Video Demo: Deep Reinforcement Learning for Coordination in Traffic Light Control

NARCIS (Netherlands)

van der Pol, E.; Oliehoek, F.A.; Bosse, T.; Bredeweg, B.

2016-01-01

This video demonstration contrasts two approaches to coordination in traffic light control using reinforcement learning: earlier work, based on a deconstruction of the state space into a linear combination of vehicle states, and our own approach based on the Deep Q-learning algorithm.

Credibility and Authenticity of Digitally Signed Videos in Traffic

Directory of Open Access Journals (Sweden)

Ivan Grgurević

2008-11-01

Full Text Available The paper presents the possibilities of insuring the credibilityand authenticity of the surveillance camera video by digitalsigning, using the public key infrastructure as part of interoperabletraffic and information system in the future intelligenttransport systems. The surveillance camera video is a sequenceof individual frames and a unique digital print, i. e. hash valueis calculated for each of these. By encryption of the hash valuesof the frames using private encryption key of the surveillancecentre, digital signatures are created and they are stored in thedatabase. The surveillance centre can issue a copy of the videoto all the interested subjects for scientific and research workand investigation. Regardless of the scope, each subsequentmanipulation of the video copy contents will certainly changethe hash value of all the frames. The procedure of determiningthe authenticity and credibility of videos is reduced to the comparisonof the hash values of the frames stored in the databaseof the surveillance centre with the values obtained from the interestedsubjects such as the traffic experts and investigators,surveillance-security services etc.

Effect and Analysis of Sustainable Cell Rate using MPEG video Traffic in ATM Networks

Directory of Open Access Journals (Sweden)

Sakshi Kaushal

2006-04-01

Full Text Available The broadband networks inhibit the capability to carry multiple types of traffic – voice, video and data, but these services need to be controlled according to the traffic contract negotiated at the time of the connection to maintain desired Quality of service. Such control techniques use traffic descriptors to evaluate its performance and effectiveness. In case of Variable Bit Rate (VBR services, Peak Cell Rate (PCR and its Cell Delay Variation Tolerance (CDVTPCR are mandatory descriptors. In addition to these, ATM Forum proposed Sustainable Cell Rate (SCR and its Cell delay variation tolerance (CDVTSCR. In this paper, we evaluated the impact of specific SCR and CDVTSCR values on the Usage Parameter Control (UPC performance in case of measured MPEG traffic for improving the efficiency

Effective Quality-of-Service Renegotiating Schemes for Streaming Video

Directory of Open Access Journals (Sweden)

Song Hwangjun

2004-01-01

Full Text Available This paper presents effective quality-of-service renegotiating schemes for streaming video. The conventional network supporting quality of service generally allows a negotiation at a call setup. However, it is not efficient for the video application since the compressed video traffic is statistically nonstationary. Thus, we consider the network supporting quality-of-service renegotiations during the data transmission and study effective quality-of-service renegotiating schemes for streaming video. The token bucket model, whose parameters are token filling rate and token bucket size, is adopted for the video traffic model. The renegotiating time instants and the parameters are determined by analyzing the statistical information of compressed video traffic. In this paper, two renegotiating approaches, that is, fixed renegotiating interval case and variable renegotiating interval case, are examined. Finally, the experimental results are provided to show the performance of the proposed schemes.

Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting

Directory of Open Access Journals (Sweden)

Hua-pu Lu

2015-01-01

Full Text Available This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. 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 methods.

Traffic Games: Modeling Freeway Traffic with Game Theory.

Science.gov (United States)

Cortés-Berrueco, Luis E; Gershenson, Carlos; Stephens, Christopher R

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers' interactions.

Sending Safety Video over WiMAX in Vehicle Communications

Directory of Open Access Journals (Sweden)

Jun Steed Huang

2013-10-01

Full Text Available This paper reports on the design of an OPNET simulation platform to test the performance of sending real-time safety video over VANET (Vehicular Adhoc NETwork using the WiMAX technology. To provide a more realistic environment for streaming real-time video, a video model was created based on the study of video traffic traces captured from a realistic vehicular camera, and different design considerations were taken into account. A practical controller over real-time streaming protocol is implemented to control data traffic congestion for future road safety development. Our driving video model was then integrated with the WiMAX OPNET model along with a mobility model based on real road maps. Using this simulation platform, different mobility cases have been studied and the performance evaluated in terms of end-to-end delay, jitter and visual experience.

The Measurement and Modeling of a P2P Streaming Video Service

Science.gov (United States)

Gao, Peng; Liu, Tao; Chen, Yanming; Wu, Xingyao; El-Khatib, Yehia; Edwards, Christopher

Most of the work on grid technology in video area has been generally restricted to aspects of resource scheduling and replica management. The traffic of such service has a lot of characteristics in common with that of the traditional video service. However the architecture and user behavior in Grid networks are quite different from those of traditional Internet. Considering the potential of grid networks and video sharing services, measuring and analyzing P2P IPTV traffic are important and fundamental works in the field grid networks.

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...

OPTIMISATION OF BUFFER SIZE FOR ENHANCING QOS OF VIDEO TRAFFIC USING CROSS LAYERED HYBRID TRANSPORT LAYER PROTOCOL APPROACH

OpenAIRE

S. Matilda; B. Palaniappan

2011-01-01

Video streaming is gaining importance, with the wide popularity of multimedia rich applications in the Internet. Video streams are delay sensitive and require seamless flow for continuous visualization. Properly designed buffers offer a solution to queuing delay. The diagonally opposite QoS metrics associated with video traffic poses an optimization problem, in the design of buffers. This paper is a continuation of our previous work [1] and deals with the design of buffers. It aims at finding...

Joint Content Placement and Traffic Management for Cloud Mobile Video Distribution over Software-Defined Networks

Institute of Scientific and Technical Information of China (English)

Zhenghuan Zhang; Xiaofeng Jiang; Hongsheng Xi

2016-01-01

To cope with the rapid growth of mobile video,video providers have leveraged cloud technologies to deploy their mobile video service system for more cost-effective and scalable performance.The emergence of Software-Defined Networking (SDN) provides a promising solution to manage the underlying network.In this paper,we introduce an SDN-enabled cloud mobile video distribution architecture and propose a joint video placement,request dispatching and traffic management mechanism to improve user experience and reduce the system operational cost.We use a utility function to capture the two aspects of user experience:the level of satisfaction and average latency,and formulate the joint optimization problem as a mixed integer programming problem.We develop an optimal algorithm based on dual decomposition and prove its optimality.We conduct simulations to evaluate the performance of our algorithm and the results show that our strategy can effectively cut down the total cost and guarantee user experience.

Traffic planning for non-homogeneous traffic

Indian Academy of Sciences (India)

Vehicles based on similar traffic operating characteristics are grouped into ... of distances to the video monitor involved using a measuring wheel to mark ... Secondly, the observers reviewed the videotape to sample traffic entity ...... makes a strong case for including service lanes for slow moving vehicles for improving the.

Bandwidth Reduction via Localized Peer-to-Peer (P2P Video

Directory of Open Access Journals (Sweden)

Ken Kerpez

2010-01-01

Full Text Available This paper presents recent research into P2P distribution of video that can be highly localized, preferably sharing content among users on the same access network and Central Office (CO. Models of video demand and localized P2P serving areas are presented. Detailed simulations of passive optical networks (PON are run, and these generate statistics of P2P video localization. Next-Generation PON (NG-PON is shown to fully enable P2P video localization, but the lower rates of Gigabit-PON (GPON restrict performance. Results here show that nearly all of the traffic volume of unicast video could be delivered via localized P2P. Strong growth in video delivery via localized P2P could lower overall future aggregation and core network bandwidth of IP video traffic by 58.2%, and total consumer Internet traffic by 43.5%. This assumes aggressive adoption of technologies and business practices that enable highly localized P2P video.

Traffic Flow Visualization and Control

National Research Council Canada - National Science Library

Larson, Robert

1999-01-01

.... Air Force Research Laboratory. It is a video-camera-based, wide-area, traffic surveillance and detection system that provides real-time traffic information to traffic management center operators...

Some random models in traffic science

Energy Technology Data Exchange (ETDEWEB)

Hjorth, U.

1996-06-01

We give an overview of stochastic models for the following traffic phenomena. Models for traffic flow including gaps and capacities for lanes, crossings and roundabouts. Models for wanted and achieved speed distributions. Mode selection models including dispersed equilibrium models and traffic accident models. Also some statistical questions are discussed. 60 refs, 1 tab

Video Self-Modeling

Science.gov (United States)

Buggey, Tom; Ogle, Lindsey

2012-01-01

Video self-modeling (VSM) first appeared on the psychology and education stage in the early 1970s. The practical applications of VSM were limited by lack of access to tools for editing video, which is necessary for almost all self-modeling videos. Thus, VSM remained in the research domain until the advent of camcorders and VCR/DVD players and,…

Heterogeneous traffic flow modelling using second-order macroscopic continuum model

Science.gov (United States)

Mohan, Ranju; Ramadurai, Gitakrishnan

2017-01-01

Modelling heterogeneous traffic flow lacking in lane discipline is one of the emerging research areas in the past few years. The two main challenges in modelling are: capturing the effect of varying size of vehicles, and the lack in lane discipline, both of which together lead to the 'gap filling' behaviour of vehicles. The same section length of the road can be occupied by different types of vehicles at the same time, and the conventional measure of traffic concentration, density (vehicles per lane per unit length), is not a good measure for heterogeneous traffic modelling. First aim of this paper is to have a parsimonious model of heterogeneous traffic that can capture the unique phenomena of gap filling. Second aim is to emphasize the suitability of higher-order models for modelling heterogeneous traffic. Third, the paper aims to suggest area occupancy as concentration measure of heterogeneous traffic lacking in lane discipline. The above mentioned two main challenges of heterogeneous traffic flow are addressed by extending an existing second-order continuum model of traffic flow, using area occupancy for traffic concentration instead of density. The extended model is calibrated and validated with field data from an arterial road in Chennai city, and the results are compared with those from few existing generalized multi-class models.

The RUBA Watchdog Video Analysis Tool

DEFF Research Database (Denmark)

Bahnsen, Chris Holmberg; Madsen, Tanja Kidholm Osmann; Jensen, Morten Bornø

We have developed a watchdog video analysis tool called RUBA (Road User Behaviour Analysis) to use for processing of traffic video. This report provides an overview of the functions of RUBA and gives a brief introduction into how analyses can be made in RUBA.......We have developed a watchdog video analysis tool called RUBA (Road User Behaviour Analysis) to use for processing of traffic video. This report provides an overview of the functions of RUBA and gives a brief introduction into how analyses can be made in RUBA....

A queuing model for road traffic simulation

International Nuclear Information System (INIS)

Guerrouahane, N.; Aissani, D.; Bouallouche-Medjkoune, L.; Farhi, N.

2015-01-01

We present in this article a stochastic queuing model for the raod traffic. The model is based on the M/G/c/c state dependent queuing model, and is inspired from the deterministic Godunov scheme for the road traffic simulation. We first propose a variant of M/G/c/c state dependent model that works with density-flow fundamental diagrams rather than density-speed relationships. We then extend this model in order to consider upstream traffic demand as well as downstream traffic supply. Finally, we show how to model a whole raod by concatenating raod sections as in the deterministic Godunov scheme

Model for traffic emissions estimation

Science.gov (United States)

Alexopoulos, A.; Assimacopoulos, D.; Mitsoulis, E.

A model is developed for the spatial and temporal evaluation of traffic emissions in metropolitan areas based on sparse measurements. All traffic data available are fully employed and the pollutant emissions are determined with the highest precision possible. The main roads are regarded as line sources of constant traffic parameters in the time interval considered. The method is flexible and allows for the estimation of distributed small traffic sources (non-line/area sources). The emissions from the latter are assumed to be proportional to the local population density as well as to the traffic density leading to local main arteries. The contribution of moving vehicles to air pollution in the Greater Athens Area for the period 1986-1988 is analyzed using the proposed model. Emissions and other related parameters are evaluated. Emissions from area sources were found to have a noticeable share of the overall air pollution.

A Framework for Video Modeling

NARCIS (Netherlands)

Petkovic, M.; Jonker, Willem

In recent years, research in video databases has increased greatly, but relatively little work has been done in the area of semantic content-based retrieval. In this paper, we present a framework for video modelling with emphasis on semantic content of video data. The video data model presented

No Reference Video-Quality-Assessment Model for Monitoring Video Quality of IPTV Services

Science.gov (United States)

Yamagishi, Kazuhisa; Okamoto, Jun; Hayashi, Takanori; Takahashi, Akira

Service providers should monitor the quality of experience of a communication service in real time to confirm its status. To do this, we previously proposed a packet-layer model that can be used for monitoring the average video quality of typical Internet protocol television content using parameters derived from transmitted packet headers. However, it is difficult to monitor the video quality per user using the average video quality because video quality depends on the video content. To accurately monitor the video quality per user, a model that can be used for estimating the video quality per video content rather than the average video quality should be developed. Therefore, to take into account the impact of video content on video quality, we propose a model that calculates the difference in video quality between the video quality of the estimation-target video and the average video quality estimated using a packet-layer model. We first conducted extensive subjective quality assessments for different codecs and video sequences. We then model their characteristics based on parameters related to compression and packet loss. Finally, we verify the performance of the proposed model by applying it to unknown data sets different from the training data sets used for developing the model.

Traffic flow dynamics. Data, models and simulation

Energy Technology Data Exchange (ETDEWEB)

Treiber, Martin [Technische Univ. Dresden (Germany). Inst. fuer Wirtschaft und Verkehr; Kesting, Arne [TomTom Development Germany GmbH, Berlin (Germany)

2013-07-01

First comprehensive textbook of this fascinating interdisciplinary topic which explains advances in a way that it is easily accessible to engineering, physics and math students. Presents practical applications of traffic theory such as driving behavior, stability analysis, stop-and-go waves, and travel time estimation. Presents the topic in a novel and systematic way by addressing both microscopic and macroscopic models with a focus on traffic instabilities. Revised and extended edition of the German textbook ''Verkehrsdynamik und -simulation''. This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on traffic instabilities and model calibration/validation present these topics in a novel and systematic way. Finally, the theoretical framework is shown at work in selected applications such as traffic-state and travel-time estimation, intelligent transportation systems, traffic operations management, and a detailed physics-based model for fuel consumption and emissions.

Video Quality Prediction Models Based on Video Content Dynamics for H.264 Video over UMTS Networks

Directory of Open Access Journals (Sweden)

Asiya Khan

2010-01-01

Full Text Available The aim of this paper is to present video quality prediction models for objective non-intrusive, prediction of H.264 encoded video for all content types combining parameters both in the physical and application layer over Universal Mobile Telecommunication Systems (UMTS networks. In order to characterize the Quality of Service (QoS level, a learning model based on Adaptive Neural Fuzzy Inference System (ANFIS and a second model based on non-linear regression analysis is proposed to predict the video quality in terms of the Mean Opinion Score (MOS. The objective of the paper is two-fold. First, to find the impact of QoS parameters on end-to-end video quality for H.264 encoded video. Second, to develop learning models based on ANFIS and non-linear regression analysis to predict video quality over UMTS networks by considering the impact of radio link loss models. The loss models considered are 2-state Markov models. Both the models are trained with a combination of physical and application layer parameters and validated with unseen dataset. Preliminary results show that good prediction accuracy was obtained from both the models. The work should help in the development of a reference-free video prediction model and QoS control methods for video over UMTS networks.

Stochastic Modeling of Traffic Air Pollution

DEFF Research Database (Denmark)

Thoft-Christensen, Palle

2014-01-01

In this paper, modeling of traffic air pollution is discussed with special reference to infrastructures. A number of subjects related to health effects of air pollution and the different types of pollutants are briefly presented. A simple model for estimating the social cost of traffic related air...... and using simple Monte Carlo techniques to obtain a stochastic estimate of the costs of traffic air pollution for infrastructures....... pollution is derived. Several authors have published papers on this very complicated subject, but no stochastic modelling procedure have obtained general acceptance. The subject is discussed basis of a deterministic model. However, it is straightforward to modify this model to include uncertain parameters...

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

Traffic modelling for Big Data backed telecom cloud

OpenAIRE

Via Baraldés, Anna

2016-01-01

The objective of this project is to provide traffic models based on new services characteristics. Specifically, we focus on modelling the traffic between origin-destination node pairs (also known as OD pairs) in a telecom network. Two use cases are distinguished: i) traffic generation in the context of simulation, and ii) traffic modelling for prediction in the context of big-data backed telecom cloud systems. To this aim, several machine learning and statistical models and technics are studi...

Modeling the heterogeneous traffic correlations in urban road systems using traffic-enhanced community detection approach

Science.gov (United States)

Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei

2018-07-01

A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.

Métodos de modelamiento y predicción de tráfico orientados a plataformas de transmisión de video e IPTV usando series de tiempo1

Directory of Open Access Journals (Sweden)

ayron Villanueva Ocampo

2012-12-01

Full Text Available This paper, intends to review the most important techniques that allow per- forming statistic video traffic modeling and forecasting, focusing in time series models, so we can identify which models are better to describe the representative IPTV stochastic traffic. For this purpose, we make a short introduction to time series analysis, and a review of the state of the art on video traffic modeling over data networks. From this research we conclude that, of all the available models to describe and forecast network traffic, the more appropriate to use within IPTV systems are ARIMA time series models, from which SARIMA model are the best option.

Automatic Traffic Data Collection under Varying Lighting and Temperature Conditions in Multimodal Environments: Thermal versus Visible Spectrum Video-Based Systems

Directory of Open Access Journals (Sweden)

Ting Fu

2017-01-01

Full Text Available Vision-based monitoring systems using visible spectrum (regular video cameras can complement or substitute conventional sensors and provide rich positional and classification data. Although new camera technologies, including thermal video sensors, may improve the performance of digital video-based sensors, their performance under various conditions has rarely been evaluated at multimodal facilities. The purpose of this research is to integrate existing computer vision methods for automated data collection and evaluate the detection, classification, and speed measurement performance of thermal video sensors under varying lighting and temperature conditions. Thermal and regular video data was collected simultaneously under different conditions across multiple sites. Although the regular video sensor narrowly outperformed the thermal sensor during daytime, the performance of the thermal sensor is significantly better for low visibility and shadow conditions, particularly for pedestrians and cyclists. Retraining the algorithm on thermal data yielded an improvement in the global accuracy of 48%. Thermal speed measurements were consistently more accurate than for the regular video at daytime and nighttime. Thermal video is insensitive to lighting interference and pavement temperature, solves issues associated with visible light cameras for traffic data collection, and offers other benefits such as privacy, insensitivity to glare, storage space, and lower processing requirements.

Traffic modelling validation of advanced driver assistance systems

NARCIS (Netherlands)

Tongeren, R. van; Gietelink, O.J.; Schutter, B. de; Verhaegen, M.

2007-01-01

This paper presents a microscopic traffic model for the validation of advanced driver assistance systems. This model describes single-lane traffic and is calibrated with data from a field operational test. To illustrate the use of the model, a Monte Carlo simulation of single-lane traffic scenarios

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.

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.

Modelling of H.264 MPEG2 TS Traffic Source

Directory of Open Access Journals (Sweden)

Stanislav Klucik

2013-01-01

Full Text Available This paper deals with IPTV traffic source modelling. Traffic sources are used for simulation, emulation and real network testing. This model is made as a derivation of known recorded traffic sources that are analysed and statistically processed. As the results show the proposed model causes in comparison to the known traffic source very similar network traffic parameters when used in a simulated network.

Real-time video analysis for retail stores

Science.gov (United States)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Characterization and Modeling of Network Traffic

DEFF Research Database (Denmark)

Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur

2011-01-01

-arrival time, IP addresses, port numbers and transport protocol are the only necessary parameters to model network traffic behaviour. In order to recreate this behaviour, a complex model is needed which is able to recreate traffic behaviour based on a set of statistics calculated from the parameters values...

Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models, Splines and Other Traffic Variables

NARCIS (Netherlands)

Anacleto, Osvaldo; Queen, Catriona; Albers, Casper J.

Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for

Research on quality metrics of wireless adaptive video streaming

Science.gov (United States)

Li, Xuefei

2018-04-01

With the development of wireless networks and intelligent terminals, video traffic has increased dramatically. Adaptive video streaming has become one of the most promising video transmission technologies. For this type of service, a good QoS (Quality of Service) of wireless network does not always guarantee that all customers have good experience. Thus, new quality metrics have been widely studies recently. Taking this into account, the objective of this paper is to investigate the quality metrics of wireless adaptive video streaming. In this paper, a wireless video streaming simulation platform with DASH mechanism and multi-rate video generator is established. Based on this platform, PSNR model, SSIM model and Quality Level model are implemented. Quality Level Model considers the QoE (Quality of Experience) factors such as image quality, stalling and switching frequency while PSNR Model and SSIM Model mainly consider the quality of the video. To evaluate the performance of these QoE models, three performance metrics (SROCC, PLCC and RMSE) which are used to make a comparison of subjective and predicted MOS (Mean Opinion Score) are calculated. From these performance metrics, the monotonicity, linearity and accuracy of these quality metrics can be observed.

Remote Video Monitor of Vehicles in Cooperative Information Platform

Science.gov (United States)

Qin, Guofeng; Wang, Xiaoguo; Wang, Li; Li, Yang; Li, Qiyan

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.

Traffic analysis toolbox volume XI : weather and traffic analysis, modeling and simulation.

Science.gov (United States)

2010-12-01

This document presents a weather module for the traffic analysis tools program. It provides traffic engineers, transportation modelers and decisions makers with a guide that can incorporate weather impacts into transportation system analysis and mode...

Traffic flow dynamics data, models and simulation

CERN Document Server

Treiber, Martin

2013-01-01

This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on ...

Semantic-based surveillance video retrieval.

Science.gov (United States)

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Particle hopping vs. fluid-dynamical models for traffic flow

Energy Technology Data Exchange (ETDEWEB)

Nagel, K.

1995-12-31

Although particle hopping models have been introduced into traffic science in the 19509, their systematic use has only started recently. Two reasons for this are, that they are advantageous on modem computers, and that recent theoretical developments allow analytical understanding of their properties and therefore more confidence for their use. In principle, particle hopping models fit between microscopic models for driving and fluiddynamical models for traffic flow. In this sense, they also help closing the conceptual gap between these two. This paper shows connections between particle hopping models and traffic flow theory. It shows that the hydrodynamical limits of certain particle hopping models correspond to the Lighthill-Whitham theory for traffic flow, and that only slightly more complex particle hopping models produce already the correct traffic jam dynamics, consistent with recent fluid-dynamical models for traffic flow. By doing so, this paper establishes that, on the macroscopic level, particle hopping models are at least as good as fluid-dynamical models. Yet, particle hopping models have at least two advantages over fluid-dynamical models: they straightforwardly allow microscopic simulations, and they include stochasticity.

