theory as mathemati...

  7. A cellular automata model for traffic flow based on kinetics theory, vehicles capabilities and driver reactions

    Science.gov (United States)

    Guzmán, H. A.; Lárraga, M. E.; Alvarez-Icaza, L.; Carvajal, J.

    2018-02-01

    In this paper, a reliable cellular automata model oriented to faithfully reproduce deceleration and acceleration according to realistic reactions of drivers, when vehicles with different deceleration capabilities are considered is presented. The model focuses on describing complex traffic phenomena by coding in its rules the basic mechanisms of drivers behavior, vehicles capabilities and kinetics, while preserving simplicity. In particular, vehiclés kinetics is based on uniform accelerated motion, rather than in impulsive accelerated motion as in most existing CA models. Thus, the proposed model calculates in an analytic way three safe preserving distances to determine the best action a follower vehicle can take under a worst case scenario. Besides, the prediction analysis guarantees that under the proper assumptions, collision between vehicles may not happen at any future time. Simulations results indicate that all interactions of heterogeneous vehicles (i.e., car-truck, truck-car, car-car and truck-truck) are properly reproduced by the model. In addition, the model overcomes one of the major limitations of CA models for traffic modeling: the inability to perform smooth approach to slower or stopped vehicles. Moreover, the model is also capable of reproducing most empirical findings including the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Like most CA models, integer values are used to make the model run faster, which makes the proposed model suitable for real time traffic simulation of large networks.

  8. Effective use of congestion in complex networks

    Science.gov (United States)

    Echagüe, Juan; Cholvi, Vicent; Kowalski, Dariusz R.

    2018-03-01

    In this paper, we introduce a congestion-aware routing protocol that selects the paths according to the congestion of nodes in the network. The aim is twofold: on one hand, and in order to prevent the networks from collapsing, it provides a good tolerance to nodes' overloads; on the other hand, and in order to guarantee efficient communication, it also incentivize the routes to follow short paths. We analyze the performance of our proposed routing strategy by means of a series of experiments carried out by using simulations. We show that it provides a tolerance to collapse close to the optimal value. Furthermore, the average length of the paths behaves optimally up to the certain value of packet generation rate ρ and it grows in a linear fashion with the increase of ρ.

  9. Can complexity decrease in congestive heart failure?

    Science.gov (United States)

    Mukherjee, Sayan; Palit, Sanjay Kumar; Banerjee, Santo; Ariffin, M. R. K.; Rondoni, Lamberto; Bhattacharya, D. K.

    2015-12-01

    The complexity of a signal can be measured by the Recurrence period density entropy (RPDE) from the reconstructed phase space. We have chosen a window based RPDE method for the classification of signals, as RPDE is an average entropic measure of the whole phase space. We have observed the changes in the complexity in cardiac signals of normal healthy person (NHP) and congestive heart failure patients (CHFP). The results show that the cardiac dynamics of a healthy subject is more complex and random compare to the same for a heart failure patient, whose dynamics is more deterministic. We have constructed a general threshold to distinguish the border line between a healthy and a congestive heart failure dynamics. The results may be useful for wide range for physiological and biomedical analysis.

  10. A Comparison of Traffic Operations among Beijing and Several International Megacities

    Directory of Open Access Journals (Sweden)

    Yuanzhou Yang

    2011-12-01

    Full Text Available High-Efficient traffic system is very important for economy and society of cities. Previous studies on the traffic comparison mostly took a city as a whole, but ignored the differences among areas inside the city. But in fact, the traffic congestion in different areas with a city is mostly different. Taking typical mega cities like Beijing, London, New York, and Tokyo as objects, this paper makes cross-comparison in the traffic operation and performance based on intelligent algorithm. Transportation infrastructure and travel demand data are discussed and unbalanced transport system is found in Beijing because of the conflict between too much traffic demand and defect road networks. From the aspects of traffic load, operational efficiency and safety, indexes including traffic v/c ratio, average vehicle speed and accident rate are selected to assess the performance of road traffic. It is concluded that road networks of Beijing have the worst performance compared with other three mega-cities and the primary reasons are the inappropriate distribution of utilization rate among the freeways, arterials, and local streets, and the high traffic concentration in urban area. So, several measures are recommended to improve the operation efficiency of traffic in Beijing especially for the green intelligent traffic system. Keywords: Traffic operation; Operational efficiency; Intelligent traffic system (ITS; Traffic load; traffic safety; Intelligent algorithm.