Validating the passenger traffic model for Copenhagen

DEFF Research Database (Denmark)

Overgård, Christian Hansen; VUK, Goran

2006-01-01

The paper presents a comprehensive validation procedure for the passenger traffic model for Copenhagen based on external data from the Danish national travel survey and traffic counts. The model was validated for the years 2000 to 2004, with 2004 being of particular interest because the Copenhagen...... matched the observed traffic better than those of the transit assignment model. With respect to the metro forecasts, the model over-predicts metro passenger flows by 10% to 50%. The wide range of findings from the project resulted in two actions. First, a project was started in January 2005 to upgrade...

On traffic modelling in GPRS networks

DEFF Research Database (Denmark)

Madsen, Tatiana Kozlova; Schwefel, Hans-Peter; Prasad, Ramjee

2005-01-01

Optimal design and dimensioning of wireless data networks, such as GPRS, requires the knowledge of traffic characteristics of different data services. This paper presents an in-detail analysis of an IP-level traffic measurements taken in an operational GPRS network. The data measurements reported...... here are done at the Gi interface. The aim of this paper is to reveal some key statistics of GPRS data applications and to validate if the existing traffic models can adequately describe traffic volume and inter-arrival time distribution for different services. Additionally, we present a method of user...

Road traffic noise: self-reported noise annoyance versus GIS modelled road traffic noise exposure.

Science.gov (United States)

Birk, Matthias; Ivina, Olga; von Klot, Stephanie; Babisch, Wolfgang; Heinrich, Joachim

2011-11-01

self-reported road traffic noise annoyance is commonly used in epidemiological studies for assessment of potential health effects. Alternatively, some studies have used geographic information system (GIS) modelled exposure to road traffic noise as an objective parameter. The aim of this study was to analyse the association between noise exposure due to neighbouring road traffic and the noise annoyance of adults, taking other determinants into consideration. parents of 951 Munich children from the two German birth cohorts GINIplus and LISAplus reported their annoyance due to road traffic noise at home. GIS modelled road traffic noise exposure (L(den), maximum within a 50 m buffer) from the noise map of the city of Munich was available for all families. GIS-based calculated distance to the closest major road (≥10,000 vehicles per day) and questionnaire based-information about family income, parental education and the type of the street of residence were explored for their potential influence. An ordered logit regression model was applied. The noise levels (L(den)) and the reported noise annoyance were compared with an established exposure-response function. the correlation between noise annoyance and noise exposure (L(den)) was fair (Spearman correlation r(s) = 0.37). The distance to a major road and the type of street were strong predictors for the noise annoyance. The annoyance modelled by the established exposure-response function and that estimated by the ordered logit model were moderately associated (Pearson's correlation r(p) = 0.50). road traffic noise annoyance was associated with GIS modelled neighbouring road traffic noise exposure (L(den)). The distance to a major road and the type of street were additional explanatory factors of the noise annoyance appraisal.

Modelling traffic pollution in streets

Energy Technology Data Exchange (ETDEWEB)

Berkowicz, R.; Hertel, O. [National Environmental Research Inst., Dept. of Atmospheric Environment, Roskilde (Denmark); Larsen, S.E.; Soerensen, N.N.; Nielsen, M. [Risoe National Lab., Dept. of Meteorology and Wind Energy, Roskilde (Denmark)

1997-01-01

This report concerns mainly the subject related to modelling air pollution from traffic in urban streets. A short overview is presented over the theoretical aspects and examples of most commonly used methods and models are given. Flow and dispersion conditions in street canyons are discussed and the presentation is substantiated with the analysis of the experimental data. The main emphasis is on the modelling methods that are suitable for routine applications and a more detailed presentation is given of the Operational Street Pollution Model (OSPM), which was developed by the National Environmental Research Institute. The model is used for surveillance of air pollution from traffic in Danish cities and also for special air pollution studies. (au) 76 refs.

Usage of Video Analysis of Traffic Conflicts for the Evaluation of Inappropriately Designed Building Elements on Intersections

Science.gov (United States)

Krivda, Vladislav; Petru, Jan

2018-04-01

Human society is constantly evolving in all areas. The transport is no exception – especially development of road transport is considerable and visible on all levels. However, it is necessary to look for tools that can harmonize economic and social progress with the full preservation of the environment for future generations. The so-called sustainable development of road transport is also closely related to the issue of creating safe transport infrastructure. For example, roads must be in compliance with technical rules on one hand and on the other one they have to be clearly understandable for all road participants (drivers, pedestrians, etc.). Unfortunately, even if the designer of transport construction meets the technical requirements, the result is a dangerous place where very frequently the accidents or traffic conflicts take place. There exist statistics of accidents, but on the contrary, there are not any statistics of traffic conflicts. And simply monitoring the traffic conflicts can lead to early detection of problematic places in road infrastructure and thus increasing the safety in the road traffic. There are many methods used for monitoring traffic conflicts. The method used in the Czech Republic is described in the submitted paper. The original method, which monitored mainly and only the behaviour of drivers and their mistakes, was innovated, so that it could be used also for evaluation of inappropriately designed building elements of road constructions. Therefore, the paper deals with the description of so-called Innovated Video Analysis of Traffic Conflicts (IVATC) and with the usage of this method for one particular example of intersection, where larger vehicles (buses, trucks, etc.) had problems with passing through it. It points out to the fact that even a relatively small change can lead to the increase of the road safety.

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

Research on the Method of Traffic Organization and Optimization Based on Dynamic Traffic Flow Model

Directory of Open Access Journals (Sweden)

Shu-bin Li

2017-01-01

Full Text Available The modern transportation system is becoming sluggish by traffic jams, so much so that it can harm the economic and society in our country. One of the reasons is the surging vehicles day by day. Another reason is the shortage of the traffic supply seriously. But the most important reason is that the traffic organization and optimization hardly met the conditions of modern transport development. In this paper, the practical method of the traffic organization and optimization used in regional area is explored by the dynamic traffic network analysis method. Firstly, the operational states of the regional traffic network are obtained by simulation method based on the self-developed traffic simulation software DynaCHINA, in which the improved traffic flow simulation model was proposed in order to be more suitable for actual domestic urban transport situation. Then the appropriated optimization model and algorithm were proposed according to different optimized content and organization goals, and the traffic simulation processes more suitable to regional optimization were designed exactly. Finally, a regional network in Tai’an city was selected as an example. The simulation results show that the proposed method is effective and feasible. It can provide strong scientific and technological support for the traffic management department.

Traffic Modelling for Moving-Block Train Control System

International Nuclear Information System (INIS)

Tang Tao; Li Keping

2007-01-01

This paper presents a new cellular automaton (CA) model for train control system simulation. In the proposed CA model, the driver reactions to train movements are captured by some updated rules. The space-time diagram of traffic flow and the trajectory of train movement is used to obtain insight into the characteristic behavior of railway traffic flow. A number of simulation results demonstrate that the proposed CA model can be successfully used for the simulations of railway traffic. Not only the characteristic behavior of railway traffic flow can be reproduced, but also the simulation values of the minimum time headway are close to the theoretical values.

Dynamic Power-Saving Method for Wi-Fi Direct Based IoT Networks Considering Variable-Bit-Rate Video Traffic.

Science.gov (United States)

Jin, Meihua; Jung, Ji-Young; Lee, Jung-Ryun

2016-10-12

With the arrival of the era of Internet of Things (IoT), Wi-Fi Direct is becoming an emerging wireless technology that allows one to communicate through a direct connection between the mobile devices anytime, anywhere. In Wi-Fi Direct-based IoT networks, all devices are categorized by group of owner (GO) and client. Since portability is emphasized in Wi-Fi Direct devices, it is essential to control the energy consumption of a device very efficiently. In order to avoid unnecessary power consumed by GO, Wi-Fi Direct standard defines two power-saving methods: Opportunistic and Notice of Absence (NoA) power-saving methods. In this paper, we suggest an algorithm to enhance the energy efficiency of Wi-Fi Direct power-saving, considering the characteristics of multimedia video traffic. Proposed algorithm utilizes the statistical distribution for the size of video frames and adjusts the lengths of awake intervals in a beacon interval dynamically. In addition, considering the inter-dependency among video frames, the proposed algorithm ensures that a video frame having high priority is transmitted with higher probability than other frames having low priority. Simulation results show that the proposed method outperforms the traditional NoA method in terms of average delay and energy efficiency.

Microscopic modeling of multi-lane highway traffic flow

Science.gov (United States)

Hodas, Nathan O.; Jagota, Anand

2003-12-01

We discuss a microscopic model for the study of multi-lane highway traffic flow dynamics. Each car experiences a force resulting from a combination of the desire of the driver to attain a certain velocity, aerodynamic drag, and change of the force due to car-car interactions. The model also includes multi-lane simulation capability and the ability to add and remove obstructions. We implement the model via a Java applet, which is used to simulate traffic jam formation, the effect of bottlenecks on traffic flow, and the existence of light, medium, and heavy traffic flow. The simulations also provide insight into how the properties of individual cars result in macroscopic behavior. Because the investigation of emergent characteristics is so common in physics, the study of traffic in this manner sheds new light on how the micro-to-macro transition works in general.

Genetics of traffic assignment models for strategic transport planning

NARCIS (Netherlands)

Bliemer, M.C.J.; Raadsen, M.P.H.; Brederode, L.J.N.; Bell, M.G.H.; Wismans, Luc Johannes Josephus; Smith, M.J.

2016-01-01

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic

Comparison of the Effects of Continuous Video Modeling, Video Prompting, and Video Modeling on Task Completion by Young Adults with Moderate Intellectual Disability

Science.gov (United States)

Mechling, Linda C.; Ayres, Kevin M.; Bryant, Kathryn J.; Foster, Ashley L.

2014-01-01

This study compared the effects of three procedures (video prompting: VP, video modeling: VM, and continuous video modeling: CVM) on task completion by three high school students with moderate intellectual disability. The comparison was made across three sets of fundamentally different tasks (putting away household items in clusters of two items;…

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.

A Modified Cellular Automaton Approach for Mixed Bicycle Traffic Flow Modeling

Directory of Open Access Journals (Sweden)

Xiaonian Shan

2015-01-01

Full Text Available Several previous studies have used the Cellular Automaton (CA for the modeling of bicycle traffic flow. However, previous CA models have several limitations, resulting in differences between the simulated and the observed traffic flow features. The primary objective of this study is to propose a modified CA model for simulating the characteristics of mixed bicycle traffic flow. Field data were collected on physically separated bicycle path in Shanghai, China, and were used to calibrate the CA model using the genetic algorithm. Traffic flow features between simulations of several CA models and field observations were compared. The results showed that our modified CA model produced more accurate simulation for the fundamental diagram and the passing events in mixed bicycle traffic flow. Based on our model, the bicycle traffic flow features, including the fundamental diagram, the number of passing events, and the number of lane changes, were analyzed. We also analyzed the traffic flow features with different traffic densities, traffic components on different travel lanes. Results of the study can provide important information for understanding and simulating the operations of mixed bicycle traffic flow.

Attention modeling for video quality assessment

DEFF Research Database (Denmark)

You, Junyong; Korhonen, Jari; Perkis, Andrew

2010-01-01

averaged spatiotemporal pooling. The local quality is derived from visual attention modeling and quality variations over frames. Saliency, motion, and contrast information are taken into account in modeling visual attention, which is then integrated into IQMs to calculate the local quality of a video frame...... average between the global quality and the local quality. Experimental results demonstrate that the combination of the global quality and local quality outperforms both sole global quality and local quality, as well as other quality models, in video quality assessment. In addition, the proposed video...... quality modeling algorithm can improve the performance of image quality metrics on video quality assessment compared to the normal averaged spatiotemporal pooling scheme....

3D Traffic Scene Understanding From Movable Platforms.

Science.gov (United States)

Geiger, Andreas; Lauer, Martin; Wojek, Christian; Stiller, Christoph; Urtasun, Raquel

2014-05-01

In this paper, we present a novel probabilistic generative model for multi-object traffic scene understanding from movable platforms which reasons jointly about the 3D scene layout as well as the location and orientation of objects in the scene. In particular, the scene topology, geometry, and traffic activities are inferred from short video sequences. Inspired by the impressive driving capabilities of humans, our model does not rely on GPS, lidar, or map knowledge. Instead, it takes advantage of a diverse set of visual cues in the form of vehicle tracklets, vanishing points, semantic scene labels, scene flow, and occupancy grids. For each of these cues, we propose likelihood functions that are integrated into a probabilistic generative model. We learn all model parameters from training data using contrastive divergence. Experiments conducted on videos of 113 representative intersections show that our approach successfully infers the correct layout in a variety of very challenging scenarios. To evaluate the importance of each feature cue, experiments using different feature combinations are conducted. Furthermore, we show how by employing context derived from the proposed method we are able to improve over the state-of-the-art in terms of object detection and object orientation estimation in challenging and cluttered urban environments.

Construction and simulation of a novel continuous traffic flow model

International Nuclear Information System (INIS)

Hwang, Yao-Hsin; Yu, Jui-Ling

2017-01-01

In this paper, we aim to propose a novel mathematical model for traffic flow and apply a newly developed characteristic particle method to solve the associate governing equations. As compared with the existing non-equilibrium higher-order traffic flow models, the present one is put forward to satisfy the following three conditions: 1.Preserve the equilibrium state in the smooth region. 2.Yield an anisotropic propagation of traffic flow information. 3.Expressed with a conservation law form for traffic momentum. These conditions will ensure a more practical simulation in traffic flow physics: The current traffic will not be influenced by the condition in the behind and result in unambiguous condition across a traffic shock. Through analyses of characteristics, stability condition and steady-state solution adherent to the equation system, it is shown that the proposed model actually conform to these conditions. Furthermore, this model can be cast into its characteristic form which, incorporated with the Rankine-Hugoniot relation, is appropriate to be simulated by the characteristic particle method to obtain accurate computational results. - Highlights: • The traffic model expressed with the momentum conservation law. • Traffic flow information propagate anisotropically and preserve the equilibrium state in the smooth region. • Computational particles of two families are invented to mimic forward-running and backward-running characteristics. • Formation of shocks will be naturally detected by the intersection of computational particles of same family. • A newly developed characteristic particle method is used to simulate traffic flow model equations.

Road traffic impact on urban water quality: a step towards integrated traffic, air and stormwater modelling.

Science.gov (United States)

Fallah Shorshani, Masoud; Bonhomme, Céline; Petrucci, Guido; André, Michel; Seigneur, Christian

2014-04-01

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.

Development of Road Traffic Assignment and Assessment Sub-Model Applied in the Traffic Study ...

Directory of Open Access Journals (Sweden)

Dražen Topolnik

2012-10-01

Full Text Available The described sub-model is just one small segment of theTraffic Study of the City of Zagreb, in the development of whichnumerous foreign and national experts and institutions tookpart. After comprehensive collection and processing of inputdata, the traffic experts, using the software package "MVATRIPS" for the analysis and search for optimal solutions to theproblem of traffic system, provided the models of public urbantransit for the future.This paper describes the analysis and assessment of sub-models in road traffic assignment for the morning peak, afternoonpeak and average off-peak hours. The principles of assignmentprocedure have been described as well as the convergencetests. The following has been specified: the users categories,the public transit pre-load, and the passenger car unit(PC U. The key guideline in selecting the route is a generalisedformulation of costs presented in the paper. The procedures ofcalibration and the assessment of the finite model have alsobeen defined according to the screenline flows, link flows, andtravelling times. In the end, the summary is given of the basiccharacteristics of the finite travelling matrices.

Video coding for decoding power-constrained embedded devices

Science.gov (United States)

Lu, Ligang; Sheinin, Vadim

2004-01-01

Low power dissipation and fast processing time are crucial requirements for embedded multimedia devices. This paper presents a technique in video coding to decrease the power consumption at a standard video decoder. Coupled with a small dedicated video internal memory cache on a decoder, the technique can substantially decrease the amount of data traffic to the external memory at the decoder. A decrease in data traffic to the external memory at decoder will result in multiple benefits: faster real-time processing and power savings. The encoder, given prior knowledge of the decoder"s dedicated video internal memory cache management scheme, regulates its choice of motion compensated predictors to reduce the decoder"s external memory accesses. This technique can be used in any standard or proprietary encoder scheme to generate a compliant output bit stream decodable by standard CPU-based and dedicated hardware-based decoders for power savings with the best quality-power cost trade off. Our simulation results show that with a relatively small amount of dedicated video internal memory cache, the technique may decrease the traffic between CPU and external memory over 50%.

ANALYSIS OF SPATIO-TEMPORAL TRAFFIC PATTERNS BASED ON PEDESTRIAN TRAJECTORIES

Directory of Open Access Journals (Sweden)

S. Busch

2016-06-01

Full Text Available For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories

Science.gov (United States)

Busch, S.; Schindler, T.; Klinger, T.; Brenner, C.

2016-06-01

For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

Hierarchical and coupling model of factors influencing vessel traffic flow.

Science.gov (United States)

Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

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.

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.

Perceptual video quality assessment in H.264 video coding standard using objective modeling.

Science.gov (United States)

Karthikeyan, Ramasamy; Sainarayanan, Gopalakrishnan; Deepa, Subramaniam Nachimuthu

2014-01-01

Since usage of digital video is wide spread nowadays, quality considerations have become essential, and industry demand for video quality measurement is rising. This proposal provides a method of perceptual quality assessment in H.264 standard encoder using objective modeling. For this purpose, quality impairments are calculated and a model is developed to compute the perceptual video quality metric based on no reference method. Because of the shuttle difference between the original video and the encoded video the quality of the encoded picture gets degraded, this quality difference is introduced by the encoding process like Intra and Inter prediction. The proposed model takes into account of the artifacts introduced by these spatial and temporal activities in the hybrid block based coding methods and an objective modeling of these artifacts into subjective quality estimation is proposed. The proposed model calculates the objective quality metric using subjective impairments; blockiness, blur and jerkiness compared to the existing bitrate only calculation defined in the ITU G 1070 model. The accuracy of the proposed perceptual video quality metrics is compared against popular full reference objective methods as defined by VQEG.

Indicators of residential traffic exposure: Modelled NOX, traffic proximity, and self-reported exposure in RHINE III

Science.gov (United States)

Carlsen, Hanne Krage; Bäck, Erik; Eneroth, Kristina; Gislason, Thorarinn; Holm, Mathias; Janson, Christer; Jensen, Steen Solvang; Johannessen, Ane; Kaasik, Marko; Modig, Lars; Segersson, David; Sigsgaard, Torben; Forsberg, Bertil; Olsson, David; Orru, Hans

2017-10-01

Few studies have investigated associations between self-reported and modelled exposure to traffic pollution. The objective of this study was to examine correlations between self-reported traffic exposure and modelled (a) NOX and (b) traffic proximity in seven different northern European cities; Aarhus (Denmark), Bergen (Norway), Gothenburg, Umeå, and Uppsala (Sweden), Reykjavik (Iceland), and Tartu (Estonia). We analysed data from the RHINE III (Respiratory Health in Northern Europe, http://www.rhine.nu)

Lagrangian generic second order traffic flow models for node

Directory of Open Access Journals (Sweden)

Asma Khelifi

2018-02-01

Full Text Available This study sheds light on higher order macroscopic traffic flow modeling on road networks, thanks to the generic second order models (GSOM family which embeds a myriad of traffic models. It has been demonstrated that such higher order models are easily solved in Lagrangian coordinates which are compatible with both microscopic and macroscopic descriptions. The generalized GSOM model is reformulated in the Lagrangian coordinate system to develop a more efficient numerical method. The difficulty in applying this approach on networks basically resides in dealing with node dynamics. Traffic flow characteristics at node are different from that on homogeneous links. Different geometry features can lead to different critical research issues. For instance, discontinuity in traffic stream can be an important issue for traffic signal operations, while capacity drop may be crucial for lane-merges. The current paper aims to establish and analyze a new adapted node model for macroscopic traffic flow models by applying upstream and downstream boundary conditions on the Lagrangian coordinates in order to perform simulations on networks of roads, and accompanying numerical method. The internal node dynamics between upstream and downstream links are taken into account of the node model. Therefore, a numerical example is provided to underscore the efficiency of this approach. Simulations show that the discretized node model yields accurate results. Additional kinematic waves and contact discontinuities are induced by the variation of the driver attribute.

Does the Model Matter? Comparing Video Self-Modeling and Video Adult Modeling for Task Acquisition and Maintenance by Adolescents with Autism Spectrum Disorders

Science.gov (United States)

Cihak, David F.; Schrader, Linda

2009-01-01

The purpose of this study was to compare the effectiveness and efficiency of learning and maintaining vocational chain tasks using video self-modeling and video adult modeling instruction. Four adolescents with autism spectrum disorders were taught vocational and prevocational skills. Although both video modeling conditions were effective for…

A General Microscopic Traffic Model Yielding Dissipative Shocks

DEFF Research Database (Denmark)

Gaididei, Yuri Borisovich; Caputo, Jean Guy; Christiansen, Peter Leth

2018-01-01

We consider a general microscopic traffic model with a delay. An algebraic traffic function reduces the equation to the Aw-Rascle microscopic model while a sigmoid function gives the standard “follow the leader”. For zero delay we prove that the homogeneous solution is globally stable...

Hierarchical and coupling model of factors influencing vessel traffic flow.

Directory of Open Access Journals (Sweden)

Zhao Liu

Full Text Available Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

Modeling self-consistent multi-class dynamic traffic flow

Science.gov (United States)

Cho, Hsun-Jung; Lo, Shih-Ching

2002-09-01

In this study, we present a systematic self-consistent multiclass multilane traffic model derived from the vehicular Boltzmann equation and the traffic dispersion model. The multilane domain is considered as a two-dimensional space and the interaction among vehicles in the domain is described by a dispersion model. The reason we consider a multilane domain as a two-dimensional space is that the driving behavior of road users may not be restricted by lanes, especially motorcyclists. The dispersion model, which is a nonlinear Poisson equation, is derived from the car-following theory and the equilibrium assumption. Under the concept that all kinds of users share the finite section, the density is distributed on a road by the dispersion model. In addition, the dynamic evolution of the traffic flow is determined by the systematic gas-kinetic model derived from the Boltzmann equation. Multiplying Boltzmann equation by the zeroth, first- and second-order moment functions, integrating both side of the equation and using chain rules, we can derive continuity, motion and variance equation, respectively. However, the second-order moment function, which is the square of the individual velocity, is employed by previous researches does not have physical meaning in traffic flow. Although the second-order expansion results in the velocity variance equation, additional terms may be generated. The velocity variance equation we propose is derived from multiplying Boltzmann equation by the individual velocity variance. It modifies the previous model and presents a new gas-kinetic traffic flow model. By coupling the gas-kinetic model and the dispersion model, a self-consistent system is presented.

Modeling the Environmental Impact of Air Traffic Operations

Science.gov (United States)

Chen, Neil

2011-01-01

There is increased interest to understand and mitigate the impacts of air traffic on the climate, since greenhouse gases, nitrogen oxides, and contrails generated by air traffic can have adverse impacts on the climate. The models described in this presentation are useful for quantifying these impacts and for studying alternative environmentally aware operational concepts. These models have been developed by leveraging and building upon existing simulation and optimization techniques developed for the design of efficient traffic flow management strategies. Specific enhancements to the existing simulation and optimization techniques include new models that simulate aircraft fuel flow, emissions and contrails. To ensure that these new models are beneficial to the larger climate research community, the outputs of these new models are compatible with existing global climate modeling tools like the FAA's Aviation Environmental Design Tool.

Modelling the effects of road traffic safety measures.

Science.gov (United States)

Lu, Meng

2006-05-01

A model is presented for assessing the effects of traffic safety measures, based on a breakdown of the process in underlying components of traffic safety (risk and consequence), and five (speed and conflict related) variables that influence these components, and are influenced by traffic safety measures. The relationships between measures, variables and components are modelled as coefficients. The focus is on probabilities rather than historical statistics, although in practice statistics may be needed to find values for the coefficients. The model may in general contribute to improve insight in the mechanisms between traffic safety measures and their safety effects. More specifically it allows comparative analysis of different types of measures by defining an effectiveness index, based on the coefficients. This index can be used to estimate absolute effects of advanced driver assistance systems (ADAS) related measures from absolute effects of substitutional (in terms of safety effects) infrastructure measures.

Video modeling by experts with video feedback to enhance gymnastics skills.

Science.gov (United States)

Boyer, Eva; Miltenberger, Raymond G; Batsche, Catherine; Fogel, Victoria

2009-01-01

The effects of combining video modeling by experts with video feedback were analyzed with 4 female competitive gymnasts (7 to 10 years old) in a multiple baseline design across behaviors. During the intervention, after the gymnast performed a specific gymnastics skill, she viewed a video segment showing an expert gymnast performing the same skill and then viewed a video replay of her own performance of the skill. The results showed that all gymnasts demonstrated improved performance across three gymnastics skills following exposure to the intervention.

A Sarsa(λ)-based control model for real-time traffic light coordination.

Science.gov (United States)

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

A Sarsa(λ-Based Control Model for Real-Time Traffic Light Coordination

Directory of Open Access Journals (Sweden)

Xiaoke Zhou

2014-01-01

Full Text Available Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Modeling Spatially Unrestricted Pedestrian Traffic on Footbridges

DEFF Research Database (Denmark)

Zivanovic, Stana; Pavic, Aleksandar; Ingólfsson, Einar Thór

2010-01-01

restricted movement of pedestrians, has kept attracting attention of researchers. However, it is the normal spatially unrestricted pedestrian traffic, and its vertical dynamic loading component, that are most relevant for vibration serviceability checks for most footbridges. Despite the existence of numerous...... design procedures concerned with this loading, the current confidence in its modelling is low due to lack of verification of the models on as-built structures. This is the motivation behind reviewing the existing design procedures for modelling normal pedestrian traffic in this paper and evaluating...

Modelling of road traffic for traffic flow optimization of modern regional center as an example of Odessa

Directory of Open Access Journals (Sweden)

S.V. Myronenko

2016-12-01

Full Text Available At present sharply there is a problem of traffic management especially in big cities. The increase in the number of vehicles, both personal and public, led to congestion of city roads, many hours of traffic jams, difficulty of movement of pedestrians, increase the number of accidents, etc. Aim: The aim of the study is to evaluate the possibility of using simulation models to solve problems of analysis and optimization of traffic flows. To achieve this goal in a simulation environment the data base of the transport network will be developed. Materials and Methods: The problem of analysis and optimization of traffic flow is considered by the example of the city of Odessa (Ukraine, the results and recommendations can be easily adapted for other cities of Ukraine, and for the cities of most countries of the former socialist bloc. Features of transport systems make it impossible to build an adequate analytical model to explore options for the management of the system and its characteristic in different conditions. At the same time simulation modelling as a method to study such objects is a promising for the solution to this problem. As a simulation environment an OmniTRANS package as a universal tool for modeling of discrete, continuous and hybrid systems. Results: With OmniTRANS programs the model of traffic in Odessa was derived and the intensity of the traffic flow. B first approximation the transport network of the central district of the city was considered and built; without calibration and simulation it was developed a database of elements of the transport network and shown how it can be used to solve problems of analysis and optimization of traffic flows. Models constructed from elements of created database, allows you to change the level of detail of the simulated objects and phenomena, thereby obtaining models as macro and micro level.

Simulation of Road Traffic Applying Model-Driven Engineering

Directory of Open Access Journals (Sweden)

Alberto FERNÁNDEZ-ISABEL

2016-05-01

Full Text Available Road traffic is an important phenomenon in modern societies. The study of its different aspects in the multiple scenarios where it happens is relevant for a huge number of problems. At the same time, its scale and complexity make it hard to study. Traffic simulations can alleviate these difficulties, simplifying the scenarios to consider and controlling their variables. However, their development also presents difficulties. The main ones come from the need to integrate the way of working of researchers and developers from multiple fields. Model-Driven Engineering (MDE addresses these problems using Modelling Languages (MLs and semi-automatic transformations to organise and describe the development, from requirements to code. This paper presents a domain-specific MDE framework for simulations of road traffic. It comprises an extensible ML, support tools, and development guidelines. The ML adopts an agent-based approach, which is focused on the roles of individuals in road traffic and their decision-making. A case study shows the process to model a traffic theory with the ML, and how to specialise that specification for an existing target platform and its simulations. The results are the basis for comparison with related work.

Geographic Video 3d Data Model And Retrieval

Science.gov (United States)

Han, Z.; Cui, C.; Kong, Y.; Wu, H.

2014-04-01

Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today's video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

Applicability of models to estimate traffic noise for urban roads.

Science.gov (United States)

Melo, Ricardo A; Pimentel, Roberto L; Lacerda, Diego M; Silva, Wekisley M

2015-01-01

Traffic noise is a highly relevant environmental impact in cities. Models to estimate traffic noise, in turn, can be useful tools to guide mitigation measures. In this paper, the applicability of models to estimate noise levels produced by a continuous flow of vehicles on urban roads is investigated. The aim is to identify which models are more appropriate to estimate traffic noise in urban areas since several models available were conceived to estimate noise from highway traffic. First, measurements of traffic noise, vehicle count and speed were carried out in five arterial urban roads of a brazilian city. Together with geometric measurements of width of lanes and distance from noise meter to lanes, these data were input in several models to estimate traffic noise. The predicted noise levels were then compared to the respective measured counterparts for each road investigated. In addition, a chart showing mean differences in noise between estimations and measurements is presented, to evaluate the overall performance of the models. Measured Leq values varied from 69 to 79 dB(A) for traffic flows varying from 1618 to 5220 vehicles/h. Mean noise level differences between estimations and measurements for all urban roads investigated ranged from -3.5 to 5.5 dB(A). According to the results, deficiencies of some models are discussed while other models are identified as applicable to noise estimations on urban roads in a condition of continuous flow. Key issues to apply such models to urban roads are highlighted.

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.

Selecting salient frames for spatiotemporal video modeling and segmentation.

Science.gov (United States)

Song, Xiaomu; Fan, Guoliang

2007-12-01

We propose a new statistical generative model for spatiotemporal video segmentation. The objective is to partition a video sequence into homogeneous segments that can be used as "building blocks" for semantic video segmentation. The baseline framework is a Gaussian mixture model (GMM)-based video modeling approach that involves a six-dimensional spatiotemporal feature space. Specifically, we introduce the concept of frame saliency to quantify the relevancy of a video frame to the GMM-based spatiotemporal video modeling. This helps us use a small set of salient frames to facilitate the model training by reducing data redundancy and irrelevance. A modified expectation maximization algorithm is developed for simultaneous GMM training and frame saliency estimation, and the frames with the highest saliency values are extracted to refine the GMM estimation for video segmentation. Moreover, it is interesting to find that frame saliency can imply some object behaviors. This makes the proposed method also applicable to other frame-related video analysis tasks, such as key-frame extraction, video skimming, etc. Experiments on real videos demonstrate the effectiveness and efficiency of the proposed method.

Time series modeling in traffic safety research.

Science.gov (United States)

Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

2018-08-01

The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

Can Skype be used beyond video calling?

NARCIS (Netherlands)

Exarchakos, G.; Menkovski, V.; Liotta, A.

2011-01-01

Skype nodes generate a substantial part of real-time bi-directional video traffic nowadays. Employing a range of adaptive mechanisms, the application configures video streaming to meet the requirements of the communication and constraints of the underlying network. While other related works focus on

Evaluating Performances of Traffic Noise Models | Oyedepo ...

African Journals Online (AJOL)

Traffic noise in decibel dB(A) were measured at six locations using 407780A Integrating Sound Level Meter, while spot speed and traffic volume were collected with cine-camera. The predicted sound exposure level (SEL) was evaluated using Burgess, British and FWHA model. The average noise level obtained are 77.64 ...

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.

Models of Weather Impact on Air Traffic

Science.gov (United States)

Kulkarni, Deepak; Wang, Yao

2017-01-01

Flight delays have been a serious problem in the national airspace system costing about $30B per year. About 70 of the delays are attributed to weather and upto two thirds of these are avoidable. Better decision support tools would reduce these delays and improve air traffic management tools. Such tools would benefit from models of weather impacts on the airspace operations. This presentation discusses use of machine learning methods to mine various types of weather and traffic data to develop such models.

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.

Visual Attention Modeling for Stereoscopic Video: A Benchmark and Computational Model.

Science.gov (United States)

Fang, Yuming; Zhang, Chi; Li, Jing; Lei, Jianjun; Perreira Da Silva, Matthieu; Le Callet, Patrick

2017-10-01

In this paper, we investigate the visual attention modeling for stereoscopic video from the following two aspects. First, we build one large-scale eye tracking database as the benchmark of visual attention modeling for stereoscopic video. The database includes 47 video sequences and their corresponding eye fixation data. Second, we propose a novel computational model of visual attention for stereoscopic video based on Gestalt theory. In the proposed model, we extract the low-level features, including luminance, color, texture, and depth, from discrete cosine transform coefficients, which are used to calculate feature contrast for the spatial saliency computation. The temporal saliency is calculated by the motion contrast from the planar and depth motion features in the stereoscopic video sequences. The final saliency is estimated by fusing the spatial and temporal saliency with uncertainty weighting, which is estimated by the laws of proximity, continuity, and common fate in Gestalt theory. Experimental results show that the proposed method outperforms the state-of-the-art stereoscopic video saliency detection models on our built large-scale eye tracking database and one other database (DML-ITRACK-3D).

A cellular automata model of traffic flow with variable probability of randomization

International Nuclear Information System (INIS)

Zheng Wei-Fan; Zhang Ji-Ye

2015-01-01

Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rules of a traffic system. By introducing an interactional potential of vehicles into the randomization step, an improved cellular automata traffic flow model with variable probability of randomization is proposed in this paper. In the proposed model, the driver is affected by the interactional potential of vehicles before him, and his decision-making process is related to the interactional potential. Compared with the traditional cellular automata model, the modeling is more suitable for the driver’s random decision-making process based on the vehicle and traffic situations in front of him in actual traffic. From the improved model, the fundamental diagram (flow–density relationship) is obtained, and the detailed high-density traffic phenomenon is reproduced through numerical simulation. (paper)

Comparison of the Effects of Video Modeling with Narration vs. Video Modeling on the Functional Skill Acquisition of Adolescents with Autism

Science.gov (United States)

Smith, Molly; Ayres, Kevin; Mechling, Linda; Smith, Katie

2013-01-01

The purpose of this study was to compare the effects of two forms of video modeling: video modeling that includes narration (VMN) and video models without narration (VM) on skill acquisition of four adolescent boys with a primary diagnosis of autism enrolled in an Extended School Year (ESY) summer program. An adapted alternating treatment design…

A Multi-Agent Traffic Control Model Based on Distributed System

Directory of Open Access Journals (Sweden)

Qian WU

2014-06-01

Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.

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

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 ...

GIS-based methods for establishing the datafoundation for traffic models

DEFF Research Database (Denmark)

Nielsen, Otto Anker

1997-01-01

Traffic models demand large amounts of data - some of which are: Traffic network topology, traffic network data, zone-data and trip matrices. GIS is a natural tool for handling most of these data as it can ease the work process and improve the quality control. However, traffic models demand a com......-plex topology not very well covered by the traditional GIS-topology. The paper describes a number of applications where ARC/INFO and ArcView have been used to automate the process of building a traffic network topology. The methodology has been used on a number of full-scale models, from medium sized urban...... areas to metropolitan areas (Copenhagen, Denmark and Bandung, Indonesia). The paper covers key subjects in the work process which has been eased considerably by using AML and Avenue scripts or by using the information from ARC/INFO in external applications:· Semi-automatic procedures for attaching zones...

Parameter Estimation for Traffic Noise Models Using a Harmony Search Algorithm

Directory of Open Access Journals (Sweden)

Deok-Soon An

2013-01-01

Full Text Available A technique has been developed for predicting road traffic noise for environmental assessment, taking into account traffic volume as well as road surface conditions. The ASJ model (ASJ Prediction Model for Road Traffic Noise, 1999, which is based on the sound power level of the noise emitted by the interaction between the road surface and tires, employs regression models for two road surface types: dense-graded asphalt (DGA and permeable asphalt (PA. However, these models are not applicable to other types of road surfaces. Accordingly, this paper introduces a parameter estimation procedure for ASJ-based noise prediction models, utilizing a harmony search (HS algorithm. Traffic noise measurement data for four different vehicle types were used in the algorithm to determine the regression parameters for several road surface types. The parameters of the traffic noise prediction models were evaluated using another measurement set, and good agreement was observed between the predicted and measured sound power levels.

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks.

Science.gov (United States)

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN).

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

Science.gov (United States)

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN). PMID:27907113

Particle reduction strategies - PAREST. Evaluation of emission reduction scenarios using chemical transport calculations. Traffic model TREMOD and traffic model TREMOVE. Sub-report

International Nuclear Information System (INIS)

Stern, Rainer

2013-01-01

The calculation of transport emissions in PAREST project is made with traffic model TREMOD 4.17 (Transport Emission Model) used by the Federal Environment Agency based on the emission factors of HBEFA 2.1 (Handbook on Emission Factors for Road Traffic). For the PAREST reference scenario 2010-2020 (CLE scenario, ''current legislation'') TREMOD 4.17 was changed (TREMOD 4.17M) in such way that measures ''Introduction of Euro 5 and 6 limit levels for passenger cars and light commercial vehicles'', ''Introduction of a limit value stage Euro VI for heavy commercial vehicles'' and ''Existing truck tolls including promoting the purchase of low-emission heavy duty vehicles'' are integrated in the reference scenario and are no longer treated as an additional measure (Joerss et al., 2010). As an alternative to TREMOD 4.17M emission data sets were created for the project, in which the traffic emissions were calculated with the TREMOVE, version 2.7 (Kugler et al., 2010). TREMOVE is the traffic model used by the European Commission for the development of traffic scenarios. This report documents the differences between the immission distributions of PM10 and NO 2 , resulting from the application of the European transport model. Considered are the reference 2005, which describes the current state for the year 2005 and the 2020 reference that describes the emission state in 2020 to be achieved. [de

Development of a forecast model for global air traffic emissions

Energy Technology Data Exchange (ETDEWEB)

Schaefer, Martin

2012-07-01

The thesis describes the methodology and results of a simulation model that quantifies fuel consumption and emissions of civil air traffic. Besides covering historical emissions, the model aims at forecasting emissions in the medium-term future. For this purpose, simulation models of aircraft and engine types are used in combination with a database of global flight movements and assumptions about traffic growth, fleet rollover and operational aspects. Results from an application of the model include emissions of scheduled air traffic for the years 2000 to 2010 as well as forecasted emissions until the year 2030. In a baseline scenario of the forecast, input assumptions (e.g. traffic growth rates) are in line with predictions by the aircraft industry. Considering the effects of advanced technologies of the short-term and medium-term future, the forecast focusses on fuel consumption and emissions of nitric oxides. Calculations for historical air traffic additionally cover emissions of carbon monoxide, unburned hydrocarbons and soot. Results are validated against reference data including studies by the International Civil Aviation Organization (ICAO) and simulation results from international research projects. (orig.)

Modeling of speed distribution for mixed bicycle traffic flow

Directory of Open Access Journals (Sweden)

Cheng Xu

2015-11-01

Full Text Available Speed is a fundamental measure of traffic performance for highway systems. There were lots of results for the speed characteristics of motorized vehicles. In this article, we studied the speed distribution for mixed bicycle traffic which was ignored in the past. Field speed data were collected from Hangzhou, China, under different survey sites, traffic conditions, and percentages of electric bicycle. The statistics results of field data show that the total mean speed of electric bicycles is 17.09 km/h, 3.63 km/h faster and 27.0% higher than that of regular bicycles. Normal, log-normal, gamma, and Weibull distribution models were used for testing speed data. The results of goodness-of-fit hypothesis tests imply that the log-normal and Weibull model can fit the field data very well. Then, the relationships between mean speed and electric bicycle proportions were proposed using linear regression models, and the mean speed for purely electric bicycles or regular bicycles can be obtained. The findings of this article will provide effective help for the safety and traffic management of mixed bicycle traffic.

The racing-game effect: why do video racing games increase risk-taking inclinations?

Science.gov (United States)

Fischer, Peter; Greitemeyer, Tobias; Morton, Thomas; Kastenmüller, Andreas; Postmes, Tom; Frey, Dieter; Kubitzki, Jörg; Odenwälder, Jörg

2009-10-01

The present studies investigated why video racing games increase players' risk-taking inclinations. Four studies reveal that playing video racing games increases risk taking in a subsequent simulated road traffic situation, as well as risk-promoting cognitions and emotions, blood pressure, sensation seeking, and attitudes toward reckless driving. Study 1 ruled out the role of experimental demand in creating such effects. Studies 2 and 3 showed that the effect of playing video racing games on risk taking was partially mediated by changes in self-perceptions as a reckless driver. These effects were evident only when the individual played racing games that reward traffic violations rather than racing games that do not reward traffic violations (Study 3) and when the individual was an active player of such games rather than a passive observer (Study 4). In sum, the results underline the potential negative impact of racing games on traffic safety.

Switching performance of OBS network model under prefetched real traffic

Science.gov (United States)

Huang, Zhenhua; Xu, Du; Lei, Wen

2005-11-01

Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.

Gis-Based Route Finding Using ANT Colony Optimization and Urban Traffic Data from Different Sources

Science.gov (United States)

Davoodi, M.; Mesgari, M. S.

2015-12-01

Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

Learning from Multiple Sources for Video Summarisation

OpenAIRE

Zhu, Xiatian; Loy, Chen Change; Gong, Shaogang

2015-01-01

Many visual surveillance tasks, e.g.video summarisation, is conventionally accomplished through analysing imagerybased features. Relying solely on visual cues for public surveillance video understanding is unreliable, since visual observations obtained from public space CCTV video data are often not sufficiently trustworthy and events of interest can be subtle. On the other hand, non-visual data sources such as weather reports and traffic sensory signals are readily accessible but are not exp...

Analysis of Child-related Road Traffic Accidents in Vietnam

Science.gov (United States)

Vu, Anh Tuan; Nguyen, Dinh Vinh Man

2018-04-01

In recent years, the number of road traffic accidents, fatalities and injuries have been decreasing, but the figures of children road traffic accidents have been increasing in Ho Chi Minh City of Vietnam. This fact strongly calls for implementing effective solutions to improve traffic safety for children by the local government. This paper presents the trends, patterns and causes of road traffic accidents involving children based on the analysis of road traffic accident data over the period 2010-2015 and the video-based observations of road traffic law violations at 15 typical school gates and 10 typical roads. The results could be useful for the city government to formulate solutions to effectively improve traffic safety for children in Ho Chi Minh City and other cities in Vietnam.

Cellular automata model for traffic flow at intersections in internet of vehicles

Science.gov (United States)

Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

2018-03-01

Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

Research on three-phase traffic flow modeling based on interaction range

Science.gov (United States)

Zeng, Jun-Wei; Yang, Xu-Gang; Qian, Yong-Sheng; Wei, Xu-Ting

2017-12-01

On the basis of the multiple velocity difference effect (MVDE) model and under short-range interaction, a new three-phase traffic flow model (S-MVDE) is proposed through careful consideration of the influence of the relationship between the speeds of the two adjacent cars on the running state of the rear car. The random slowing rule in the MVDE model is modified in order to emphasize the influence of vehicle interaction between two vehicles on the probability of vehicles’ deceleration. A single-lane model which without bottleneck structure under periodic boundary conditions is simulated, and it is proved that the traffic flow simulated by S-MVDE model will generate the synchronous flow of three-phase traffic theory. Under the open boundary, the model is expanded by adding an on-ramp, the congestion pattern caused by the bottleneck is simulated at different main road flow rates and on-ramp flow rates, which is compared with the traffic congestion pattern observed by Kerner et al. and it is found that the results are consistent with the congestion characteristics in the three-phase traffic flow theory.