  11. Pulmonary Vascular Congestion: A Mechanism for Distal Lung Unit Dysfunction in Obesity.

    Science.gov (United States)

    Oppenheimer, Beno W; Berger, Kenneth I; Ali, Saleem; Segal, Leopoldo N; Donnino, Robert; Katz, Stuart; Parikh, Manish; Goldring, Roberta M

    2016-01-01

    Obesity is characterized by increased systemic and pulmonary blood volumes (pulmonary vascular congestion). Concomitant abnormal alveolar membrane diffusion suggests subclinical interstitial edema. In this setting, functional abnormalities should encompass the entire distal lung including the airways. We hypothesize that in obesity: 1) pulmonary vascular congestion will affect the distal lung unit with concordant alveolar membrane and distal airway abnormalities; and 2) the degree of pulmonary congestion and membrane dysfunction will relate to the cardiac response. 54 non-smoking obese subjects underwent spirometry, impulse oscillometry (IOS), diffusion capacity (DLCO) with partition into membrane diffusion (DM) and capillary blood volume (VC), and cardiac MRI (n = 24). Alveolar-capillary membrane efficiency was assessed by calculation of DM/VC. Mean age was 45±12 years; mean BMI was 44.8±7 kg/m2. Vital capacity was 88±13% predicted with reduction in functional residual capacity (58±12% predicted). Despite normal DLCO (98±18% predicted), VC was elevated (135±31% predicted) while DM averaged 94±22% predicted. DM/VC varied from 0.4 to 1.4 with high values reflecting recruitment of alveolar membrane and low values indicating alveolar membrane dysfunction. The most abnormal IOS (R5 and X5) occurred in subjects with lowest DM/VC (r2 = 0.31, ppulmonary vascular congestion and failure to achieve the high output state of obesity. Pulmonary vascular congestion and consequent fluid transudation and/or alterations in the structure of the alveolar capillary membrane may be considered often unrecognized causes of airway dysfunction in obesity.

  12. Travel Times, Congestion Levels, and Delays at Intersections Calculated on the Basis of Floating Car Data

    DEFF Research Database (Denmark)

    Lahrmann, Harry; Torp, Kristian

    2010-01-01

    Traditionally, the mapping of flow rate in a road network has been based on spot and intersection counting. Using these counting techniques, detailed information about traffic at a few well-picked spots in the road network is obtained. However, these techniques give no exact information about tra...... of the cars. This paper presents a method to determine travel time, congestion levels and delays using GPS data from moving vehicles – the so-called floating car data....... traffic only a few meters away from the measuring spots. The situation is totally the opposite when it comes to log data from GPS receivers in cars. Here detailed information about individual cars in the entire road network is obtained. However, the GPS data is only available from a small subset...

  13. Congestion Pricing for Aircraft Pushback Slot Allocation.

    Science.gov (United States)

    Liu, Lihua; Zhang, Yaping; Liu, Lan; Xing, Zhiwei

    2017-01-01

    In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the "external cost of surface congestion" is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm.

  14. Congestion Pricing for Aircraft Pushback Slot Allocation.

    Directory of Open Access Journals (Sweden)

    Lihua Liu

    Full Text Available In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the "external cost of surface congestion" is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm.

  15. Intelligent Traffic Information System a Real-Time Traffic Information System on the Shiraz Bypass

    Directory of Open Access Journals (Sweden)

    Sodagaran Amir

    2016-01-01

    Full Text Available Real-time traffic information system is an Intelligent Transportation System (ITS that allows commuters to make their traveling plan better. In this regard, an intelligent and real-time traffic information system was developed based on the video detection and an image processing algorithm was applied to measure traffic-flow according to the average speed of vehicles. Then, traffic status of each pass way is broadcasted to the electronic boards installed on all decision making entrance / exit. Different levels of congestion related to the routes ahead are shown on the boards with different colors in order to assist commuters. This system was implemented on the Shiraz Dry River’s bypasses which account as vital routes to moderate traffic of city center. Experimental results are promising due to the proximity of determined traffic status by the system compared to the detection done by traffic experts. Average speed improvement is another result of using this system. This intelligent system developed and implemented in Shiraz city for the first time in Iran.s.

  16. Traffic dynamics on coupled spatial networks

    International Nuclear Information System (INIS)

    Du, Wen-Bo; Zhou, Xing-Lian; Chen, Zhen; Cai, Kai-Quan; Cao, Xian-Bin

    2014-01-01

    With the rapid development of modern traffic, various means of transportation systems make it more convenient and diversified for passengers to travel out. In this paper, we establish a two-layered spatial network model where the low-speed lower layer is a regular lattice and the high-speed upper layer is a scale-free network embedded in the lattice. Passengers will travel along the path with the minimal travel time, and they can transfer from one layer to the other, which will induce extra transfer cost. We extensively investigate the traffic process on these coupled spatial networks and focus on the effect of the parameter α, the speed ratio between two networks. It is found that, as α grows, the network capacity of the coupled networks increases in the early stage and then decreases, indicating that cooperation between the coupled networks will induce the highest network capacity at an optimal α. We then provide an explanation for this non-monotonous dependence from a micro-scope point of view. The travel time reliability is also examined. Both in free-flow state and congestion state, the travel time is linearly related to the Euclidean distance. However, the variance of travel time in the congestion state is remarkably larger than that in the free-flow state, namely, people have to set aside more redundant time in an unreliable traffic system

  17. Bayesian Data Assimilation for Improved Modeling of Road Traffic

    NARCIS (Netherlands)

    Van Hinsbergen, C.P.Y.

    2010-01-01

    This thesis deals with the optimal use of existing models that predict certain phenomena of the road traffic system. Such models are extensively used in Advanced Traffic Information Systems (ATIS), Dynamic Traffic Management (DTM) or Model Predictive Control (MPC) approaches in order to improve the

  18. Simulating and evaluating an adaptive and integrated traffic lights control system for smart city application

    Science.gov (United States)

    Djuana, E.; Rahardjo, K.; Gozali, F.; Tan, S.; Rambung, R.; Adrian, D.

    2018-01-01

    A city could be categorized as a smart city when the information technology has been developed to the point that the administration could sense, understand, and control every resource to serve its people and sustain the development of the city. One of the smart city aspects is transportation and traffic management. This paper presents a research project to design an adaptive traffic lights control system as a part of the smart system for optimizing road utilization and reducing congestion. Research problems presented include: (1) Congestion in one direction toward an intersection due to dynamic traffic condition from time to time during the day, while the timing cycles in traffic lights system are mostly static; (2) No timing synchronization among traffic lights in adjacent intersections that is causing unsteady flows; (3) Difficulties in traffic condition monitoring on the intersection and the lack of facility for remotely controlling traffic lights. In this research, a simulator has been built to model the adaptivity and integration among different traffic lights controllers in adjacent intersections, and a case study consisting of three sets of intersections along Jalan K. H. Hasyim Ashari has been simulated. It can be concluded that timing slots synchronization among traffic lights is crucial for maintaining a steady traffic flow.

  19. Comparative Analysis of Tokyo and Moscow Experience in Addressing the Traffic Jams Problem: A View from Moscow and Tokyo

    OpenAIRE

    Kiichiro Hatoyama

    2011-01-01

    The problem of traffic jams in Moscow turns out to be chronic. The author employs a comparative analysis of the experiences of different countries, especially Russia and Japan, in decreasing traffic congestion, appropriate damage and in solving other transport problems. The article analyzes the objective and subjective reasons for the deterioration of the traffic situation, as well as effective strategies to address them. 

  20. Comparative Analysis of Tokyo and Moscow Experience in Addressing the Traffic Jams Problem: A View from Moscow and Tokyo

    Directory of Open Access Journals (Sweden)

    Kiichiro Hatoyama

    2011-01-01

    Full Text Available The problem of traffic jams in Moscow turns out to be chronic. The author employs a comparative analysis of the experiences of different countries, especially Russia and Japan, in decreasing traffic congestion, appropriate damage and in solving other transport problems. The article analyzes the objective and subjective reasons for the deterioration of the traffic situation, as well as effective strategies to address them. 