Error Resilient Video Compression Using Behavior Models

Directory of Open Access Journals (Sweden)

Jacco R. Taal

2004-03-01

Full Text Available Wireless and Internet video applications are inherently subjected to bit errors and packet errors, respectively. This is especially so if constraints on the end-to-end compression and transmission latencies are imposed. Therefore, it is necessary to develop methods to optimize the video compression parameters and the rate allocation of these applications that take into account residual channel bit errors. In this paper, we study the behavior of a predictive (interframe video encoder and model the encoders behavior using only the statistics of the original input data and of the underlying channel prone to bit errors. The resulting data-driven behavior models are then used to carry out group-of-pictures partitioning and to control the rate of the video encoder in such a way that the overall quality of the decoded video with compression and channel errors is optimized.

A Bayes Theory-Based Modeling Algorithm to End-to-end Network Traffic

Directory of Open Access Journals (Sweden)

Zhao Hong-hao

2016-01-01

Full Text Available Recently, network traffic has exponentially increasing due to all kind of applications, such as mobile Internet, smart cities, smart transportations, Internet of things, and so on. the end-to-end network traffic becomes more important for traffic engineering. Usually end-to-end traffic estimation is highly difficult. This paper proposes a Bayes theory-based method to model the end-to-end network traffic. Firstly, the end-to-end network traffic is described as a independent identically distributed normal process. Then the Bases theory is used to characterize the end-to-end network traffic. By calculating the parameters, the model is determined correctly. Simulation results show that our approach is feasible and effective.

Learning from video modeling examples: Does gender matter?

NARCIS (Netherlands)

Hoogerheide, V.; Loyens, S.M.M.; van Gog, T.

2016-01-01

Online learning from video modeling examples, in which a human model demonstrates and explains how to perform a learning task, is an effective instructional method that is increasingly used nowadays. However, model characteristics such as gender tend to differ across videos, and the model-observer

Film grain noise modeling in advanced video coding

Science.gov (United States)

Oh, Byung Tae; Kuo, C.-C. Jay; Sun, Shijun; Lei, Shawmin

2007-01-01

A new technique for film grain noise extraction, modeling and synthesis is proposed and applied to the coding of high definition video in this work. The film grain noise is viewed as a part of artistic presentation by people in the movie industry. On one hand, since the film grain noise can boost the natural appearance of pictures in high definition video, it should be preserved in high-fidelity video processing systems. On the other hand, video coding with film grain noise is expensive. It is desirable to extract film grain noise from the input video as a pre-processing step at the encoder and re-synthesize the film grain noise and add it back to the decoded video as a post-processing step at the decoder. Under this framework, the coding gain of the denoised video is higher while the quality of the final reconstructed video can still be well preserved. Following this idea, we present a method to remove film grain noise from image/video without distorting its original content. Besides, we describe a parametric model containing a small set of parameters to represent the extracted film grain noise. The proposed model generates the film grain noise that is close to the real one in terms of power spectral density and cross-channel spectral correlation. Experimental results are shown to demonstrate the efficiency of the proposed scheme.

Comparison of five bicycle facility designs in signalized intersections using traffic conflict studies

DEFF Research Database (Denmark)

Madsen, Tanja Kidholm Osmann; Lahrmann, Harry Spaabæk

2017-01-01

Highlights •Traffic conflict study comparing cyclists’ relative risk for five bicycle layouts. •Watchdog video analysis software applied to reduce video data. •Video analysis software necessary to conduct larger conflict studies. •Recessed bicycle track seems to provide the highest safety level...

Uncoordinated Multi-user Video Streaming in VANETs using Skype

DEFF Research Database (Denmark)

Belyaev, Evgeny; Moreschini, Sergio; Vinel, Alexey

2017-01-01

Real-time video delivery in Vehicle-to-Infrastructure (V2I) scenario enables a variety of multimedia vehicular services. We conduct experiments with Dedicated Short Range Communications (DSRC) transceivers located in the mutual proximity and exchanging Skype video calls traffic. We demonstrate...

Wave dynamics in an extended macroscopic traffic flow model with periodic boundaries

Science.gov (United States)

Wang, Yu-Qing; Chu, Xing-Jian; Zhou, Chao-Fan; Yan, Bo-Wen; Jia, Bin; Fang, Chen-Hao

2018-06-01

Motivated by the previous traffic flow model considering the real-time traffic state, a modified macroscopic traffic flow model is established. The periodic boundary condition is applied to the car-following model. Besides, the traffic state factor R is defined in order to correct the real traffic conditions in a more reasonable way. It is a key step that we introduce the relaxation time as a density-dependent function and provide corresponding evolvement of traffic flow. Three different typical initial densities, namely the high density, the medium one and the low one, are intensively investigated. It can be found that the hysteresis loop exists in the proposed periodic-boundary system. Furthermore, the linear and nonlinear stability analyses are performed in order to test the robustness of the system.

Intelligent Model for Video Survillance Security System

Directory of Open Access Journals (Sweden)

J. Vidhya

2013-12-01

Full Text Available Video surveillance system senses and trails out all the threatening issues in the real time environment. It prevents from security threats with the help of visual devices which gather the information related to videos like CCTV’S and IP (Internet Protocol cameras. Video surveillance system has become a key for addressing problems in the public security. They are mostly deployed on the IP based network. So, all the possible security threats exist in the IP based application might also be the threats available for the reliable application which is available for video surveillance. In result, it may increase cybercrime, illegal video access, mishandling videos and so on. Hence, in this paper an intelligent model is used to propose security for video surveillance system which ensures safety and it provides secured access on video.

Web-video-mining-supported workflow modeling for laparoscopic surgeries.

Science.gov (United States)

Liu, Rui; Zhang, Xiaoli; Zhang, Hao

2016-11-01

As quality assurance is of strong concern in advanced surgeries, intelligent surgical systems are expected to have knowledge such as the knowledge of the surgical workflow model (SWM) to support their intuitive cooperation with surgeons. For generating a robust and reliable SWM, a large amount of training data is required. However, training data collected by physically recording surgery operations is often limited and data collection is time-consuming and labor-intensive, severely influencing knowledge scalability of the surgical systems. The objective of this research is to solve the knowledge scalability problem in surgical workflow modeling with a low cost and labor efficient way. A novel web-video-mining-supported surgical workflow modeling (webSWM) method is developed. A novel video quality analysis method based on topic analysis and sentiment analysis techniques is developed to select high-quality videos from abundant and noisy web videos. A statistical learning method is then used to build the workflow model based on the selected videos. To test the effectiveness of the webSWM method, 250 web videos were mined to generate a surgical workflow for the robotic cholecystectomy surgery. The generated workflow was evaluated by 4 web-retrieved videos and 4 operation-room-recorded videos, respectively. The evaluation results (video selection consistency n-index ≥0.60; surgical workflow matching degree ≥0.84) proved the effectiveness of the webSWM method in generating robust and reliable SWM knowledge by mining web videos. With the webSWM method, abundant web videos were selected and a reliable SWM was modeled in a short time with low labor cost. Satisfied performances in mining web videos and learning surgery-related knowledge show that the webSWM method is promising in scaling knowledge for intelligent surgical systems. Copyright © 2016 Elsevier B.V. All rights reserved.

MODELS OF AIR TRAFFIC CONTROLLERS ERRORS PREVENTION IN TERMINAL CONTROL AREAS UNDER UNCERTAINTY CONDITIONS

Directory of Open Access Journals (Sweden)

Volodymyr Kharchenko

2017-03-01

Full Text Available Purpose: the aim of this study is to research applied models of air traffic controllers’ errors prevention in terminal control areas (TMA under uncertainty conditions. In this work the theoretical framework descripting safety events and errors of air traffic controllers connected with the operations in TMA is proposed. Methods: optimisation of terminal control area formal description based on the Threat and Error management model and the TMA network model of air traffic flows. Results: the human factors variables associated with safety events in work of air traffic controllers under uncertainty conditions were obtained. The Threat and Error management model application principles to air traffic controller operations and the TMA network model of air traffic flows were proposed. Discussion: Information processing context for preventing air traffic controller errors, examples of threats in work of air traffic controllers, which are relevant for TMA operations under uncertainty conditions.

Macroscopic models for traffic safety.

NARCIS (Netherlands)

Oppe, S.

1988-01-01

Recently there has been an increased interest in the application of macroscopic models for the description of developments in traffic safety. A discussion was started on the causes of the sudden decrease in the number of fatal and injury accidents after 1974. Before that time these numbers had

Learning from Video Modeling Examples: Does Gender Matter?

Science.gov (United States)

Hoogerheide, Vincent; Loyens, Sofie M. M.; van Gog, Tamara

2016-01-01

Online learning from video modeling examples, in which a human model demonstrates and explains how to perform a learning task, is an effective instructional method that is increasingly used nowadays. However, model characteristics such as gender tend to differ across videos, and the model-observer similarity hypothesis suggests that such…

Learning from video modeling examples: does gender matter?

NARCIS (Netherlands)

V. Hoogerheide (Vincent); S.M.M. Loyens (Sofie); T.A.J.M. van Gog (Tamara)

2016-01-01

textabstractOnline learning from video modeling examples, in which a human model demonstrates and explains how to perform a learning task, is an effective instructional method that is increasingly used nowadays. However, model characteristics such as gender tend to differ across videos, and the

A critical review of principal traffic noise models: Strategies and implications

Energy Technology Data Exchange (ETDEWEB)

Garg, Naveen, E-mail: ngarg@mail.nplindia.ernet.in [Apex Level Standards and Industrial Metrology Division, CSIR-National Physical Laboratory, New Delhi 110012 (India); Department of Mechanical, Production and Industrial Engineering, Delhi Technological University, Delhi 110042 (India); Maji, Sagar [Department of Mechanical, Production and Industrial Engineering, Delhi Technological University, Delhi 110042 (India)

2014-04-01

The paper presents an exhaustive comparison of principal traffic noise models adopted in recent years in developed nations. The comparison is drawn on the basis of technical attributes including source modelling and sound propagation algorithms. Although the characterization of source in terms of rolling and propulsion noise in conjunction with advanced numerical methods for sound propagation has significantly reduced the uncertainty in traffic noise predictions, the approach followed is quite complex and requires specialized mathematical skills for predictions which is sometimes quite cumbersome for town planners. Also, it is sometimes difficult to follow the best approach when a variety of solutions have been proposed. This paper critically reviews all these aspects pertaining to the recent models developed and adapted in some countries and also discusses the strategies followed and implications of these models. - Highlights: • Principal traffic noise models developed are reviewed. • Sound propagation algorithms used in traffic noise models are compared. • Implications of models are discussed.

Learning to Swim Using Video Modelling and Video Feedback within a Self-Management Program

Science.gov (United States)

Lao, So-An; Furlonger, Brett E.; Moore, Dennis W.; Busacca, Margherita

2016-01-01

Although many adults who cannot swim are primarily interested in learning by direct coaching there are options that have a focus on self-directed learning. As an alternative a self-management program combined with video modelling, video feedback and high quality and affordable video technology was used to assess its effectiveness to assisting an…

Aircraft/Air Traffic Management Functional Analysis Model: Technical Description. 2.0

Science.gov (United States)

Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

1998-01-01

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.

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.

Nonlinear analysis of an extended traffic flow model in ITS environment

Energy Technology Data Exchange (ETDEWEB)

Yu Lei [College of Automation, Northwestern Polytechnical University, Xi' an, Shaanxi 710072 (China)], E-mail: yuleijk@126.com; Shi Zhongke [College of Automation, Northwestern Polytechnical University, Xi' an, Shaanxi 710072 (China)

2008-05-15

An extended traffic flow model is proposed by introducing the relative velocity of arbitrary number of cars that precede and that follow into the Newell-Whitham-type car-following model. The stability condition of this model is obtained by using the linear stability theory. The results show that the stability of traffic flow is improved by taking into account the relative velocity of cars ahead and backward. By applying the nonlinear analysis the modified Korteweg-de Vries (mKdV) equation is derived to describe the traffic behavior near the critical point. The kink-antikink soliton, the solution of the mKdV equation, is obtained to describe the traffic jams. From the numerical simulation, it is shown that the traffic jams are suppressed efficiently by taking into account the relative velocity of cars ahead and backward. The analytical results are consistent with the simulation one.

Nonlinear analysis of an extended traffic flow model in ITS environment

International Nuclear Information System (INIS)

Yu Lei; Shi Zhongke

2008-01-01

An extended traffic flow model is proposed by introducing the relative velocity of arbitrary number of cars that precede and that follow into the Newell-Whitham-type car-following model. The stability condition of this model is obtained by using the linear stability theory. The results show that the stability of traffic flow is improved by taking into account the relative velocity of cars ahead and backward. By applying the nonlinear analysis the modified Korteweg-de Vries (mKdV) equation is derived to describe the traffic behavior near the critical point. The kink-antikink soliton, the solution of the mKdV equation, is obtained to describe the traffic jams. From the numerical simulation, it is shown that the traffic jams are suppressed efficiently by taking into account the relative velocity of cars ahead and backward. The analytical results are consistent with the simulation one

Engineering modeling of traffic noise in shielded areas in cities.

Science.gov (United States)

Salomons, Erik M; Polinder, Henk; Lohman, Walter J A; Zhou, Han; Borst, Hieronymous C; Miedema, Henk M E

2009-11-01

A computational study of road traffic noise in cities is presented. Based on numerical boundary-element calculations of canyon-to-canyon propagation, an efficient engineering algorithm is developed to calculate the effect of multiple reflections in street canyons. The algorithm is supported by a room-acoustical analysis of the reverberant sound fields in the source and receiver canyons. Using the algorithm, a simple model for traffic noise in cities is developed. Noise maps and exposure distributions of the city of Amsterdam are calculated with the model, and for comparison also with an engineering model that is currently used for traffic noise impact assessments in cities. Considerable differences between the two model predictions are found for shielded buildings with day-evening-night levels of 40-60 dB at the facades. Further, an analysis is presented of level differences between the most and the least exposed facades of buildings. Large level differences are found for buildings directly exposed to traffic noise from nearby roads. It is shown that by a redistribution of traffic flow around these buildings, one can achieve low sound levels at quiet sides and a corresponding reduction in the percentage of highly annoyed inhabitants from typically 23% to 18%.

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.

Nonlinear stability of traffic models and the use of Lyapunov vectors for estimating the traffic state

Science.gov (United States)

Palatella, Luigi; Trevisan, Anna; Rambaldi, Sandro

2013-08-01

Valuable information for estimating the traffic flow is obtained with current GPS technology by monitoring position and velocity of vehicles. In this paper, we present a proof of concept study that shows how the traffic state can be estimated using only partial and noisy data by assimilating them in a dynamical model. Our approach is based on a data assimilation algorithm, developed by the authors for chaotic geophysical models, designed to be equivalent but computationally much less demanding than the traditional extended Kalman filter. Here we show that the algorithm is even more efficient if the system is not chaotic and demonstrate by numerical experiments that an accurate reconstruction of the complete traffic state can be obtained at a very low computational cost by monitoring only a small percentage of vehicles.

GIS-BASED ROUTE FINDING USING ANT COLONY OPTIMIZATION AND URBAN TRAFFIC DATA FROM DIFFERENT SOURCES

Directory of Open Access Journals (Sweden)

M. Davoodi

2015-12-01

Full Text Available Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD, Automatic Number Plate Recognition (ANPR, Floating Car Data (FCD, VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

Distribution of Video-on-Demand Service over Cable Television Networks

Directory of Open Access Journals (Sweden)

L. T. Jordanova

2009-06-01

Full Text Available The paper deals with investigations carried out to increase the effectiveness of video-on-demand (VoD systems when cable television networks are used. A comparative analysis of the existing VoD architectures is made with respect to the equipment cost and the traffic load over the central transport network. Through statistical studies the main characteristics of a particular hybrid VoD are determined (such as twenty-four-hour distribution of the video traffic, average inter-arrival time of the VoD requests, average duration of video streams demanded, movies distribution according to the subscribers’ preferences. An algorithm for the videocontent flexible distribution among the distribution hubs is suggested. Thus a higher effectiveness of the system is achieved without significantly increasing the equipment cost.

A new modelling approach for road traffic emissions: VERSIT+

NARCIS (Netherlands)

Smit, R.; Smokers, R.T.M.; Rabé, E.L.M.

2007-01-01

The objective of VERSIT+ LD is to predict traffic stream emissions for light-duty vehicles in any particular traffic situation. With respect to hot running emissions, VERSIT+ LD consists of a set of statistical models for detailed vehicle categories that have been constructed using multiple linear

Common and Innovative Visuals: A sparsity modeling framework for video.

Science.gov (United States)

Abdolhosseini Moghadam, Abdolreza; Kumar, Mrityunjay; Radha, Hayder

2014-05-02

Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.

Science.gov (United States)

Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing

2015-01-01

Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.

Using Video-Based Modeling to Promote Acquisition of Fundamental Motor Skills

Science.gov (United States)

Obrusnikova, Iva; Rattigan, Peter J.

2016-01-01

Video-based modeling is becoming increasingly popular for teaching fundamental motor skills to children in physical education. Two frequently used video-based instructional strategies that incorporate modeling are video prompting (VP) and video modeling (VM). Both strategies have been used across multiple disciplines and populations to teach a…

Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring

DEFF Research Database (Denmark)

Alldieck, Thiemo; Bahnsen, Chris Holmberg; Moeslund, Thomas B.

2016-01-01

In order to enable a robust 24-h monitoring of traffic under changing environmental conditions, it is beneficial to observe the traffic scene using several sensors, preferably from different modalities. To fully benefit from multi-modal sensor output, however, one must fuse the data. This paper...... introduces a new approach for fusing color RGB and thermal video streams by using not only the information from the videos themselves, but also the available contextual information of a scene. The contextual information is used to judge the quality of a particular modality and guides the fusion of two...

A Bayes Theory-Based Modeling Algorithm to End-to-end Network Traffic

OpenAIRE

Zhao Hong-hao; Meng Fan-bo; Zhao Si-wen; Zhao Si-hang; Lu Yi

2016-01-01

Recently, network traffic has exponentially increasing due to all kind of applications, such as mobile Internet, smart cities, smart transportations, Internet of things, and so on. the end-to-end network traffic becomes more important for traffic engineering. Usually end-to-end traffic estimation is highly difficult. This paper proposes a Bayes theory-based method to model the end-to-end network traffic. Firstly, the end-to-end network traffic is described as a independent identically distrib...

Bi-directional approach for logical traffic isolation forensic model

CSIR Research Space (South Africa)

Dlamini, I

2009-08-01

Full Text Available -it-as-you-can" system, which seizes all packets passing through a certain traffic point, captures and writes them to the storage. The main aim of this paper is to address some of the challenges faced by the Logical Traffic Isolation (LTI) model, more specifically...

Modeling Left-Turn Driving Behavior at Signalized Intersections with Mixed Traffic Conditions

Directory of Open Access Journals (Sweden)

Hong Li

2016-01-01

Full Text Available In many developing countries, mixed traffic is the most common type of urban transportation; traffic of this type faces many major problems in traffic engineering, such as conflicts, inefficiency, and security issues. This paper focuses on the traffic engineering concerns on the driving behavior of left-turning vehicles caused by different degrees of pedestrian violations. The traffic characteristics of left-turning vehicles and pedestrians in the affected region at a signalized intersection were analyzed and a cellular-automata-based “following-conflict” driving behavior model that mainly addresses four basic behavior modes was proposed to study the conflict and behavior mechanisms of left-turning vehicles by mathematic methodologies. Four basic driving behavior modes were reproduced in computer simulations, and a logit model of the behavior mode choice was also developed to analyze the relative share of each behavior mode. Finally, the microscopic characteristics of driving behaviors and the macroscopic parameters of traffic flow in the affected region were all determined. These data are important reference for geometry and capacity design for signalized intersections. The simulation results show that the proposed models are valid and can be used to represent the behavior of left-turning vehicles in the case of conflicts with illegally crossing pedestrians. These results will have potential applications on improving traffic safety and traffic capacity at signalized intersections with mixed traffic conditions.

Learning a Continuous-Time Streaming Video QoE Model.

Science.gov (United States)

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C

2018-05-01

Over-the-top adaptive video streaming services are frequently impacted by fluctuating network conditions that can lead to rebuffering events (stalling events) and sudden bitrate changes. These events visually impact video consumers' quality of experience (QoE) and can lead to consumer churn. The development of models that can accurately predict viewers' instantaneous subjective QoE under such volatile network conditions could potentially enable the more efficient design of quality-control protocols for media-driven services, such as YouTube, Amazon, Netflix, and so on. However, most existing models only predict a single overall QoE score on a given video and are based on simple global video features, without accounting for relevant aspects of human perception and behavior. We have created a QoE evaluator, called the time-varying QoE Indexer, that accounts for interactions between stalling events, analyzes the spatial and temporal content of a video, predicts the perceptual video quality, models the state of the client-side data buffer, and consequently predicts continuous-time quality scores that agree quite well with human opinion scores. The new QoE predictor also embeds the impact of relevant human cognitive factors, such as memory and recency, and their complex interactions with the video content being viewed. We evaluated the proposed model on three different video databases and attained standout QoE prediction performance.

Teaching Daily Living Skills to Seven Individuals with Severe Intellectual Disabilities: A Comparison of Video Prompting to Video Modeling

Science.gov (United States)

Cannella-Malone, Helen I.; Fleming, Courtney; Chung, Yi-Cheih; Wheeler, Geoffrey M.; Basbagill, Abby R.; Singh, Angella H.

2011-01-01

We conducted a systematic replication of Cannella-Malone et al. by comparing the effects of video prompting to video modeling for teaching seven students with severe disabilities to do laundry and wash dishes. The video prompting and video modeling procedures were counterbalanced across tasks and participants and compared in an alternating…

Strategic Air Traffic Planning Using Eulerian Route Based Modeling and Optimization

Science.gov (United States)

Bombelli, Alessandro

Due to a soaring air travel growth in the last decades, air traffic management has become increasingly challenging. As a consequence, planning tools are being devised to help human decision-makers achieve a better management of air traffic. Planning tools are divided into two categories, strategic and tactical. Strategic planning generally addresses a larger planning domain and is performed days to hours in advance. Tactical planning is more localized and is performed hours to minutes in advance. An aggregate route model for strategic air traffic flow management is presented. It is an Eulerian model, describing the flow between cells of unidirectional point-to-point routes. Aggregate routes are created from flight trajectory data based on similarity measures. Spatial similarity is determined using the Frechet distance. The aggregate routes approximate actual well-traveled traffic patterns. By specifying the model resolution, an appropriate balance between model accuracy and model dimension can be achieved. For a particular planning horizon, during which weather is expected to restrict the flow, a procedure for designing airborne reroutes and augmenting the traffic flow model is developed. The dynamics of the traffic flow on the resulting network take the form of a discrete-time, linear time-invariant system. The traffic flow controls are ground holding, pre-departure rerouting and airborne rerouting. Strategic planning--determining how the controls should be used to modify the future traffic flow when local capacity violations are anticipated--is posed as an integer programming problem of minimizing a weighted sum of flight delays subject to control and capacity constraints. Several tests indicate the effectiveness of the modeling and strategic planning approach. In the final, most challenging, test, strategic planning is demonstrated for the six western-most Centers of the 22-Center national airspace. The planning time horizon is four hours long, and there is

The Effects of Video Game Experience on Computer-Based Air Traffic Controller Specialist, Air Traffic Scenario Test Scores.