  1. Shockwave-Based Automated Vehicle Longitudinal Control Algorithm for Nonrecurrent Congestion Mitigation

    Directory of Open Access Journals (Sweden)

    Liuhui Zhao

    2017-01-01

    Full Text Available A shockwave-based speed harmonization algorithm for the longitudinal movement of automated vehicles is presented in this paper. In the advent of Connected/Automated Vehicle (C/AV environment, the proposed algorithm can be applied to capture instantaneous shockwaves constructed from vehicular speed profiles shared by individual equipped vehicles. With a continuous wavelet transform (CWT method, the algorithm detects abnormal speed drops in real-time and optimizes speed to prevent the shockwave propagating to the upstream traffic. A traffic simulation model is calibrated to evaluate the applicability and efficiency of the proposed algorithm. Based on 100% C/AV market penetration, the simulation results show that the CWT-based algorithm accurately detects abnormal speed drops. With the improved accuracy of abnormal speed drop detection, the simulation results also demonstrate that the congestion can be mitigated by reducing travel time and delay up to approximately 9% and 18%, respectively. It is also found that the shockwave caused by nonrecurrent congestion is quickly dissipated even with low market penetration.

  2. Traffic and related self-driven many-particle systems

    Science.gov (United States)

    Helbing, Dirk

    2001-10-01

    Since the subject of traffic dynamics has captured the interest of physicists, many surprising effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by ``phantom traffic jams'' even though drivers all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction in the volume of traffic cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize into lanes, while similar systems ``freeze by heating''? All of these questions have been answered by applying and extending methods from statistical physics and nonlinear dynamics to self-driven many-particle systems. This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic. These include microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts, such as a general modeling framework for self-driven many-particle systems, including spin systems. While the primary focus is upon vehicle and pedestrian traffic, applications to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are touched upon as well.

  3. Road Environments: Impact of Metals on Human Health in Heavily Congested Cities of Poland.

    Science.gov (United States)

    Adamiec, Ewa

    2017-06-29

    Road dust as a by-product of exhaust and non-exhaust emissions can be a major cause of systemic oxidative stress and multiple disorders. Substantial amounts of road dust are repeatedly resuspended, in particular at traffic lights and junctions where more braking is involved, causing potential threat to pedestrians, especially children. In order to determine the degree of contamination in the heavily traffic-congested cities of Poland, a total of 148 samples of road dust (RD), sludge from storm drains (SL) and roadside soil (RS) were collected. Sixteen metals were analysed using inductively coupled plasma mass spectrometry (ICP-MS), inductively coupled plasma atomic emission spectroscopy (ICP-OES) and atomic absorption spectroscopy (AAS) in all samples. Chemical evaluation followed by Principal Component Analysis (PCA) revealed that road environments have been severely contaminated with traffic-related elements. Concentration of copper in all road-environment samples is even higher, exceeding even up to 15 times its average concentrations established for the surrounding soils. Non-carcinogenic health risk assessment revealed that the hazard index (HI) for children in all road-environment samples exceeds the safe level of 1. Therefore, greater attention should be paid to potential health risks caused by the ingestion of traffic-related particles during outdoor activities.

  4. Urban emissions hotspots: Quantifying vehicle congestion and air pollution using mobile phone GPS data.

    Science.gov (United States)

    Gately, Conor K; Hutyra, Lucy R; Peterson, Scott; Sue Wing, Ian

    2017-10-01

    On-road emissions vary widely on time scales as short as minutes and length scales as short as tens of meters. Detailed data on emissions at these scales are a prerequisite to accurately quantifying ambient pollution concentrations and identifying hotspots of human exposure within urban areas. We construct a highly resolved inventory of hourly fluxes of CO, NO 2 , NO x , PM 2.5 and CO 2 from road vehicles on 280,000 road segments in eastern Massachusetts for the year 2012. Our inventory integrates a large database of hourly vehicle speeds derived from mobile phone and vehicle GPS data with multiple regional datasets of vehicle flows, fleet characteristics, and local meteorology. We quantify the 'excess' emissions from traffic congestion, finding modest congestion enhancement (3-6%) at regional scales, but hundreds of local hotspots with highly elevated annual emissions (up to 75% for individual roadways in key corridors). Congestion-driven reductions in vehicle fuel economy necessitated 'excess' consumption of 113 million gallons of motor fuel, worth ∼ $415M, but this accounted for only 3.5% of the total fuel consumed in Massachusetts, as over 80% of vehicle travel occurs in uncongested conditions. Across our study domain, emissions are highly spatially concentrated, with 70% of pollution originating from only 10% of the roads. The 2011 EPA National Emissions Inventory (NEI) understates our aggregate emissions of NO x , PM 2.5 , and CO 2 by 46%, 38%, and 18%, respectively. However, CO emissions agree within 5% for the two inventories, suggesting that the large biases in NO x and PM 2.5 emissions arise from differences in estimates of diesel vehicle activity. By providing fine-scale information on local emission hotspots and regional emissions patterns, our inventory framework supports targeted traffic interventions, transparent benchmarking, and improvements in overall urban air quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Hemostatic biomarkers in dogs with chronic congestive heart failure

    DEFF Research Database (Denmark)

    Tarnow, Inge; Falk, Torkel; Tidholm, Anna

    2007-01-01

    Background: Chronic congestive heart failure (CHF) in humans is associated with abnormal hemostasis, and abnormalities in hemostatic biomarkers carry a poor prognosis. Alterations in hemostatic pathways can be involved in the pathogenesis of CHF in dogs, and microthrombosis in the myocardium could...... contribute to increased mortality. Hypothesis: That plasma concentration or activity of hemostatic biomarkers is altered in dogs with CHF and that these factors predict mortality. Animals: Thirty-four dogs with CHF caused by either dilated cardiomyopathy (DCM, n = 14) or degenerative valvular disease (CDVD......, n = 20) compared with 23 healthy age-matched control dogs were included in this study. Dogs with CHF were recruited from 2 referral cardiology clinics, and control dogs were owned by friends or colleagues of the investigators. Methods: Clinical examination and echocardiography were performed in all...

  6. Social Optimality of Cordon Area Congestion Pricing in an Monocentric City

    Directory of Open Access Journals (Sweden)

    Harya S Dillon

    2015-04-01

    Full Text Available Abstrak. Kemacetan lalu lintas merupakan epidemi global yang telah melumpuhkan banyak kota. Dari sudut pandang ekonomi mikro, kemacetan dapat dipandang sebagai eksternalitas negatif dimana diperlukan bea Pigovian sebagai solusi atas ekuilibrium yang kurang optimal tersebut. Eksternalitas ini dirasakan dalam bentuk tundaan perjalanan dan pembangunan kota yang rakus lahan. Meskipun teori mengenai ketepatgunaan bea kemacetan (congestion pricing telah mapan sejak akhir 1970-an, penerapan dan implementasi kebijakan tertunda oleh kendala teknologi. Salah satu bentuk implementasi bayaran kemacetan yang sering dijumpai adalah bea lintas-kordon (cordon charging, dimana penglaju yang masuk ke wilayah pusat dibebani sejumlah biaya. Ketepatgunaan dari bea lintas-kordon telah dikaji secara empiris dan juga dengan simulasi numerik, namun penjelasan teoretis belum dilakukan secara tuntas. Penulis mengembangkan model kota monosentris untuk meneliti dampak kebijakan bea lintas-kordon pada kepadatan kota dan permintaan akan lahan kota (equilibrium rent. Bea lintas-kordon akan menaikkan harga lahan di pusat kota dan memperbesar gradien kurva tawaran-sewa (bid-rent curve. Namun yang lebih penting untuk diperhatikan adalah bahwa besaran ini ditentukan oleh parameter kordon. Dengan demikian dapat disimpulkan bahwa daya manfaat kebijakan ini sangat dipengaruhi oleh pilihan parameter kordon yang dibuat perencana.Kata kunci. kemacetan, bea lintas-kordon, kota monosentris, struktur kotaAbstract. Traffic congestion is a global epidemic that at time has put cities to a state of paralysis. From a microeconomics point of view, congestion can be approached as a negative externality that merits a Pigovian tax to correct the suboptimal equilibrium. Externalities manifest in delays and wasteful urbanization. While the efficiency of congestion pricing has been well established since the late 1970s, policy adoption and implementation have been delayed due to technological

  7. Trip-timing decisions with traffic incidents

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Lindsey, Robin

    2013-01-01

    This paper analyzes traffic bottleneck congestion when drivers randomly cause incidents that temporarily block the bottleneck. Drivers have general scheduling preferences for time spent at home and at work. They independently choose morning departure times from home to maximize expected utility...... without knowing whether an incident has occurred. The resulting departure time pattern may be compressed or dispersed according to whether or not the bottleneck is fully utilized throughout the departure period on days without incidents. For both the user equilibrium (UE) and the social optimum (SO...