Science.gov (United States)

1997-02-01

application with a strong resemblance to a video game , concern has been raised that prior video game experience might have a moderating effect on scores. Much...such as spatial ability. The effects of computer or video game experience on work sample scores have not been systematically investigated. The purpose...of this study was to evaluate the incremental validity of prior video game experience over that of general aptitude as a predictor of work sample test

The Technological Barriers of Using Video Modeling in the Classroom

Science.gov (United States)

Marino, Desha; Myck-Wayne, Janice

2015-01-01

The purpose of this investigation is to identify the technological barriers teachers encounter when attempting to implement video modeling in the classroom. Video modeling is an emerging evidence-based intervention method used with individuals with autism. Research has shown the positive effects video modeling can have on its recipients. Educators…

Dynamic Textures Modeling via Joint Video Dictionary Learning.

Science.gov (United States)

Wei, Xian; Li, Yuanxiang; Shen, Hao; Chen, Fang; Kleinsteuber, Martin; Wang, Zhongfeng

2017-04-06

Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series. Hence, a dynamic scene sequence is represented by an appropriate transition matrix associated with a dictionary. In order to ensure the stability of JVDL, we impose several constraints on such transition matrix and dictionary. The developed framework is able to capture the dynamics of a moving scene by exploring both sparse properties and the temporal correlations of consecutive video frames. Moreover, such learned JVDL parameters can be used for various DT applications, such as DT synthesis and recognition. Experimental results demonstrate the strong competitiveness of the proposed JVDL approach in comparison with state-of-the-art video representation methods. Especially, it performs significantly better in dealing with DT synthesis and recognition on heavily corrupted data.

Hierarchical Context Modeling for Video Event Recognition.

Science.gov (United States)

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Comparing Video Modeling and Graduated Guidance Together and Video Modeling Alone for Teaching Role Playing Skills to Children with Autism

Science.gov (United States)

Akmanoglu, Nurgul; Yanardag, Mehmet; Batu, E. Sema

2014-01-01

Teaching play skills is important for children with autism. The purpose of the present study was to compare effectiveness and efficiency of providing video modeling and graduated guidance together and video modeling alone for teaching role playing skills to children with autism. The study was conducted with four students. The study was conducted…

Macroscopic Model and Simulation Analysis of Air Traffic Flow in Airport Terminal Area

Directory of Open Access Journals (Sweden)

Honghai Zhang

2014-01-01

Full Text Available We focus on the spatiotemporal characteristics and their evolvement law of the air traffic flow in airport terminal area to provide scientific basis for optimizing flight control processes and alleviating severe air traffic conditions. Methods in this work combine mathematical derivation and simulation analysis. Based on cell transmission model the macroscopic models of arrival and departure air traffic flow in terminal area are established. Meanwhile, the interrelationship and influential factors of the three characteristic parameters as traffic flux, density, and velocity are presented. Then according to such models, the macro emergence of traffic flow evolution is emulated with the NetLogo simulation platform, and the correlativity of basic traffic flow parameters is deduced and verified by means of sensitivity analysis. The results suggest that there are remarkable relations among the three characteristic parameters of the air traffic flow in terminal area. Moreover, such relationships evolve distinctly with the flight procedures, control separations, and ATC strategies.

Models, methods and software tools for building complex adaptive traffic systems

International Nuclear Information System (INIS)

Alyushin, S.A.

2011-01-01

The paper studies the modern methods and tools to simulate the behavior of complex adaptive systems (CAS), the existing systems of traffic modeling in simulators and their characteristics; proposes requirements for assessing the suitability of the system to simulate the CAS behavior in simulators. The author has developed a model of adaptive agent representation and its functioning environment to meet certain requirements set above, and has presented methods of agents' interactions and methods of conflict resolution in simulated traffic situations. A simulation system realizing computer modeling for simulating the behavior of CAS in traffic situations has been created [ru

Human recognition in a video network

Science.gov (United States)

Bhanu, Bir

2009-10-01

Video networks is an emerging interdisciplinary field with significant and exciting scientific and technological challenges. It has great promise in solving many real-world problems and enabling a broad range of applications, including smart homes, video surveillance, environment and traffic monitoring, elderly care, intelligent environments, and entertainment in public and private spaces. This paper provides an overview of the design of a wireless video network as an experimental environment, camera selection, hand-off and control, anomaly detection. It addresses challenging questions for individual identification using gait and face at a distance and present new techniques and their comparison for robust identification.

Cellular automata model for urban road traffic flow considering pedestrian crossing street

Science.gov (United States)

Zhao, Han-Tao; Yang, Shuo; Chen, Xiao-Xu

2016-11-01

In order to analyze the effect of pedestrians' crossing street on vehicle flows, we investigated traffic characteristics of vehicles and pedestrians. Based on that, rules of lane changing, acceleration, deceleration, randomization and update are modified. Then we established two urban two-lane cellular automata models of traffic flow, one of which is about sections with non-signalized crosswalk and the other is on uncontrolled sections with pedestrians crossing street at random. MATLAB is used for numerical simulation of the different traffic conditions; meanwhile space-time diagram and relational graphs of traffic flow parameters are generated and then comparatively analyzed. Simulation results indicate that when vehicle density is lower than around 25 vehs/(km lane), pedestrians have modest impact on traffic flow, whereas when vehicle density is higher than about 60 vehs/(km lane), traffic speed and volume will decrease significantly especially on sections with non-signal-controlled crosswalk. The results illustrate that the proposed models reconstruct the traffic flow's characteristic with the situation where there are pedestrians crossing and can provide some practical reference for urban traffic management.

User interface using a 3D model for video surveillance

Science.gov (United States)

Hata, Toshihiko; Boh, Satoru; Tsukada, Akihiro; Ozaki, Minoru

1998-02-01

These days fewer people, who must carry out their tasks quickly and precisely, are required in industrial surveillance and monitoring applications such as plant control or building security. Utilizing multimedia technology is a good approach to meet this need, and we previously developed Media Controller, which is designed for the applications and provides realtime recording and retrieval of digital video data in a distributed environment. In this paper, we propose a user interface for such a distributed video surveillance system in which 3D models of buildings and facilities are connected to the surveillance video. A novel method of synchronizing camera field data with each frame of a video stream is considered. This method records and reads the camera field data similarity to the video data and transmits it synchronously with the video stream. This enables the user interface to have such useful functions as comprehending the camera field immediately and providing clues when visibility is poor, for not only live video but also playback video. We have also implemented and evaluated the display function which makes surveillance video and 3D model work together using Media Controller with Java and Virtual Reality Modeling Language employed for multi-purpose and intranet use of 3D model.

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

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

Modeling pedestrian gap crossing index under mixed traffic condition.

Science.gov (United States)

Naser, Mohamed M; Zulkiple, Adnan; Al Bargi, Walid A; Khalifa, Nasradeen A; Daniel, Basil David

2017-12-01

There are a variety of challenges faced by pedestrians when they walk along and attempt to cross a road, as the most recorded accidents occur during this time. Pedestrians of all types, including both sexes with numerous aging groups, are always subjected to risk and are characterized as the most exposed road users. The increased demand for better traffic management strategies to reduce the risks at intersections, improve quality traffic management, traffic volume, and longer cycle time has further increased concerns over the past decade. This paper aims to develop a sustainable pedestrian gap crossing index model based on traffic flow density. It focusses on the gaps accepted by pedestrians and their decision for street crossing, where (Log-Gap) logarithm of accepted gaps was used to optimize the result of a model for gap crossing behavior. Through a review of extant literature, 15 influential variables were extracted for further empirical analysis. Subsequently, data from the observation at an uncontrolled mid-block in Jalan Ampang in Kuala Lumpur, Malaysia was gathered and Multiple Linear Regression (MLR) and Binary Logit Model (BLM) techniques were employed to analyze the results. From the results, different pedestrian behavioral characteristics were considered for a minimum gap size model, out of which only a few (four) variables could explain the pedestrian road crossing behavior while the remaining variables have an insignificant effect. Among the different variables, age, rolling gap, vehicle type, and crossing were the most influential variables. The study concludes that pedestrians' decision to cross the street depends on the pedestrian age, rolling gap, vehicle type, and size of traffic gap before crossing. The inferences from these models will be useful to increase pedestrian safety and performance evaluation of uncontrolled midblock road crossings in developing countries. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

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.

A comparison of peer video modeling and self video modeling to teach textual responses in children with autism.

Science.gov (United States)

Marcus, Alonna; Wilder, David A

2009-01-01

Peer video modeling was compared to self video modeling to teach 3 children with autism to respond appropriately to (i.e., identify or label) novel letters. A combination multiple baseline and multielement design was used to compare the two procedures. Results showed that all 3 participants met the mastery criterion in the self-modeling condition, whereas only 1 of the participants met the mastery criterion in the peer-modeling condition. In addition, the participant who met the mastery criterion in both conditions reached the criterion more quickly in the self-modeling condition. Results are discussed in terms of their implications for teaching new skills to children with autism.

Learning from video modeling examples : Effects of seeing the human model's face

NARCIS (Netherlands)

Van Gog, Tamara; Verveer, Ilse; Verveer, Lise

2014-01-01

Video modeling examples in which a human(-like) model shows learners how to perform a task are increasingly used in education, as they have become very easy to create and distribute in e-learning environments. However, little is known about design guidelines to optimize learning from video modeling

Integrating Usability Evaluation into Model-Driven Video Game Development

OpenAIRE

Fernandez , Adrian; Insfran , Emilio; Abrahão , Silvia; Carsí , José ,; Montero , Emanuel

2012-01-01

Part 3: Short Papers; International audience; The increasing complexity of video game development highlights the need of design and evaluation methods for enhancing quality and reducing time and cost. In this context, Model-Driven Development approaches seem to be very promising since a video game can be obtained by transforming platform-independent models into platform-specific models that can be in turn transformed into code. Although this approach is started to being used for video game de...

Multi-Agent Based Microscopic Simulation Modeling for Urban Traffic Flow

Directory of Open Access Journals (Sweden)

Xianyan Kuang

2014-10-01

Full Text Available Traffic simulation plays an important role in the evaluation of traffic decisions. The movement of vehicles essentially is the operating process of drivers, in order to reproduce the urban traffic flow from the micro-aspect on computer, this paper establishes an urban traffic flow microscopic simulation system (UTFSim based on multi-agent. The system is seen as an intelligent virtual environment system (IVES, and the four-layer structure of it is built. The road agent, vehicle agent and signal agent are modeled. The concept of driving trajectory which is divided into LDT (Lane Driving Trajectory and VDDT (Vehicle Dynamic Driving Trajectory is introduced. The “Link-Node” road network model is improved. The driving behaviors including free driving, following driving, lane changing, slowing down, vehicle stop, etc. are analyzed. The results of the signal control experiments utilizing the UTFSim developed in the platform of Visual Studio. NET indicates that it plays a good performance and can be used in the evaluation of traffic management and control.

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.

Model petri net of adaptive traffic lights and its collaboration with a special event

Directory of Open Access Journals (Sweden)

Tristono Tomi

2018-01-01

Full Text Available Traffic lights have an important role as the system control of vehicles flow on the urban network. Commonly, most countries still using fixed time strategy. Our research proposes the adaptive traffic lights model to response the traffic demand. It uses basic Petri net as a general modeling framework. Foractuating method of minimum and maximum green signal time interval, the green traffic lights have three-time extension units. Next, we collaborate on a case of the existence of railways that crosses on the southern arm of an intersection. We introduce both of collaboration model design of traffic lights and the railway's gate which always closes while a train passing. Verification and validation of the model are based on the simulation result of vehicles queue. The collaboration model design of traffic lights has excellent performance, and it can resolve the congestion problem better than conventional schedule.

Teaching autistic children conversational speech using video modeling.

Science.gov (United States)

Charlop, M H; Milstein, J P

1989-01-01

We assessed the effects of video modeling on acquisition and generalization of conversational skills among autistic children. Three autistic boys observed videotaped conversations consisting of two people discussing specific toys. When criterion for learning was met, generalization of conversational skills was assessed with untrained topics of conversation; new stimuli (toys); unfamiliar persons, siblings, and autistic peers; and other settings. The results indicated that the children learned through video modeling, generalized their conversational skills, and maintained conversational speech over a 15-month period. Video modeling shows much promise as a rapid and effective procedure for teaching complex verbal skills such as conversational speech. PMID:2793634

Study on network traffic forecast model of SVR optimized by GAFSA

International Nuclear Information System (INIS)

Liu, Yuan; Wang, RuiXue

2016-01-01

There are some problems, such as low precision, on existing network traffic forecast model. In accordance with these problems, this paper proposed the network traffic forecast model of support vector regression (SVR) algorithm optimized by global artificial fish swarm algorithm (GAFSA). GAFSA constitutes an improvement of artificial fish swarm algorithm, which is a swarm intelligence optimization algorithm with a significant effect of optimization. The optimum training parameters used for SVR could be calculated by optimizing chosen parameters, which would make the forecast more accurate. With the optimum training parameters searched by GAFSA algorithm, a model of network traffic forecast, which greatly solved problems of great errors in SVR improved by others intelligent algorithms, could be built with the forecast result approaching stability and the increased forecast precision. The simulation shows that, compared with other models (e.g. GA-SVR, CPSO-SVR), the forecast results of GAFSA-SVR network traffic forecast model is more stable with the precision improved to more than 89%, which plays an important role on instructing network control behavior and analyzing security situation.

An EMD–SARIMA-Based Modeling Approach for Air Traffic Forecasting

Directory of Open Access Journals (Sweden)

Wei Nai

2017-12-01

Full Text Available The ever-increasing air traffic demand in China has brought huge pressure on the planning and management of, and investment in, air terminals as well as airline companies. In this context, accurate and adequate short-term air traffic forecasting is essential for the operations of those entities. In consideration of such a problem, a hybrid air traffic forecasting model based on empirical mode decomposition (EMD and seasonal auto regressive integrated moving average (SARIMA has been proposed in this paper. The model proposed decomposes the original time series into components at first, and models each component with the SARIMA forecasting model, then integrates all the models together to form the final combined forecast result. By using the monthly air cargo and passenger flow data from the years 2006 to 2014 available at the official website of the Civil Aviation Administration of China (CAAC, the effectiveness in forecasting of the model proposed has been demonstrated, and by a horizontal performance comparison between several other widely used forecasting models, the advantage of the proposed model has also been proved.

Modeling secondary accidents identified by traffic shock waves.

Science.gov (United States)

Junhua, Wang; Boya, Liu; Lanfang, Zhang; Ragland, David R

2016-02-01

The high potential for occurrence and the negative consequences of secondary accidents make them an issue of great concern affecting freeway safety. Using accident records from a three-year period together with California interstate freeway loop data, a dynamic method for more accurate classification based on the traffic shock wave detecting method was used to identify secondary accidents. Spatio-temporal gaps between the primary and secondary accident were proven be fit via a mixture of Weibull and normal distribution. A logistic regression model was developed to investigate major factors contributing to secondary accident occurrence. Traffic shock wave speed and volume at the occurrence of a primary accident were explicitly considered in the model, as a secondary accident is defined as an accident that occurs within the spatio-temporal impact scope of the primary accident. Results show that the shock waves originating in the wake of a primary accident have a more significant impact on the likelihood of a secondary accident occurrence than the effects of traffic volume. Primary accidents with long durations can significantly increase the possibility of secondary accidents. Unsafe speed and weather are other factors contributing to secondary crash occurrence. It is strongly suggested that when police or rescue personnel arrive at the scene of an accident, they should not suddenly block, decrease, or unblock the traffic flow, but instead endeavor to control traffic in a smooth and controlled manner. Also it is important to reduce accident processing time to reduce the risk of secondary accident. Copyright © 2015 Elsevier Ltd. All rights reserved.

Traffic simulation based ship collision probability modeling

Energy Technology Data Exchange (ETDEWEB)

Goerlandt, Floris, E-mail: floris.goerlandt@tkk.f [Aalto University, School of Science and Technology, Department of Applied Mechanics, Marine Technology, P.O. Box 15300, FI-00076 AALTO, Espoo (Finland); Kujala, Pentti [Aalto University, School of Science and Technology, Department of Applied Mechanics, Marine Technology, P.O. Box 15300, FI-00076 AALTO, Espoo (Finland)

2011-01-15

Maritime traffic poses various risks in terms of human, environmental and economic loss. In a risk analysis of ship collisions, it is important to get a reasonable estimate for the probability of such accidents and the consequences they lead to. In this paper, a method is proposed to assess the probability of vessels colliding with each other. The method is capable of determining the expected number of accidents, the locations where and the time when they are most likely to occur, while providing input for models concerned with the expected consequences. At the basis of the collision detection algorithm lays an extensive time domain micro-simulation of vessel traffic in the given area. The Monte Carlo simulation technique is applied to obtain a meaningful prediction of the relevant factors of the collision events. Data obtained through the Automatic Identification System is analyzed in detail to obtain realistic input data for the traffic simulation: traffic routes, the number of vessels on each route, the ship departure times, main dimensions and sailing speed. The results obtained by the proposed method for the studied case of the Gulf of Finland are presented, showing reasonable agreement with registered accident and near-miss data.

Analyses of Lattice Traffic Flow Model on a Gradient Highway

International Nuclear Information System (INIS)

Gupta Arvind Kumar; Redhu Poonam; Sharma Sapna

2014-01-01

The optimal current difference lattice hydrodynamic model is extended to investigate the traffic flow dynamics on a unidirectional single lane gradient highway. The effect of slope on uphill/downhill highway is examined through linear stability analysis and shown that the slope significantly affects the stability region on the phase diagram. Using nonlinear stability analysis, the Burgers, Korteweg-deVries (KdV) and modified Korteweg-deVries (mKdV) equations are derived in stable, metastable and unstable region, respectively. The effect of reaction coefficient is examined and concluded that it plays an important role in suppressing the traffic jams on a gradient highway. The theoretical findings have been verified through numerical simulation which confirm that the slope on a gradient highway significantly influence the traffic dynamics and traffic jam can be suppressed efficiently by considering the optimal current difference effect in the new lattice model. (nuclear physics)

Classification and unification of the microscopic deterministic traffic models.

Science.gov (United States)

Yang, Bo; Monterola, Christopher

2015-10-01

We identify a universal mathematical structure in microscopic deterministic traffic models (with identical drivers), and thus we show that all such existing models in the literature, including both the two-phase and three-phase models, can be understood as special cases of a master model by expansion around a set of well-defined ground states. This allows any two traffic models to be properly compared and identified. The three-phase models are characterized by the vanishing of leading orders of expansion within a certain density range, and as an example the popular intelligent driver model is shown to be equivalent to a generalized optimal velocity (OV) model. We also explore the diverse solutions of the generalized OV model that can be important both for understanding human driving behaviors and algorithms for autonomous driverless vehicles.

An evaluation of the production effects of video self-modeling.

Science.gov (United States)

O'Handley, Roderick D; Allen, Keith D

2017-12-01

A multiple baseline across tasks design was used to evaluate the production effects of video self-modeling on three activities of daily living tasks of an adult male with Autism Spectrum Disorder and Intellectual Disability. Results indicated large increases in task accuracy after the production of a self-modeling video for each task, but before the video was viewed by the participant. Results also indicated small increases when the participant was directed to view the same video self-models before being prompted to complete each task. Copyright © 2017 Elsevier Ltd. All rights reserved.

Methods and Algorithms for Detecting Objects in Video Files

Directory of Open Access Journals (Sweden)

Nguyen The Cuong

2018-01-01

Full Text Available Video files are files that store motion pictures and sounds like in real life. In today's world, the need for automated processing of information in video files is increasing. Automated processing of information has a wide range of application including office/home surveillance cameras, traffic control, sports applications, remote object detection, and others. In particular, detection and tracking of object movement in video file plays an important role. This article describes the methods of detecting objects in video files. Today, this problem in the field of computer vision is being studied worldwide.

Simple cellular automaton model for traffic breakdown, highway capacity, and synchronized flow

Science.gov (United States)

Kerner, Boris S.; Klenov, Sergey L.; Schreckenberg, Michael

2011-10-01

We present a simple cellular automaton (CA) model for two-lane roads explaining the physics of traffic breakdown, highway capacity, and synchronized flow. The model consists of the rules “acceleration,” “deceleration,” “randomization,” and “motion” of the Nagel-Schreckenberg CA model as well as “overacceleration through lane changing to the faster lane,” “comparison of vehicle gap with the synchronization gap,” and “speed adaptation within the synchronization gap” of Kerner's three-phase traffic theory. We show that these few rules of the CA model can appropriately simulate fundamental empirical features of traffic breakdown and highway capacity found in traffic data measured over years in different countries, like characteristics of synchronized flow, the existence of the spontaneous and induced breakdowns at the same bottleneck, and associated probabilistic features of traffic breakdown and highway capacity. Single-vehicle data derived in model simulations show that synchronized flow first occurs and then self-maintains due to a spatiotemporal competition between speed adaptation to a slower speed of the preceding vehicle and passing of this slower vehicle. We find that the application of simple dependences of randomization probability and synchronization gap on driving situation allows us to explain the physics of moving synchronized flow patterns and the pinch effect in synchronized flow as observed in real traffic data.