  8. The design of traffic signal coordinated control

    Science.gov (United States)

    Guo, Xueting; Sun, Hongsheng; Wang, Xifu

    2017-05-01

    Traffic as the tertiary industry is an important pillar industry to support the normal development of the economy. But now China's road traffic development and economic development has shown a great imbalance and fault phenomenon, which greatly inhibited the normal development of China's economy. Now in many large and medium-sized cities in China are implementing green belt construction. The so-called green band is when the road conditions to meet the conditions for the establishment of the green band, the sections of the intersection of several planning to a traffic coordination control system, so that when the driver at a specific speed can be achieved without stopping the continuous Through the intersection. Green belt can effectively reduce the delay and queuing length of vehicle driving, the normal function of urban roads and reduce the economic losses caused by traffic congestion is a great help. In this paper, the theoretical basis of the design of the coordinated control system is described. Secondly, the green time offset is calculated by the analytic method and the green band is established. And then the VISSIM software is used to simulate the traffic system before and after the improvement. Finally, the results of the two simulations are compared.

  9. Radiotherapy for hypersplenism from congestive splenomegaly

    International Nuclear Information System (INIS)

    Liu, Mu-Tai; Hsieh, Chang-Yo; Chang, Tung-Hao; Lin, Jao-Perng; Huang, Chia-Chun

    2004-01-01

    We evaluated the effects of splenic irradiation on the common hematological disorders of hypersplenism. From August 2002 to March 2003, five patients with hypersplenism due to congestive splenomegaly underwent splenic irradiation at the Department od Radiation Oncology, Changhua Chirstian Hospital, Taiwan. 3 were males and 2 were females aging from 38 to 66 years. All patients had history of liver cirrhosis. 4 patients underwent thee-dimensional conformal radiotherapy and received conventional radiotherapy with anterior-posterior parallel opposing fields. The followup-period ranged from 1 to 7 months. Thrombocytopenia and splenomegaly were found in all 5 patients by physical examination, hematological test, abdominal sonography and/or abdominal computed tomography. After radiotherapy, thrombocytopenia improved, but leukopenia and anemia did not. No complication due to radiotherapy was found during the follow-up period after splenic irradiation. 2 patients died of hepatocellular carcinoma with active bleeding. One patient died of renal failure due to end-stage renal disease. Based on our results, it seems that splenic irradiation might be effective in treating thrombocytopenia and splenomegaly. Splenic irradiatin seems to be effective for thrombocytopenia, splenomegaly and splenic pain associated with hypersplenism from congenstive splenomegaly. This approach is non-invasive and may be an alternative treatment for splenectomy and splenic embolization for patients with hypersplenism due to congestive splenomegaly. The shortcoming of this study are small sample size, short period of follow-up and lack of randomization. A randomized control trial with more cases and further follow-up of hematological tests and splenic size estimation are warranted to evaluate long term improvement of congestive splenomegaly with thrombocytopeniaafter splenic irradiation

  10. Transmission congestion management in the electricity market

    Science.gov (United States)

    Chen, Yue

    2018-04-01

    In this paper we mainly discuss how to optimize the arrangement to decrease the loss of each line when the power generation side of the system transmission congestion occurs in a safe and economical manner. We respectively set the adjust model if the transmission can be eliminated which can calculate the best scheme and safety margin model when transmission cannot be eliminated which is a multi-objective planning problem. We solve the two models on the condition of the load power demands are 982.4MW and 1052.8 MW by Lingo and get the optimal management scheme.