Traffic Multiresolution Modeling and Consistency Analysis of Urban Expressway Based on Asynchronous Integration Strategy

Directory of Open Access Journals (Sweden)

Liyan Zhang

2017-01-01

Full Text Available The paper studies multiresolution traffic flow simulation model of urban expressway. Firstly, compared with two-level hybrid model, three-level multiresolution hybrid model has been chosen. Then, multiresolution simulation framework and integration strategies are introduced. Thirdly, the paper proposes an urban expressway multiresolution traffic simulation model by asynchronous integration strategy based on Set Theory, which includes three submodels: macromodel, mesomodel, and micromodel. After that, the applicable conditions and derivation process of the three submodels are discussed in detail. In addition, in order to simulate and evaluate the multiresolution model, “simple simulation scenario” of North-South Elevated Expressway in Shanghai has been established. The simulation results showed the following. (1 Volume-density relationships of three submodels are unanimous with detector data. (2 When traffic density is high, macromodel has a high precision and smaller error and the dispersion of results is smaller. Compared with macromodel, simulation accuracies of micromodel and mesomodel are lower but errors are bigger. (3 Multiresolution model can simulate characteristics of traffic flow, capture traffic wave, and keep the consistency of traffic state transition. Finally, the results showed that the novel multiresolution model can have higher simulation accuracy and it is feasible and effective in the real traffic simulation scenario.

Oslo traffic study - part 2: quantifying effects of traffic measures using individual exposure modeling

International Nuclear Information System (INIS)

Clench-Aas, J.; Bartonova, A.; Klaeboe, R.; Kolbenstvedt, M.

2000-01-01

In quantifying the benefits of air pollution reduction measures, it is desirable to compare the size of the benefits with the effects of other individual confounding factors such as smoking or passive smoking. The effect of pollution is rarely very large and in order to quantify it, exposure estimating procedures must be as accurate as possible. Dispersion models, run for hourly time intervals and controlled by measurements, are therefore used to provide estimates for specific receptor points. Results of three consecutive cross-sectional investigations in an area of Oslo characterized by heavy traffic are presented. The study was designed to provide repeated information on the effects of traffic diversion measures on the self-reporting of symptoms of reduced health of 1100 adults living in Oslo. The principal source of air pollution in Oslo is vehicular traffic. The primary pollutants of interest are nitrogen dioxide (NO 2 ) and respirable particles (PM 2.5 and PM 10 ). The mean hourly concentration of exposure was estimated at each participant's home by means of a time-dependent finite dispersion model combined with subgrid models to describe the source contribution to the grid concentrations. The study controlled the confounding factors. Using the symptom fatigue, the study illustrates that by controlling the changes in population composition, estimated exposure-effect relationships for health symptoms allow the effect of the studied traffic measures on the population to be evaluated. Since the method is based on individual estimates of exposure to different pollutants, it allows standardizing the exposure to compare effects of different pollutants. The study offers a methodology that is useful in evaluating the benefits of measures by both being able to quantify and compare the effects of different compounds and effects on different population sub-groups. (author)

Constructing Self-Modeling Videos: Procedures and Technology

Science.gov (United States)

Collier-Meek, Melissa A.; Fallon, Lindsay M.; Johnson, Austin H.; Sanetti, Lisa M. H.; Delcampo, Marisa A.

2012-01-01

Although widely recommended, evidence-based interventions are not regularly utilized by school practitioners. Video self-modeling is an effective and efficient evidence-based intervention for a variety of student problem behaviors. However, like many other evidence-based interventions, it is not frequently used in schools. As video creation…

Automatic road traffic safety management system in urban areas

Directory of Open Access Journals (Sweden)

Oskarbski Jacek

2017-01-01

Full Text Available Traffic incidents and accidents contribute to decreasing levels of transport system reliability and safety. Traffic management and emergency systems on the road, using, among others, automatic detection, video surveillance, communication technologies and institutional solutions improve the organization of the work of various departments involved in traffic and safety management. Automation of incident management helps to reduce the time of a rescue operation as well as of the normalization of the flow of traffic after completion of a rescue operation, which also affects the reduction of the risk of secondary accidents and contributes to reducing their severity. The paper presents the possibility of including city traffic departments in the process of incident management. The results of research on the automatic incident detection in cities are also presented.

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

Science.gov (United States)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

A New Macro Model for Traffic Flow on a Highway with Ramps and Numerical Tests

International Nuclear Information System (INIS)

Tang Tieqiao; Huang Haijun; Zhang Ying; Wong, S.C.; Gao Ziyou

2009-01-01

In this paper, we present a new macro model for traffic flow on a highway with ramps based on the existing models. We use the new model to study the effects of on-off-ramp on the main road traffic during the morning rush period and the evening rush period. Numerical tests show that, during the two rush periods, these effects are often different and related to the status of the main road traffic. If the main road traffic flow is uniform, then ramps always produce stop-and-go traffic when the main road density is between two critical values, and ramps have little effect on the main road traffic when the main road density is less than the smaller critical value or greater than the larger critical value. If a small perturbation appears on the main road, ramp may lead to stop-and-go traffic, or relieve or even eliminate the stop-and-go traffic, under different circumstances. These results are consistent with real traffic, which shows that the new model is reasonable.

Video-based real-time on-street parking occupancy detection system

Science.gov (United States)

Bulan, Orhan; Loce, Robert P.; Wu, Wencheng; Wang, YaoRong; Bernal, Edgar A.; Fan, Zhigang

2013-10-01

Urban parking management is receiving significant attention due to its potential to reduce traffic congestion, fuel consumption, and emissions. Real-time parking occupancy detection is a critical component of on-street parking management systems, where occupancy information is relayed to drivers via smart phone apps, radio, Internet, on-road signs, or global positioning system auxiliary signals. Video-based parking occupancy detection systems can provide a cost-effective solution to the sensing task while providing additional functionality for traffic law enforcement and surveillance. We present a video-based on-street parking occupancy detection system that can operate in real time. Our system accounts for the inherent challenges that exist in on-street parking settings, including illumination changes, rain, shadows, occlusions, and camera motion. Our method utilizes several components from video processing and computer vision for motion detection, background subtraction, and vehicle detection. We also present three traffic law enforcement applications: parking angle violation detection, parking boundary violation detection, and exclusion zone violation detection, which can be integrated into the parking occupancy cameras as a value-added option. Our experimental results show that the proposed parking occupancy detection method performs in real-time at 5 frames/s and achieves better than 90% detection accuracy across several days of videos captured in a busy street block under various weather conditions such as sunny, cloudy, and rainy, among others.

An Improved Macro Model of Traffic Flow with the Consideration of Ramps and Numerical Tests

Directory of Open Access Journals (Sweden)

Zhongke Shi

2015-01-01

Full Text Available We present an improved macro model for traffic flow based on the existing models. The equilibrium point equation of the model is obtained. The stop-and-go traffic phenomenon is described in phase plane and the relationship between traffic jams and system instability is clearly shown in the phase plane diagrams. Using the improved model, some traffic phenomena on a highway with ramps are found in this paper. The numerical simulation is carried out to investigate various nonlinear traffic phenomena with a single ramp generated by different initial densities and vehicle generation rates. According to the actual road sections of Xi’an-Baoji highways, the situations of morning peak with several ramps are also analyzed. All these results are consistent with real traffic, which shows that the improved model is reasonable.

Context-based object-of-interest detection for a generic traffic surveillance analysis system

NARCIS (Netherlands)

Bao, X.; Javanbakhti, S.; Zinger, S.; Wijnhoven, R.G.J.; With, de P.H.N.

2014-01-01

We present a new traffic surveillance video analysis system, focusing on building a framework with robust and generic techniques, based on both scene understanding and moving object-of-interest detection. Since traffic surveillance is widely applied, we want to design a single system that can be

Modeling, Identification, Estimation, and Simulation of Urban Traffic Flow in Jakarta and Bandung

Directory of Open Access Journals (Sweden)

Herman Y. Sutarto

2015-06-01

Full Text Available This paper presents an overview of urban traffic flow from the perspective of system theory and stochastic control. The topics of modeling, identification, estimation and simulation techniques are evaluated and validated using actual traffic flow data from the city of Jakarta and Bandung, Indonesia, and synthetic data generated from traffic micro-simulator VISSIM. The results on particle filter (PF based state estimation and Expectation-Maximization (EM based parameter estimation (identification confirm the proposed model gives satisfactory results that capture the variation of urban traffic flow. The combination of the technique and the simulator platform assembles possibility to develop a real-time traffic light controller.  

Video Modeling and Word Identification in Adolescents with Autism Spectrum Disorder

Science.gov (United States)

Morlock, Larissa; Reynolds, Jennifer L.; Fisher, Sycarah; Comer, Ronald J.

2015-01-01

Video modeling involves the learner viewing videos of a model demonstrating a target skill. According to the National Professional Development Center on Autism Spectrum Disorders (2011), video modeling is an evidenced-based intervention for individuals with Autism Spectrum Disorder (ASD) in elementary through middle school. Little research exists…

Video-modelling to improve task completion in a child with autism.

Science.gov (United States)

Rayner, Christopher Stephen

2010-01-01

To evaluate the use of video modelling as an intervention for increasing task completion for individuals with autism who have high support needs. A 12-year-old-boy with autism received video modelling intervention on two routines (unpacking his bag and brushing his teeth). Use of the video modelling intervention led to rapid increases in the percentage of steps performed in the unpacking his bag sequence and these gains generalized to packing his bag prior to departure from school. There was limited success in the use of the video modelling intervention for teaching the participant to brush his teeth. Video modelling can be successfully applied to enhance daily functioning in a classroom environment for students with autism and high support needs.

Modeling connected and autonomous vehicles in heterogeneous traffic flow

Science.gov (United States)

Ye, Lanhang; Yamamoto, Toshiyuki

2018-01-01

The objective of this study was to develop a heterogeneous traffic-flow model to study the possible impact of connected and autonomous vehicles (CAVs) on the traffic flow. Based on a recently proposed two-state safe-speed model (TSM), a two-lane cellular automaton (CA) model was developed, wherein both the CAVs and conventional vehicles were incorporated in the heterogeneous traffic flow. In particular, operation rules for CAVs are established considering the new characteristics of this emerging technology, including autonomous driving through the adaptive cruise control and inter-vehicle connection via short-range communication. Simulations were conducted under various CAV-penetration rates in the heterogeneous flow. The impact of CAVs on the road capacity was numerically investigated. The simulation results indicate that the road capacity increases with an increase in the CAV-penetration rate within the heterogeneous flow. Up to a CAV-penetration rate of 30%, the road capacity increases gradually; the effect of the difference in the CAV capability on the growth rate is insignificant. When the CAV-penetration rate exceeds 30%, the growth rate is largely decided by the capability of the CAV. The greater the capability, the higher the road-capacity growth rate. The relationship between the CAV-penetration rate and the road capacity is numerically analyzed, providing some insights into the possible impact of the CAVs on traffic systems.

Modeling the Short-Term Effect of Traffic and Meteorology on Air Pollution in Turin with Generalized Additive Models

Directory of Open Access Journals (Sweden)

Pancrazio Bertaccini

2012-01-01

Full Text Available Vehicular traffic plays an important role in atmospheric pollution and can be used as one of the key predictors in air-quality forecasting models. The models that can account for the role of traffic are especially valuable in urban areas, where high pollutant concentrations are often observed during particular times of day (rush hour and year (winter. In this paper, we develop a generalized additive models approach to analyze the behavior of concentrations of nitrogen dioxide (NO2, and particulate matter (PM10, collected at the environmental monitoring stations distributed throughout the city of Turin, Italy, from December 2003 to April 2005. We describe nonlinear relationships between predictors and pollutants, that are adjusted for unobserved time-varying confounders. We examine several functional forms for the traffic variable and find that a simple form can often provide adequate modeling power. Our analysis shows that there is a saturation effect of traffic on NO2, while such saturation is less evident in models linking traffic to PM10 behavior, having adjusted for meteorological covariates. Moreover, we consider the proposed models separately by seasons and highlight similarities and differences in the predictors’ partial effects. Finally, we show how forecasting can help in evaluating traffic regulation policies.

Linking spatial and dynamic models for traffic maneuvers

DEFF Research Database (Denmark)

Olderog, Ernst-Rüdiger; Ravn, Anders Peter; Wisniewski, Rafal

2015-01-01

For traffic maneuvers of multiple vehicles on highways we build an abstract spatial and a concrete dynamic model. In the spatial model we show the safety (collision freedom) of lane-change maneuvers. By linking the spatial and dynamic model via suitable refinements of the spatial atoms to distance...

Early Model of Traffic Sign Reminder Based on Neural Network

Directory of Open Access Journals (Sweden)

Budi Rahmani

2012-12-01

Full Text Available Recognizing the traffic signs installed on the streets is one of the requirements of driving on the road. Laxity in driving may result in traffic accident. This paper describes a real-time reminder model, by utilizing a camera that can be installed in a car to capture image of traffic signs, and is processed and later to inform the driver. The extracting feature harnessing the morphological elements (strel is used in this paper. Artificial Neural Networks is used to train the system and to produce a final decision. The result shows that the accuracy in detecting and recognizing the ten types of traffic signs in real-time is 80%.

Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies

Science.gov (United States)

Mason, Rose A.; Ganz, Jennifer B.; Parker, Richard I.; Burke, Mack D.; Camargo, Siglia P.

2012-01-01

Video modeling with other as model (VMO) is a more practical method for implementing video-based modeling techniques, such as video self-modeling, which requires significantly more editing. Despite this, identification of contextual factors such as participant characteristics and targeted outcomes that moderate the effectiveness of VMO has not…

CameraCast: flexible access to remote video sensors

Science.gov (United States)

Kong, Jiantao; Ganev, Ivan; Schwan, Karsten; Widener, Patrick

2007-01-01

New applications like remote surveillance and online environmental or traffic monitoring are making it increasingly important to provide flexible and protected access to remote video sensor devices. Current systems use application-level codes like web-based solutions to provide such access. This requires adherence to user-level APIs provided by such services, access to remote video information through given application-specific service and server topologies, and that the data being captured and distributed is manipulated by third party service codes. CameraCast is a simple, easily used system-level solution to remote video access. It provides a logical device API so that an application can identically operate on local vs. remote video sensor devices, using its own service and server topologies. In addition, the application can take advantage of API enhancements to protect remote video information, using a capability-based model for differential data protection that offers fine grain control over the information made available to specific codes or machines, thereby limiting their ability to violate privacy or security constraints. Experimental evaluations of CameraCast show that the performance of accessing remote video information approximates that of accesses to local devices, given sufficient networking resources. High performance is also attained when protection restrictions are enforced, due to an efficient kernel-level realization of differential data protection.

Design of a logical traffic isolation forensic model

CSIR Research Space (South Africa)

Dlamini, I

2009-07-01

Full Text Available the network, further delaying the transmitted data. This paper extends the work on a forensic model for traffic isolation based on Differentiated Services (DiffServ). This model intends to solve the packet loss problem that can result to insufficient evidence...

Distributed Dynamic Traffic Modeling and Implementation Oriented Different Levels of Induced Travelers

Directory of Open Access Journals (Sweden)

Yan Liu

2015-01-01

Full Text Available In order to respond to the variable state of traffic network in time, a distributed dynamic traffic assignment strategy is proposed which can improve the intelligent traffic management. The proposed dynamic assignment method is based on utility theory and is oriented to different levels of induced users. A distributed model based on the marginal utility is developed which combines the advantages of both decentralized paradigm and traveler preference, so as to provide efficient and robust dynamic traffic assignment solutions under uncertain network conditions. Then, the solution algorithm including subroute update and subroute calculation is proposed. To testify the effectiveness of the proposed model in optimizing traffic network operation and minimizing traveler’s cost on different induced levels, a sequence numerical experiment is conducted. In the experiment, there are two test environments: one is in different network load conditions and the other is in different deployment coverage of local agents. The numerical results show that the proposed model not only can improve the running efficiency of road network but also can significantly decrease the average travel time.

Low Cost Wireless Network Camera Sensors for Traffic Monitoring

Science.gov (United States)

2012-07-01

Many freeways and arterials in major cities in Texas are presently equipped with video detection cameras to : collect data and help in traffic/incident management. In this study, carefully controlled experiments determined : the throughput and output...

Efficient Use of Video for 3d Modelling of Cultural Heritage Objects

Science.gov (United States)

Alsadik, B.; Gerke, M.; Vosselman, G.

2015-03-01

Currently, there is a rapid development in the techniques of the automated image based modelling (IBM), especially in advanced structure-from-motion (SFM) and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 - 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

EFFICIENT USE OF VIDEO FOR 3D MODELLING OF CULTURAL HERITAGE OBJECTS

Directory of Open Access Journals (Sweden)

B. Alsadik

2015-03-01

Full Text Available Currently, there is a rapid development in the techniques of the automated image based modelling (IBM, especially in advanced structure-from-motion (SFM and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 – 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO

Directory of Open Access Journals (Sweden)

Lixin Yan

2016-07-01

Full Text Available The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1 the Markov blanket (MB algorithm is employed to extract the main factors associated with hazardous traffic events; (2 a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle’s speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G have significant influences on hazardous traffic events. The sequential minimal optimization (SMO algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles.

Occupational Therapy and Video Modeling for Children with Autism

Science.gov (United States)

Becker, Emily Ann; Watry-Christian, Meghan; Simmons, Amanda; Van Eperen, Ashleigh

2016-01-01

This review explores the evidence in support of using video modeling for teaching children with autism. The process of implementing video modeling, the use of various perspectives, and a wide range of target skills are addressed. Additionally, several helpful clinician resources including handheld device applications, books, and websites are…

Cellular automata model for traffic flow with safe driving conditions

International Nuclear Information System (INIS)

Lárraga María Elena; Alvarez-Icaza Luis

2014-01-01

In this paper, a recently introduced cellular automata (CA) model is used for a statistical analysis of the inner microscopic structure of synchronized traffic flow. The analysis focuses on the formation and dissolution of clusters or platoons of vehicles, as the mechanism that causes the presence of this synchronized traffic state with a high flow. This platoon formation is one of the most interesting phenomena observed in traffic flows and plays an important role both in manual and automated highway systems (AHS). Simulation results, obtained from a single-lane system under periodic boundary conditions indicate that in the density region where the synchronized state is observed, most vehicles travel together in platoons with approximately the same speed and small spatial distances. The examination of velocity variations and individual vehicle gaps shows that the flow corresponding to the synchronized state is stable, safe and highly correlated. Moreover, results indicate that the observed platoon formation in real traffic is reproduced in simulations by the relation between vehicle headway and velocity that is embedded in the dynamics definition of the CA model. (general)

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.

A Study on the Model of Traffic Flow and Vehicle Exhaust Emission

Directory of Open Access Journals (Sweden)

Han Xue

2013-01-01

Full Text Available The increase of traffic flow in cities causes traffic congestion and accidents as well as air pollution. Traffic problems have attracted the interest of many researchers from the perspective of theory and engineering. In order to provide a simple and practical method for measuring the exhaust emission and assessing the effect of pollution control, a model is based on the relationship between traffic flow and vehicle exhaust emission under a certain level of road capacity constraints. In the proposed model, the hydrocarbons (HC, carbon monoxide (CO, and nitrogen oxides (NOx are considered as the indexes of total exhaust emission, and the speed is used as an intermediate variable. To verify the rationality and practicality of the model, a case study for Beijing, China, is provided in which the effects of taxi fare regulation and the specific vehicle emission reduction policy are analyzed.

The Racing-Game Effect : Why Do Video Racing Games Increase Risk-Taking Inclinations?

NARCIS (Netherlands)

Fischer, Peter; Greitemeyer, Tobias; Morton, Thomas; Kastenmueller, Andreas; Postmes, Tom; Frey, Dieter; Kubitzki, Joerg; Odenwaelder, Joerg; Kastenmüller, A.; Odenwälder, J.

2009-01-01

The present studies investigated why video racing games increase players' risk-taking inclinations. Four studies reveal that playing video racing games increases risk taking in a subsequent simulated road traffic situation, as well as risk-promoting cognitions and emotions, blood pressure, sensation

High efficiency video coding (HEVC) algorithms and architectures

CERN Document Server

Budagavi, Madhukar; Sullivan, Gary

2014-01-01

This book provides developers, engineers, researchers and students with detailed knowledge about the High Efficiency Video Coding (HEVC) standard. HEVC is the successor to the widely successful H.264/AVC video compression standard, and it provides around twice as much compression as H.264/AVC for the same level of quality. The applications for HEVC will not only cover the space of the well-known current uses and capabilities of digital video – they will also include the deployment of new services and the delivery of enhanced video quality, such as ultra-high-definition television (UHDTV) and video with higher dynamic range, wider range of representable color, and greater representation precision than what is typically found today. HEVC is the next major generation of video coding design – a flexible, reliable and robust solution that will support the next decade of video applications and ease the burden of video on world-wide network traffic. This book provides a detailed explanation of the various parts ...

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.

Continuity-Aware Scheduling Algorithm for Scalable Video Streaming

Directory of Open Access Journals (Sweden)

Atinat Palawan

2016-05-01

Full Text Available The consumer demand for retrieving and delivering visual content through consumer electronic devices has increased rapidly in recent years. The quality of video in packet networks is susceptible to certain traffic characteristics: average bandwidth availability, loss, delay and delay variation (jitter. This paper presents a scheduling algorithm that modifies the stream of scalable video to combat jitter. The algorithm provides unequal look-ahead by safeguarding the base layer (without the need for overhead of the scalable video. The results of the experiments show that our scheduling algorithm reduces the number of frames with a violated deadline and significantly improves the continuity of the video stream without compromising the average Y Peek Signal-to-Noise Ratio (PSNR.

DASH-based network performance-aware solution for personalised video delivery systems

OpenAIRE

Rovcanin, Lejla

2016-01-01

Video content is an increasingly prevalent contributor of Internet traffic. The proliferation of available video content has been fuelled by both Internet expansion and the growing power and affordability of viewing devices. Such content can be consumed anywhere and anytime, using a variety of technologies. The high data rates required for streaming video content and the large volume of requests for such content degrade network performance when devices compete for finite network bandwidth. Th...

Development of Seasonal ARIMA Models for Traffic Noise Forecasting

Directory of Open Access Journals (Sweden)

Guarnaccia Claudio

2017-01-01

Full Text Available In this paper, a time series analysis approach is adopted to monitor and predict a traffic noise levels dataset, measured in a site of Messina, Italy. In general, acoustical noise shows a high prediction complexity, since its slope is strongly related to the variability of the sources and to intrinsic randomness. In the analysed site the predominant source is road traffic, that has a periodic and non-stationary behaviour. The study of the time evolution of this hazardous agent is very useful to assess the impact to human health and activities. The time series models adopted in this paper are of the stochastic seasonal ARIMA class; these types of model are based on the strong periodicity registered in the acoustical equivalent levels. The observed periodicity is related to the highly variability of urban traffic in the different days of the week. Three different seasonal ARIMA models are proposed and calibrated on a rich dataset of 800 sound level measurements. The predictive capabilities of these techniques are encouraging. The implemented models show a good forecasting performances in terms of low residuals, i.e. difference between observed and estimated noise values. The residuals are analysed by means of statistical indexes, plots and tests.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

Science.gov (United States)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

System and Analysis for Low Latency Video Processing using Microservices

OpenAIRE

VASUKI BALASUBRAMANIAM, KARTHIKEYAN

2017-01-01

The evolution of big data processing and analysis has led to data-parallel frameworks such as Hadoop, MapReduce, Spark, and Hive, which are capable of analyzing large streams of data such as server logs, web transactions, and user reviews. Videos are one of the biggest sources of data and dominate the Internet traffic. Video processing on a large scale is critical and challenging as videos possess spatial and temporal features, which are not taken into account by the existing data-parallel fr...

An extended car-following model considering the acceleration derivative in some typical traffic environments

Science.gov (United States)

Zhou, Tong; Chen, Dong; Liu, Weining

2018-03-01

Based on the full velocity difference and acceleration car-following model, an extended car-following model is proposed by considering the vehicle’s acceleration derivative. The stability condition is given by applying the control theory. Considering some typical traffic environments, the results of theoretical analysis and numerical simulation show the extended model has a more actual acceleration of string vehicles than that of the previous models in starting process, stopping process and sudden brake. Meanwhile, the traffic jams more easily occur when the coefficient of vehicle’s acceleration derivative increases, which is presented by space-time evolution. The results confirm that the vehicle’s acceleration derivative plays an important role in the traffic jamming transition and the evolution of traffic congestion.

Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

Science.gov (United States)

Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

2014-02-01

The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

Non-intrusive Packet-Layer Model for Monitoring Video Quality of IPTV Services

Science.gov (United States)

Yamagishi, Kazuhisa; Hayashi, Takanori

Developing a non-intrusive packet-layer model is required to passively monitor the quality of experience (QoE) during service. We propose a packet-layer model that can be used to estimate the video quality of IPTV using quality parameters derived from transmitted packet headers. The computational load of the model is lighter than that of the model that takes video signals and/or video-related bitstream information such as motion vectors as input. This model is applicable even if the transmitted bitstream information is encrypted because it uses transmitted packet headers rather than bitstream information. For developing the model, we conducted three extensive subjective quality assessments for different encoders and decoders (codecs), and video content. Then, we modeled the subjective video quality assessment characteristics based on objective features affected by coding and packet loss. Finally, we verified the model's validity by applying our model to unknown data sets different from training data sets used above.

Multiobjective Traffic Signal Control Model for Intersection Based on Dynamic Turning Movements Estimation

Directory of Open Access Journals (Sweden)

Pengpeng Jiao

2014-01-01

Full Text Available The real-time traffic signal control for intersection requires dynamic turning movements as the basic input data. It is impossible to detect dynamic turning movements directly through current traffic surveillance systems, but dynamic origin-destination (O-D estimation can obtain it. However, the combined models of dynamic O-D estimation and real-time traffic signal control are rare in the literature. A framework for the multiobjective traffic signal control model for intersection based on dynamic O-D estimation (MSC-DODE is presented. A state-space model using Kalman filtering is first formulated to estimate the dynamic turning movements; then a revised sequential Kalman filtering algorithm is designed to solve the model, and the root mean square error and mean percentage error are used to evaluate the accuracy of estimated dynamic turning proportions. Furthermore, a multiobjective traffic signal control model is put forward to achieve real-time signal control parameters and evaluation indices. Finally, based on practical survey data, the evaluation indices from MSC-DODE are compared with those from Webster method. The actual and estimated turning movements are further input into MSC-DODE, respectively, and results are also compared. Case studies show that results of MSC-DODE are better than those of Webster method and are very close to unavailable actual values.

Video as a Medium for Learning and Teaching

CERN Document Server

CERN. Geneva

2017-01-01

Videos play an important role in today's digital era. According to Cisco®, video (business and consumer combined) was  59% of the total Internet traffic in 2014. Video is permeating our educational institutions, transforming the way we teach, learn, study, communicate and work (Kaltura Report 2015). But are videos always the best choice? In this lecture we examine the benefits of the use of video in learning as well as its limits.Tips on how to minimize those limits will be explained.Example short videos that demonstrate success (or not) stories will be shown.Finally, guidelines for making good videos for education will be given. NB! All Academic Training lectures are recorded but not webcasted. The recording will be linked from this event and the CDS Academic Training collection. Participation is free. No registration needed. Bio: Pedro de Freitas has realized a MSc in learning & teaching technologies and MSc in Psychology in the University of Geneva. His thesis subject ...

Properties of Traffic Risk Coefficient

Science.gov (United States)

Tang, Tie-Qiao; Huang, Hai-Jun; Shang, Hua-Yan; Xue, Yu

2009-10-01

We use the model with the consideration of the traffic interruption probability (Physica A 387(2008)6845) to study the relationship between the traffic risk coefficient and the traffic interruption probability. The analytical and numerical results show that the traffic interruption probability will reduce the traffic risk coefficient and that the reduction is related to the density, which shows that this model can improve traffic security.

Reducing OR Traffic Using Education, Policy Development, and Communication Technology.

Science.gov (United States)

Esser, Jennifer; Shrinski, Keonemana; Cady, Rhonda; Belew, John

2016-01-01

A bundled approach to surgical site infection (SSI) prevention strategies includes reducing OR traffic. A nurse-led quality improvement (QI) team sought to reduce OR traffic through education and a process change that included wireless communication technology and policy development. The team measured OR traffic by counting the frequency of door openings per hour in seven surgical suites during 305 surgical procedures conducted during similar 22-week periods before and after the QI project intervention. Door openings decreased significantly (P < 0.05) from an average of 37.8 per hour to 32.8 per hour after the QI project intervention. This suggests that our multifaceted approach reduces OR traffic. The next steps of this project include analyzing automatically captured video to understand OR traffic patterns and expanding education to departments and external personnel frequently present in our surgical suites. Future research evaluating the effectiveness of this OR traffic initiative on SSI incidence is recommended. Copyright © 2016 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Memory effects in microscopic traffic models and wide scattering in flow-density data

Science.gov (United States)

Treiber, Martin; Helbing, Dirk

2003-10-01

By means of microscopic simulations we show that noninstantaneous adaptation of the driving behavior to the traffic situation together with the conventional method to measure flow-density data provides a possible explanation for the observed inverse-λ shape and the wide scattering of flow-density data in “synchronized” congested traffic. We model a memory effect in the response of drivers to the traffic situation for a wide class of car-following models by introducing an additional dynamical variable (the “subjective level of service”) describing the adaptation of drivers to the surrounding traffic situation during the past few minutes and couple this internal state to parameters of the underlying model that are related to the driving style. For illustration, we use the intelligent-driver model (IDM) as the underlying model, characterize the level of service solely by the velocity, and couple the internal variable to the IDM parameter “time gap” to model an increase of the time gap in congested traffic (“frustration effect”), which is supported by single-vehicle data. We simulate open systems with a bottleneck and obtain flow-density data by implementing “virtual detectors.” The shape, relative size, and apparent “stochasticity” of the region of the scattered data points agree nearly quantitatively with empirical data. Wide scattering is even observed for identical vehicles, although the proposed model is a time-continuous, deterministic, single-lane car-following model with a unique fundamental diagram.

A Framework for Validating Traffic Simulation Models at the Vehicle Trajectory Level

Science.gov (United States)

2017-03-01

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

Retail video analytics: an overview and survey

Science.gov (United States)

Connell, Jonathan; Fan, Quanfu; Gabbur, Prasad; Haas, Norman; Pankanti, Sharath; Trinh, Hoang

2013-03-01

Today retail video analytics has gone beyond the traditional domain of security and loss prevention by providing retailers insightful business intelligence such as store traffic statistics and queue data. Such information allows for enhanced customer experience, optimized store performance, reduced operational costs, and ultimately higher profitability. This paper gives an overview of various camera-based applications in retail as well as the state-ofthe- art computer vision techniques behind them. It also presents some of the promising technical directions for exploration in retail video analytics.

Models and mechanisms of IPTV VоD traffic balancing

OpenAIRE

Klymash, Mykhailo; Hayali, Yasser; Lavriv, Orest

2012-01-01

Models for traffic balancing that enable to evaluate the current IPTV traffic balancing mechanisms are suggested in this paper. Also, an analysis of each of these mechanisms is performed using the IPTV traffic model. Запропоновано моделі балансування трафіку IPTV VoD для оцінки існуючих механізмів балансування. Проведено аналіз кожного з цих механізмів за допомогою моделі IPTV трафіку....

Effects of Video Modeling on Treatment Integrity of Behavioral Interventions

Science.gov (United States)

DiGennaro-Reed, Florence D.; Codding, Robin; Catania, Cynthia N.; Maguire, Helena

2010-01-01

We examined the effects of individualized video modeling on the accurate implementation of behavioral interventions using a multiple baseline design across 3 teachers. During video modeling, treatment integrity improved above baseline levels; however, teacher performance remained variable. The addition of verbal performance feedback increased…

Using Video Modeling and Video Prompting to Teach Core Academic Content to Students with Learning Disabilities

Science.gov (United States)

Kellems, Ryan O.; Edwards, Sean

2016-01-01

Practitioners are constantly searching for evidence-based practices that are effective in teaching academic skills to students with learning disabilities (LD). Video modeling (VM) and video prompting have become popular instructional interventions for many students across a wide range of different disability classifications, including those with…

Traffic flow model at fixed control signals with discrete service time distribution

Directory of Open Access Journals (Sweden)

Lucky I. Igbinosun

2016-04-01

Full Text Available Most of the models of road traffic flow at fixed-cycle controlled intersection assume stationary distributions and provide steady state results. The assumption that a constant number of vehicles can leave the system during the green phase is unrealistic in real life situations. A discrete time queuing model was developed to describe the operation of traffic flow at a road intersection with fixed-cycle signalized control and to account for the randomness in the number of vehicles that can leave the system. The results show the expected queue size in the system when the traffic is light and for a busy period, respectively. For the light period, when the traffic intensity is less than one, it takes a shorter green cycle time for vehicles to clear up than during high traffic intensity (the road junction is saturated. Increasing the number of cars that can leave the junction at the turn of the green phase reduces the number of cycle times before the queue is cleared.

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.

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

Science.gov (United States)

Skene, Katherine J.; Gent, Janneane F.; McKay, Lisa A.; Belanger, Kathleen; Leaderer, Brian P.; Holford, Theodore R.

2010-12-01

An integrated exposure model was developed that estimates nitrogen dioxide (NO 2) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO 2 taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO 2 measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO 2 levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.

Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

Science.gov (United States)

Li, Shu-Bin; Cao, Dan-Ni; Dang, Wen-Xiu; Zhang, Lin

As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.

Modelling the Magnetic Disturbances Due to Road-Traffic

Directory of Open Access Journals (Sweden)

J -J Schott

2011-07-01

Full Text Available Magnetic disturbances due to the traffic are tentatively modelled assuming that the sources are moving dipoles. The influencing section of the road ("useful" portion should be modelled in 3D. The parameters of the model (time of closest position to the magnetometer, velocity, including its sign, dipole moment are fairly accurately estimated. The fit is improved with the incorporation of a small induction effect.

Adherent Raindrop Modeling, Detectionand Removal in Video.

Science.gov (United States)

You, Shaodi; Tan, Robby T; Kawakami, Rei; Mukaigawa, Yasuhiro; Ikeuchi, Katsushi

2016-09-01

Raindrops adhered to a windscreen or window glass can significantly degrade the visibility of a scene. Modeling, detecting and removing raindrops will, therefore, benefit many computer vision applications, particularly outdoor surveillance systems and intelligent vehicle systems. In this paper, a method that automatically detects and removes adherent raindrops is introduced. The core idea is to exploit the local spatio-temporal derivatives of raindrops. To accomplish the idea, we first model adherent raindrops using law of physics, and detect raindrops based on these models in combination with motion and intensity temporal derivatives of the input video. Having detected the raindrops, we remove them and restore the images based on an analysis that some areas of raindrops completely occludes the scene, and some other areas occlude only partially. For partially occluding areas, we restore them by retrieving as much as possible information of the scene, namely, by solving a blending function on the detected partially occluding areas using the temporal intensity derivative. For completely occluding areas, we recover them by using a video completion technique. Experimental results using various real videos show the effectiveness of our method.

A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

Directory of Open Access Journals (Sweden)

Bahadır KARASULU

2013-04-01

Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

Density waves in a lattice hydrodynamic traffic flow model with the anticipation effect

International Nuclear Information System (INIS)

Zhao Min; Sun Di-Hua; Tian Chuan

2012-01-01

By introducing the traffic anticipation effect in the real world into the original lattice hydrodynamic model, we present a new anticipation effect lattice hydrodynamic (AELH) model, and obtain the linear stability condition of the model by applying the linear stability theory. Through nonlinear analysis, we derive the Burgers equation and Korteweg-de Vries (KdV) equation, to describe the propagating behaviour of traffic density waves in the stable and the metastable regions, respectively. The good agreement between simulation results and analytical results shows that the stability of traffic flow can be enhanced when the anticipation effect is considered. (interdisciplinary physics and related areas of science and technology)

Modelling traffic flows with intelligent cars and intelligent roads

NARCIS (Netherlands)

van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

2003-01-01

This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

Pattern-based approach for logical traffic isolation forensic modelling

CSIR Research Space (South Africa)

Dlamini, I

2009-08-01

Full Text Available reusability and flexibility of the LTI model. This model is viewed as a three-tier architecture, which for experimental purposes is composed of the following components: traffic generator, DiffServ network and the sink server. The Mediator pattern is used...

Comparison of Microscopic Drivers' Probabilistic Lane-changing Models With Real Traffic Microscopic Data

Directory of Open Access Journals (Sweden)

Seyyed Mohammad Sadat Hoseini

2011-07-01

Full Text Available The difficulties of microscopic-level simulation models to accurately reproduce real traffic phenomena stem not only from the complexity of calibration and validation operations, but also from the structural inadequacies of the sub-models themselves. Both of these drawbacks originate from the scant information available on real phenomena because of the difficulty in gathering accurate field data. This paper studies the traffic behaviour of individual drivers utilizing vehicle trajectory data extracted from digital images collected from freeways in Iran. These data are used to evaluate the four proposed microscopic traffic models. One of the models is based on the traffic regulations in Iran and the three others are probabilistic models that use a decision factor for calculating the probability of choosing a position on the freeway by a driver. The decision factors for three probabilistic models are increasing speed, decreasing risk of collision, and increasing speed combined with decreasing risk of collision. The models are simulated by a cellular automata simulator and compared with the real data. It is shown that the model based on driving regulations is not valid, but that other models appear useful for predicting the driver’s behaviour on freeway segments in Iran during noncongested conditions.

Rate-control algorithms testing by using video source model

DEFF Research Database (Denmark)

Belyaev, Evgeny; Turlikov, Andrey; Ukhanova, Anna

2008-01-01

In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set.......In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set....

QoS Support Polling Scheme for Multimedia Traffic in Wireless LAN MAC Protocol

Institute of Scientific and Technical Information of China (English)

YANG Zhijun; ZHAO Dongfeng

2008-01-01

Quality of service (QoS) support is a key attribute for multimedia traffic including video, voice, and data in wireless local area networks (LANs) but is limited in 802.11-based wireless LANs. A polling-based scheme called the point coordination function (PCF) was developed for 802.11 LANs to support the trans-mission of multimedia traffic. However, the PCF is not able to meet the desired practical traffic differentiation requirements for real-time data. This paper describes a QoS support polling scheme based on the IEEE 802.11 medium access control (MAC) protocol. The scheme uses a two-level polling mechanism with the QoS classes differentiated by two different access policies. Stations with higher priority traffic such as key or real-time data form the first level and can access the common channel through an exhaustive access policy. Other stations with lower priority traffic form the second level and can access the channel through a gated access policy. A system model based on imbedded Markov chain theory and a generation function were setup to explicitly analyze the mean information packet waiting time of the two-level polling scheme. Theo-retical and simulation results show that the new scheme efficiently differentiates services to guarantee better QoS and system stability.

Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

Science.gov (United States)

Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong

2016-02-01

Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

Bandwidth allocation for video under quality of service constraints

CERN Document Server

Anjum, Bushra

2014-01-01

We present queueing-based algorithms to calculate the bandwidth required for a video stream so that the three main Quality of Service constraints, i.e., end-to-end delay, jitter and packet loss, are ensured. Conversational and streaming video-based applications are becoming a major part of the everyday Internet usage. The quality of these applications (QoS), as experienced by the user, depends on three main metrics of the underlying network, namely, end-to-end delay, jitter and packet loss. These metrics are, in turn, directly related to the capacity of the links that the video traffic trave

Video modeling to train staff to implement discrete-trial instruction.

Science.gov (United States)

Catania, Cynthia N; Almeida, Daniel; Liu-Constant, Brian; DiGennaro Reed, Florence D

2009-01-01

Three new direct-service staff participated in a program that used a video model to train target skills needed to conduct a discrete-trial session. Percentage accuracy in completing a discrete-trial teaching session was evaluated using a multiple baseline design across participants. During baseline, performances ranged from a mean of 12% to 63% accuracy. During video modeling, there was an immediate increase in accuracy to a mean of 98%, 85%, and 94% for each participant. Performance during maintenance and generalization probes remained at high levels. Results suggest that video modeling can be an effective technique to train staff to conduct discrete-trial sessions.

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.

A Continuous Dynamic Traffic Assignment Model From Plate Scanning Technique

Energy Technology Data Exchange (ETDEWEB)

Rivas, A.; Gallego, I.; Sanchez-Cambronero, S.; Ruiz-Ripoll, L.; Barba, R.M.

2016-07-01

This paper presents a methodology for the dynamic estimation of traffic flows on all links of a network from observable field data assuming the first-in-first-out (FIFO) hypothesis. The traffic flow intensities recorded at the exit of the scanned links are propagated to obtain the flow waves on unscanned links. For that, the model calculates the flow-cost functions through information registered with the plate scanning technique. The model also responds to the concern about the parameter quality of flow-cost functions to replicate the real traffic flow behaviour. It includes a new algorithm for the adjustment of the parameter values to link characteristics when its quality is questionable. For that, it is necessary the a priori study of the location of the scanning devices to identify all path flows and to measure travel times in all links. A synthetic network is used to illustrate the proposed method and to prove its usefulness and feasibility. (Author)

The Global Classroom Video Conferencing Model and First Evaluations

DEFF Research Database (Denmark)

Weitze, Charlotte Lærke; Ørngreen, Rikke; Levinsen, Karin

2013-01-01

pedagogical innovativeness, including collaborative and technological issues. The research is based on the Global Classroom Model as it is implemented and used at an adult learning center in Denmark (VUC Storstrøm). VUC Storstrøms (VUC) Global Classroom Model is an approach to video conferencing and e......Learning using campus-based teaching combined with laptop solutions for students at home. After a couple of years of campus-to-campus video streaming, VUC started a fulltime day program in 2011 with the support of a hybrid campus and videoconference model. In this model the teachers and some of the students......This paper presents and discusses findings about how students, teachers, and the organization experience a start-up-project applying video conferences between campus and home. This is new territory for adult learning centers. The paper discusses the transition to this eLearning form and discusses...

Real-time traffic signal optimization model based on average delay time per person

Directory of Open Access Journals (Sweden)

Pengpeng Jiao

2015-10-01

Full Text Available Real-time traffic signal control is very important for relieving urban traffic congestion. Many existing traffic control models were formulated using optimization approach, with the objective functions of minimizing vehicle delay time. To improve people’s trip efficiency, this article aims to minimize delay time per person. Based on the time-varying traffic flow data at intersections, the article first fits curves of accumulative arrival and departure vehicles, as well as the corresponding functions. Moreover, this article transfers vehicle delay time to personal delay time using average passenger load of cars and buses, employs such time as the objective function, and proposes a signal timing optimization model for intersections to achieve real-time signal parameters, including cycle length and green time. This research further implements a case study based on practical data collected at an intersection in Beijing, China. The average delay time per person and queue length are employed as evaluation indices to show the performances of the model. The results show that the proposed methodology is capable of improving traffic efficiency and is very effective for real-world applications.

Sub-component modeling for face image reconstruction in video communications

Science.gov (United States)

Shiell, Derek J.; Xiao, Jing; Katsaggelos, Aggelos K.

2008-08-01

Emerging communications trends point to streaming video as a new form of content delivery. These systems are implemented over wired systems, such as cable or ethernet, and wireless networks, cell phones, and portable game systems. These communications systems require sophisticated methods of compression and error-resilience encoding to enable communications across band-limited and noisy delivery channels. Additionally, the transmitted video data must be of high enough quality to ensure a satisfactory end-user experience. Traditionally, video compression makes use of temporal and spatial coherence to reduce the information required to represent an image. In many communications systems, the communications channel is characterized by a probabilistic model which describes the capacity or fidelity of the channel. The implication is that information is lost or distorted in the channel, and requires concealment on the receiving end. We demonstrate a generative model based transmission scheme to compress human face images in video, which has the advantages of a potentially higher compression ratio, while maintaining robustness to errors and data corruption. This is accomplished by training an offline face model and using the model to reconstruct face images on the receiving end. We propose a sub-component AAM modeling the appearance of sub-facial components individually, and show face reconstruction results under different types of video degradation using a weighted and non-weighted version of the sub-component AAM.

An improved multi-value cellular automata model for heterogeneous bicycle traffic flow

Energy Technology Data Exchange (ETDEWEB)

Jin, Sheng [College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058 China (China); Qu, Xiaobo [Griffith School of Engineering, Griffith University, Gold Coast, 4222 Australia (Australia); Xu, Cheng [Department of Transportation Management Engineering, Zhejiang Police College, Hangzhou, 310053 China (China); College of Transportation, Jilin University, Changchun, 130022 China (China); Ma, Dongfang, E-mail: mdf2004@zju.edu.cn [Ocean College, Zhejiang University, Hangzhou, 310058 China (China); Wang, Dianhai [College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058 China (China)

2015-10-16

This letter develops an improved multi-value cellular automata model for heterogeneous bicycle traffic flow taking the higher maximum speed of electric bicycles into consideration. The update rules of both regular and electric bicycles are improved, with maximum speeds of two and three cells per second respectively. Numerical simulation results for deterministic and stochastic cases are obtained. The fundamental diagrams and multiple states effects under different model parameters are analyzed and discussed. Field observations were made to calibrate the slowdown probabilities. The results imply that the improved extended Burgers cellular automata (IEBCA) model is more consistent with the field observations than previous models and greatly enhances the realism of the bicycle traffic model. - Highlights: • We proposed an improved multi-value CA model with higher maximum speed. • Update rules are introduced for heterogeneous bicycle traffic with maximum speed 2 and 3 cells/s. • Simulation results of the proposed model are consistent with field bicycle data. • Slowdown probabilities of both regular and electric bicycles are calibrated.