  11. Simulation of three lanes one-way freeway in low visibility weather by possible traffic accidents

    Science.gov (United States)

    Pang, Ming-bao; Zheng, Sha-sha; Cai, Zhang-hui

    2015-09-01

    The aim of this work is to investigate the traffic impact of low visibility weather on a freeway including the fraction of real vehicle rear-end accidents and road traffic capacity. Based on symmetric two-lane Nagel-Schreckenberg (STNS) model, a cellular automaton model of three-lane freeway mainline with the real occurrence of rear-end accidents in low visibility weather, which considers delayed reaction time and deceleration restriction, was established with access to real-time traffic information of intelligent transportation system (ITS). The characteristics of traffic flow in different visibility weather were discussed via the simulation experiments. The results indicate that incoming flow control (decreasing upstream traffic volume) and inputting variable speed limits (VSL) signal are effective in accident reducing and road actual traffic volume's enhancing. According to different visibility and traffic demand the appropriate control strategies should be adopted in order to not only decrease the probability of vehicle accidents but also avoid congestion.

  12. Continuous integration congestion cost allocation based on sensitivity

    International Nuclear Information System (INIS)

    Wu, Z.Q.; Wang, Y.N.

    2004-01-01

    Congestion cost allocation is a very important topic in congestion management. Allocation methods based on the Aumann-Shapley value use the discrete numerical integration method, which needs to solve the incremented OPF solution many times, and as such it is not suitable for practical application to large-scale systems. The optimal solution and its sensitivity change tendency during congestion removal using a DC optimal power flow (OPF) process is analysed. A simple continuous integration method based on the sensitivity is proposed for the congestion cost allocation. The proposed sensitivity analysis method needs a smaller computation time than the method based on using the quadratic method and inner point iteration. The proposed congestion cost allocation method uses a continuous integration method rather than discrete numerical integration. The method does not need to solve the incremented OPF solutions; which allows it use in large-scale systems. The method can also be used for AC OPF congestion management. (author)

  13. London-type congestion tax with revenue-recycling

    OpenAIRE

    Yukihiro Kidokoro

    2005-01-01

    Road pricing in London attracts a great deal of interest. A challenging aspect of the London scheme is that congestion tax revenue is used to upgrade public transit networks. Although Parry and Bento (2001) show that the total social surplus would increase if congestion tax revenues are used to cut labor taxes, political difficulties exist in implementing revenue-recycling between congestion taxes and labor taxes. Given such political difficulties, the London scheme seems to be very attractiv...

  14. Automation of Data Traffic Control on DSM Architecture

    Science.gov (United States)

    Frumkin, Michael; Jin, Hao-Qiang; Yan, Jerry

    2001-01-01

    The design of distributed shared memory (DSM) computers liberates users from the duty to distribute data across processors and allows for the incremental development of parallel programs using, for example, OpenMP or Java threads. DSM architecture greatly simplifies the development of parallel programs having good performance on a few processors. However, to achieve a good program scalability on DSM computers requires that the user understand data flow in the application and use various techniques to avoid data traffic congestions. In this paper we discuss a number of such techniques, including data blocking, data placement, data transposition and page size control and evaluate their efficiency on the NAS (NASA Advanced Supercomputing) Parallel Benchmarks. We also present a tool which automates the detection of constructs causing data congestions in Fortran array oriented codes and advises the user on code transformations for improving data traffic in the application.

  15. Congestion cost allocation method in a pool model

    International Nuclear Information System (INIS)

    Jung, H.S.; Hur, D.; Park, J.K.

    2003-01-01

    The congestion cost caused by transmission capacities and voltage limit is an important issue in a competitive electricity market. To allocate the congestion cost equitably, the active constraints in a constrained dispatch and the sequence of these constraints should be considered. A multi-stage method is proposed which reflects the effects of both the active constraints and the sequence. In a multi-stage method, the types of congestion are analysed in order to consider the sequence, and the relationship between congestion and the active constraints is derived in a mathematical way. The case study shows that the proposed method can give more accurate and equitable signals to customers. (Author)

  16. Electricity transmission congestion costs: A review of recent reports

    Energy Technology Data Exchange (ETDEWEB)

    Lesieutre, Bernard C.; Eto, Joseph H.

    2003-10-01

    Recently, independent system operators (ISOs) and others have published reports on the costs of transmission congestion. The magnitude of congestion costs cited in these reports has contributed to the national discussion on the current state of U.S. electricity transmission system and whether it provides an adequate platform for competition in wholesale electricity markets. This report reviews reports of congestion costs and begins to assess their implications for the current national discussion on the importance of the U.S. electricity transmission system for enabling competitive wholesale electricity markets. As a guiding principle, we posit that a more robust electricity system could reduce congestion costs; and thereby, (1) facilitate more vibrant and fair competition in wholesale electricity markets, and (2) enable consumers to seek out the lowest prices for electricity. Yet, examining the details suggests that, sometimes, there will be trade-offs between these goals. Therefore, it is essential to understand who pays, how much, and how do they benefit in evaluating options (both transmission and non-transmission alternatives) to address transmission congestion. To describe the differences among published estimates of congestion costs, we develop and motivate three ways by which transmission congestion costs are calculated in restructured markets. The assessment demonstrates that published transmission congestion costs are not directly comparable because they have been developed to serve different purposes. More importantly, critical information needed to make them more comparable, for example in order to evaluate the impacts of options to relieve congestion, is sometimes not available.

  17. Congestion Pricing for Aircraft Pushback Slot Allocation

    Science.gov (United States)

    Zhang, Yaping

    2017-01-01

    In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the “external cost of surface congestion” is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm. PMID:28114429

  18. Crystal structures of three sterically congested disilanes

    Directory of Open Access Journals (Sweden)

    Kothanda Rama Pichaandi

    2017-03-01

    Full Text Available In the three sterically congested silanes, C24H38Si2 (1 (1,1,2,2-tetraisopropyl-1,2-diphenyldisilane, C24H34Br4Si2 (2 [1,1,2,2-tetrakis(2-bromopropan-2-yl-1,2-diphenyldisilane] and C32H38Si2 (3 (1,2-di-tert-butyl-1,1,2,2-tetraphenyldisilane, the Si—Si bond length is shortest in (1 and longest in (2, with (3 having an intermediate value, which parallels the increasing steric congestion. A comparison of the two isopropyl derivatives, (1 and 2, shows a significant increase in the Si—C(ipso distance with the introduction of bromine. Also, in the brominated compound 2, attractive intermolecular Br...Br interactions exist with Br...Br separations ca 0.52 Å shorter than the sum of the van der Waals radii. In compound 2, one of the bromoisopropyl groups is rotationally disordered in an 0.8812 (9:0.1188 (9 ratio. Compound 3 exhibits `whole molecule' disorder in a 0.9645 (7:0.0355 (7 ratio with the Si—Si bonds in the two components making an angle of ca 66°.

  19. Effects of mental workload on physiological and subjective responses during traffic density monitoring: A field study.

    Science.gov (United States)

    Fallahi, Majid; Motamedzade, Majid; Heidarimoghadam, Rashid; Soltanian, Ali Reza; Miyake, Shinji

    2016-01-01

    This study evaluated operators' mental workload while monitoring traffic density in a city traffic control center. To determine the mental workload, physiological signals (ECG, EMG) were recorded and the NASA-Task Load Index (TLX) was administered for 16 operators. The results showed that the operators experienced a larger mental workload during high traffic density than during low traffic density. The traffic control center stressors caused changes in heart rate variability features and EMG amplitude, although the average workload score was significantly higher in HTD conditions than in LTD conditions. The findings indicated that increasing traffic congestion had a significant effect on HR, RMSSD, SDNN, LF/HF ratio, and EMG amplitude. The results suggested that when operators' workload increases, their mental fatigue and stress level increase and their mental health deteriorate. Therefore, it maybe necessary to implement an ergonomic program to manage mental health. Furthermore, by evaluating mental workload, the traffic control center director can organize the center's traffic congestion operators to sustain the appropriate mental workload and improve traffic control management. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  20. Online Traffic Signal Control for Reducing Vehicle Carbon Dioxide Emissions

    Science.gov (United States)

    Oda, Toshihiko; Otokita, Tohru; Niikura, Satoshi

    In Japan, carbon dioxide (CO2) emissions caused by vehicles have been increasing year by year and it is well known that CO2 causes a serious global warming problem. For urban traffic control systems, there is a great demand for realization of signal control measures as soon as possible due to the urgency of the recent environmental situation. This paper describes a new traffic signal control for reducing vehicle CO2 emissions on an arterial road. First, we develop a model for estimating the emissions using the traffic delay and the number of stops a driver makes. Second, to find the optimal control parameters, we introduce a random search method with rapid convergence suitable for an online traffic control. We conduct experiments in Kawasaki to verify the effectiveness of our method. The experiments show that our approach decreases not only the emissions but also congestion and travel time significantly, compared to the method implemented in the real system.