An improved multi-value cellular automata model for heterogeneous bicycle traffic flow

International Nuclear Information System (INIS)

Jin, Sheng; Qu, Xiaobo; Xu, Cheng; Ma, Dongfang; Wang, Dianhai

2015-01-01

This letter develops an improved multi-value cellular automata model for heterogeneous bicycle traffic flow taking the higher maximum speed of electric bicycles into consideration. The update rules of both regular and electric bicycles are improved, with maximum speeds of two and three cells per second respectively. Numerical simulation results for deterministic and stochastic cases are obtained. The fundamental diagrams and multiple states effects under different model parameters are analyzed and discussed. Field observations were made to calibrate the slowdown probabilities. The results imply that the improved extended Burgers cellular automata (IEBCA) model is more consistent with the field observations than previous models and greatly enhances the realism of the bicycle traffic model. - Highlights: • We proposed an improved multi-value CA model with higher maximum speed. • Update rules are introduced for heterogeneous bicycle traffic with maximum speed 2 and 3 cells/s. • Simulation results of the proposed model are consistent with field bicycle data. • Slowdown probabilities of both regular and electric bicycles are calibrated

A new lattice model of traffic flow with the consideration of the driver's forecast effects

Energy Technology Data Exchange (ETDEWEB)

Peng, G.H., E-mail: pengguanghan@yahoo.com.cn [College of Physics and Electronic Science, Hunan University of Arts and Science, Changde 415000 (China); Cai, X.H.; Liu, C.Q.; Cao, B.F. [College of Physics and Electronic Science, Hunan University of Arts and Science, Changde 415000 (China)

2011-05-30

In this Letter, a new lattice model is presented with the consideration of the driver's forecast effects (DFE). The linear stability condition of the extended model is obtained by using the linear stability theory. The analytical results show that the new model can improve the stability of traffic flow by considering DFE. The modified KdV equation near the critical point is derived to describe the traffic jam by nonlinear analysis. Numerical simulation also shows that the new model can improve the stability of traffic flow by adjusting the driver's forecast intensity parameter, which is consistent with the theoretical analysis. -- Highlights: → A new driver's forecast lattice model of traffic flow has been presented. → The driver's forecast effects on the stability of traffic flow have been explored. → The modified KdV equation near the critical point is derived to describe the traffic jam by nonlinear analysis. → The analytical and numerical results show that the driver's forecast effect can improve the stability of traffic flow.

Model for Detection and Classification of DDoS Traffic Based on Artificial Neural Network

Directory of Open Access Journals (Sweden)

D. Peraković

2017-06-01

Full Text Available Detection of DDoS (Distributed Denial of Service traffic is of great importance for the availability protection of services and other information and communication resources. The research presented in this paper shows the application of artificial neural networks in the development of detection and classification model for three types of DDoS attacks and legitimate network traffic. Simulation results of developed model showed accuracy of 95.6% in classification of pre-defined classes of traffic.

Identifying traffic accident black spots with Poisson-Tweedie models

DEFF Research Database (Denmark)

Debrabant, Birgit; Halekoh, Ulrich; Bonat, Wagner Hugo

2018-01-01

This paper aims at the identification of black spots for traffic accidents, i.e. locations with accident counts beyond what is usual for similar locations, using spatially and temporally aggregated hospital records from Funen, Denmark. Specifically, we apply an autoregressive Poisson-Tweedie model...... considered calendar years and calculated by simulations a probability of p=0.03 for these to be chance findings. Altogether, our results recommend these sites for further investigation and suggest that our simple approach could play a role in future area based traffic accident prevention planning....

Particle Reduction Strategies - PAREST. Traffic emission modelling. Model comparision and alternative scenarios. Sub-report

International Nuclear Information System (INIS)

Kugler, Ulrike; Theloke, Jochen; Joerss, Wolfram

2013-01-01

The modeling of the reference scenario and the various reduction scenarios in PAREST was based on the Central System of Emissions (CSE) (CSE, 2007). Emissions from road traffic were calculated by using the traffic emission model TREMOD (Knoerr et al., 2005) and fed into the CSE. The version TREMOD 4.17 has been used. The resulting emission levels in PAREST reference scenario were supplemented by the emission-reducing effect of the implementation of the future Euro 5 and 6 emission standards for cars and light commercial vehicles and Euro VI for heavy commercial vehicles in combination with the truck toll extension. [de

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

Science.gov (United States)

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

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.

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.

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].

Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.

Science.gov (United States)

Ki, Sehwan; Bae, Sung-Ho; Kim, Munchurl; Ko, Hyunsuk

2018-07-01

Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attempted to achieve high coding efficiency by eliminating perceptual redundancy, using just-noticeable-distortion (JND) directed PVC. The previous JNDs were modeled by adding white Gaussian noise or specific signal patterns into the original images, which were not appropriate in finding JND thresholds due to distortion with energy reduction. In this paper, we present a novel discrete cosine transform-based energy-reduced JND model, called ERJND, that is more suitable for JND-based PVC schemes. Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. The two JNQD models can automatically adjust JND levels based on given quantization step sizes. One of the two JNQD models, called LR-JNQD, is based on linear regression and determines the model parameter for JNQD based on extracted handcraft features. The other JNQD model is based on a convolution neural network (CNN), called CNN-JNQD. To our best knowledge, our paper is the first approach to automatically adjust JND levels according to quantization step sizes for preprocessing the input to video encoders. In experiments, both the LR-JNQD and CNN-JNQD models were applied to high efficiency video coding (HEVC) and yielded maximum (average) bitrate reductions of 38.51% (10.38%) and 67.88% (24.91%), respectively, with little subjective video quality degradation, compared with the input without preprocessing applied.

Finite size scaling analysis on Nagel-Schreckenberg model for traffic flow

Science.gov (United States)

Balouchi, Ashkan; Browne, Dana

2015-03-01

The traffic flow problem as a many-particle non-equilibrium system has caught the interest of physicists for decades. Understanding the traffic flow properties and though obtaining the ability to control the transition from the free-flow phase to the jammed phase plays a critical role in the future world of urging self-driven cars technology. We have studied phase transitions in one-lane traffic flow through the mean velocity, distributions of car spacing, dynamic susceptibility and jam persistence -as candidates for an order parameter- using the Nagel-Schreckenberg model to simulate traffic flow. The length dependent transition has been observed for a range of maximum velocities greater than a certain value. Finite size scaling analysis indicates power-law scaling of these quantities at the onset of the jammed phase.

Virtual Reality Game Education to Learn Traffic Regulation

Directory of Open Access Journals (Sweden)

Andru Deva Lukito

2017-10-01

Full Text Available Abstract – Traffic accident has become number 3 of children death cause in the world according to WHO[1]. Traffic accident that involve children often caused by their own by breaking the law or regulation. Therefor education about traffic regulation and law including traffic sign and its meaning must be given to children early. Because education means process to change a person or a group attitude and behavior in order to make them mature through teaching and training [2]. One of them that can be used is digital media.  One of interactive digital media is digital game, various form of digital game start from 2D, 2.5D, 3D with many point of view and new technology. VR (Virtual Reality as new digital media where alternate reality exist to test various theory without any real consequences, according to Greenbaum “Virtual Reality is an alternate world filled with computer-generated images that respond to human movements. These simulated environments are usually visited with the aid of an expensive data suit which features stereophonic video goggles and fiber-optic data gloves”[3]. Greenbaum statement before were make VR suitable to test traffic law and regulation and educate kid to obey the traffic sign and regulation without real consequences from real world. This Journal contain the result of using virtual reality as traffic regulation education media. Education material that arranged consisting traffic sign that appear on the road and safety riding gear. Keywords – Virtual Reality, Traffic sign, Road traffic, children, education

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.

Analysis and comparison of safety models using average daily, average hourly, and microscopic traffic.

Science.gov (United States)

Wang, Ling; Abdel-Aty, Mohamed; Wang, Xuesong; Yu, Rongjie

2018-02-01

There have been plenty of traffic safety studies based on average daily traffic (ADT), average hourly traffic (AHT), or microscopic traffic at 5 min intervals. Nevertheless, not enough research has compared the performance of these three types of safety studies, and seldom of previous studies have intended to find whether the results of one type of study is transferable to the other two studies. First, this study built three models: a Bayesian Poisson-lognormal model to estimate the daily crash frequency using ADT, a Bayesian Poisson-lognormal model to estimate the hourly crash frequency using AHT, and a Bayesian logistic regression model for the real-time safety analysis using microscopic traffic. The model results showed that the crash contributing factors found by different models were comparable but not the same. Four variables, i.e., the logarithm of volume, the standard deviation of speed, the logarithm of segment length, and the existence of diverge segment, were positively significant in the three models. Additionally, weaving segments experienced higher daily and hourly crash frequencies than merge and basic segments. Then, each of the ADT-based, AHT-based, and real-time models was used to estimate safety conditions at different levels: daily and hourly, meanwhile, the real-time model was also used in 5 min intervals. The results uncovered that the ADT- and AHT-based safety models performed similar in predicting daily and hourly crash frequencies, and the real-time safety model was able to provide hourly crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Recurrent and Dynamic Models for Predicting Streaming Video Quality of Experience.

Science.gov (United States)

Bampis, Christos G; Li, Zhi; Katsavounidis, Ioannis; Bovik, Alan C

2018-07-01

Streaming video services represent a very large fraction of global bandwidth consumption. Due to the exploding demands of mobile video streaming services, coupled with limited bandwidth availability, video streams are often transmitted through unreliable, low-bandwidth networks. This unavoidably leads to two types of major streaming-related impairments: compression artifacts and/or rebuffering events. In streaming video applications, the end-user is a human observer; hence being able to predict the subjective Quality of Experience (QoE) associated with streamed videos could lead to the creation of perceptually optimized resource allocation strategies driving higher quality video streaming services. We propose a variety of recurrent dynamic neural networks that conduct continuous-time subjective QoE prediction. By formulating the problem as one of time-series forecasting, we train a variety of recurrent neural networks and non-linear autoregressive models to predict QoE using several recently developed subjective QoE databases. These models combine multiple, diverse neural network inputs, such as predicted video quality scores, rebuffering measurements, and data related to memory and its effects on human behavioral responses, using them to predict QoE on video streams impaired by both compression artifacts and rebuffering events. Instead of finding a single time-series prediction model, we propose and evaluate ways of aggregating different models into a forecasting ensemble that delivers improved results with reduced forecasting variance. We also deploy appropriate new evaluation metrics for comparing time-series predictions in streaming applications. Our experimental results demonstrate improved prediction performance that approaches human performance. An implementation of this work can be found at https://github.com/christosbampis/NARX_QoE_release.

Improving traffic signal management and operations : a basic service model.

Science.gov (United States)

2009-12-01

This report provides a guide for achieving a basic service model for traffic signal management and : operations. The basic service model is based on simply stated and defensible operational objectives : that consider the staffing level, expertise and...

High-Performance Motion Estimation for Image Sensors with Video Compression

Directory of Open Access Journals (Sweden)

Weizhi Xu

2015-08-01

Full Text Available It is important to reduce the time cost of video compression for image sensors in video sensor network. Motion estimation (ME is the most time-consuming part in video compression. Previous work on ME exploited intra-frame data reuse in a reference frame to improve the time efficiency but neglected inter-frame data reuse. We propose a novel inter-frame data reuse scheme which can exploit both intra-frame and inter-frame data reuse for ME in video compression (VC-ME. Pixels of reconstructed frames are kept on-chip until they are used by the next current frame to avoid off-chip memory access. On-chip buffers with smart schedules of data access are designed to perform the new data reuse scheme. Three levels of the proposed inter-frame data reuse scheme are presented and analyzed. They give different choices with tradeoff between off-chip bandwidth requirement and on-chip memory size. All three levels have better data reuse efficiency than their intra-frame counterparts, so off-chip memory traffic is reduced effectively. Comparing the new inter-frame data reuse scheme with the traditional intra-frame data reuse scheme, the memory traffic can be reduced by 50% for VC-ME.

The Fusion Model of Intelligent Transportation Systems Based on the Urban Traffic Ontology

Science.gov (United States)

Yang, Wang-Dong; Wang, Tao

On these issues unified representation of urban transport information using urban transport ontology, it defines the statute and the algebraic operations of semantic fusion in ontology level in order to achieve the fusion of urban traffic information in the semantic completeness and consistency. Thus this paper takes advantage of the semantic completeness of the ontology to build urban traffic ontology model with which we resolve the problems as ontology mergence and equivalence verification in semantic fusion of traffic information integration. Information integration in urban transport can increase the function of semantic fusion, and reduce the amount of data integration of urban traffic information as well enhance the efficiency and integrity of traffic information query for the help, through the practical application of intelligent traffic information integration platform of Changde city, the paper has practically proved that the semantic fusion based on ontology increases the effect and efficiency of the urban traffic information integration, reduces the storage quantity, and improve query efficiency and information completeness.

Cross-band noise model refinement for transform domain Wyner–Ziv video coding

DEFF Research Database (Denmark)

Huang, Xin; Forchhammer, Søren

2012-01-01

TDWZ video coding trails that of conventional video coding solutions, mainly due to the quality of side information, inaccurate noise modeling and loss in the final coding step. The major goal of this paper is to enhance the accuracy of the noise modeling, which is one of the most important aspects...... influencing the coding performance of DVC. A TDWZ video decoder with a novel cross-band based adaptive noise model is proposed, and a noise residue refinement scheme is introduced to successively update the estimated noise residue for noise modeling after each bit-plane. Experimental results show...... that the proposed noise model and noise residue refinement scheme can improve the rate-distortion (RD) performance of TDWZ video coding significantly. The quality of the side information modeling is also evaluated by a measure of the ideal code length....

Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow

Science.gov (United States)

Fariz Hasan, Ahmad; Fikri Che Husin, Mohd; Affendi Rosli, Khairul; Norhafiz Hashim, Mohd; Faiz Zainal Abidin, Amar

2018-03-01

Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. By rapid number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. This system can take over the burden some task was performed by human operator in traffic monitoring centre. The main technique proposed by this paper is concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The system is able to automatically segment vehicle extracted from heavy traffic scene by optical flow estimation alongside with blob analysis technique in order to detect the moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.

Application of discriminative models for interactive query refinement in video retrieval

Science.gov (United States)

Srivastava, Amit; Khanwalkar, Saurabh; Kumar, Anoop

2013-12-01

The ability to quickly search for large volumes of videos for specific actions or events can provide a dramatic new capability to intelligence agencies. Example-based queries from video are a form of content-based information retrieval (CBIR) where the objective is to retrieve clips from a video corpus, or stream, using a representative query sample to find more like this. Often, the accuracy of video retrieval is largely limited by the gap between the available video descriptors and the underlying query concept, and such exemplar queries return many irrelevant results with relevant ones. In this paper, we present an Interactive Query Refinement (IQR) system which acts as a powerful tool to leverage human feedback and allow intelligence analyst to iteratively refine search queries for improved precision in the retrieved results. In our approach to IQR, we leverage discriminative models that operate on high dimensional features derived from low-level video descriptors in an iterative framework. Our IQR model solicits relevance feedback on examples selected from the region of uncertainty and updates the discriminating boundary to produce a relevance ranked results list. We achieved 358% relative improvement in Mean Average Precision (MAP) over initial retrieval list at a rank cutoff of 100 over 4 iterations. We compare our discriminative IQR model approach to a naïve IQR and show our model-based approach yields 49% relative improvement over the no model naïve system.

Exact solutions to traffic density estimation problems involving the Lighthill-Whitham-Richards traffic flow model using mixed integer programming

KAUST Repository

Canepa, Edward S.; Claudel, Christian G.

2012-01-01

This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.

Exact solutions to traffic density estimation problems involving the Lighthill-Whitham-Richards traffic flow model using mixed integer programming

KAUST Repository

Canepa, Edward S.

2012-09-01

This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.

Calibration of CORSIM models under saturated traffic flow conditions.

Science.gov (United States)

2013-09-01

This study proposes a methodology to calibrate microscopic traffic flow simulation models. : The proposed methodology has the capability to calibrate simultaneously all the calibration : parameters as well as demand patterns for any network topology....

Cognitive process modelling of controllers in en route air traffic control.

Science.gov (United States)

Inoue, Satoru; Furuta, Kazuo; Nakata, Keiichi; Kanno, Taro; Aoyama, Hisae; Brown, Mark

2012-01-01

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes. This research focuses on an experimental study to gain a better understanding of controllers' cognitive processes in air traffic control. We conducted ethnographic observations and then analysed the data to develop a model of controllers' cognitive process. This analysis revealed that strategic routines are applicable to decision making.

End-to-End Traffic Flow Modeling of the Integrated SCaN Network

Science.gov (United States)

Cheung, K.-M.; Abraham, D. S.

2012-05-01

In this article, we describe the analysis and simulation effort of the end-to-end traffic flow for the Integrated Space Communications and Navigation (SCaN) Network. Using the network traffic derived for the 30-day period of July 2018 from the Space Communications Mission Model (SCMM), we generate the wide-area network (WAN) bandwidths of the ground links for different architecture options of the Integrated SCaN Network. We also develop a new analytical scheme to model the traffic flow and buffering mechanism of a store-and-forward network. It is found that the WAN bandwidth of the Integrated SCaN Network is an important differentiator of different architecture options, as the recurring circuit costs of certain architecture options can be prohibitively high.

Game Theory Model of Traffic Participants within Amber Time at Signalized Intersection

Directory of Open Access Journals (Sweden)

Weiwei Qi

2014-01-01

Full Text Available The traffic light scheme is composed of red, green, and amber lights, and it has been defined clearly for the traffic access of red and green lights; however, the definition of that for the amber light is indistinct, which leads to the appearance of uncertainty factors and serious traffic conflicts during the amber light. At present, the traffic administrations are faced with the decision of whether to forbid passing or not during the amber light in the cities of China. On one hand, it will go against the purpose of setting amber lights if forbidding passing; on the other hand, it may lead to a mess of traffic flow running if not. And meanwhile the drivers are faced with the decision of passing the intersection or stopping during the amber light as well. So the decision-making behavior of traffic administrations and drivers can be converted into a double game model. And through quantification of their earnings in different choice conditions, the optimum decision-making plan under specific conditions could be solved via the Nash equilibrium solution concept. Thus the results will provide a basis for the formulation of the traffic management strategy.

Game Theory Model of Traffic Participants within Amber Time at Signalized Intersection

Science.gov (United States)

Qi, Weiwei; Wen, Huiying; Fu, Chuanyun; Song, Mo

2014-01-01

The traffic light scheme is composed of red, green, and amber lights, and it has been defined clearly for the traffic access of red and green lights; however, the definition of that for the amber light is indistinct, which leads to the appearance of uncertainty factors and serious traffic conflicts during the amber light. At present, the traffic administrations are faced with the decision of whether to forbid passing or not during the amber light in the cities of China. On one hand, it will go against the purpose of setting amber lights if forbidding passing; on the other hand, it may lead to a mess of traffic flow running if not. And meanwhile the drivers are faced with the decision of passing the intersection or stopping during the amber light as well. So the decision-making behavior of traffic administrations and drivers can be converted into a double game model. And through quantification of their earnings in different choice conditions, the optimum decision-making plan under specific conditions could be solved via the Nash equilibrium solution concept. Thus the results will provide a basis for the formulation of the traffic management strategy. PMID:25580108

Traffic forecasts ignoring induced demand

DEFF Research Database (Denmark)

Næss, Petter; Nicolaisen, Morten Skou; Strand, Arvid

2012-01-01

the model calculations included only a part of the induced traffic, the difference in cost-benefit results compared to the model excluding all induced traffic was substantial. The results show lower travel time savings, more adverse environmental impacts and a considerably lower benefitcost ratio when...... induced traffic is partly accounted for than when it is ignored. By exaggerating the economic benefits of road capacity increase and underestimating its negative effects, omission of induced traffic can result in over-allocation of public money on road construction and correspondingly less focus on other...... performance of a proposed road project in Copenhagen with and without short-term induced traffic included in the transport model. The available transport model was not able to include long-term induced traffic resulting from changes in land use and in the level of service of public transport. Even though...

Examining the Effects of Video Modeling and Prompts to Teach Activities of Daily Living Skills.

Science.gov (United States)

Aldi, Catarina; Crigler, Alexandra; Kates-McElrath, Kelly; Long, Brian; Smith, Hillary; Rehak, Kim; Wilkinson, Lisa

2016-12-01

Video modeling has been shown to be effective in teaching a number of skills to learners diagnosed with autism spectrum disorders (ASD). In this study, we taught two young men diagnosed with ASD three different activities of daily living skills (ADLS) using point-of-view video modeling. Results indicated that both participants met criterion for all ADLS. Participants did not maintain mastery criterion at a 1-month follow-up, but did score above baseline at maintenance with and without video modeling. • Point-of-view video models may be an effective intervention to teach daily living skills. • Video modeling with handheld portable devices (Apple iPod or iPad) can be just as effective as video modeling with stationary viewing devices (television or computer). • The use of handheld portable devices (Apple iPod and iPad) makes video modeling accessible and possible in a wide variety of environments.

Continuous Video Modeling to Prompt Completion of Multi-Component Tasks by Adults with Moderate Intellectual Disability

Science.gov (United States)

Mechling, Linda C.; Ayres, Kevin M.; Purrazzella, Kaitlin; Purrazzella, Kimberly

2014-01-01

This investigation examined the ability of four adults with moderate intellectual disability to complete multi-component tasks using continuous video modeling. Continuous video modeling, which is a newly researched application of video modeling, presents video in a "looping" format which automatically repeats playing of the video while…

An improvement analysis on video compression using file segmentation

Science.gov (United States)

Sharma, Shubhankar; Singh, K. John; Priya, M.

2017-11-01

From the past two decades the extreme evolution of the Internet has lead a massive rise in video technology and significantly video consumption over the Internet which inhabits the bulk of data traffic in general. Clearly, video consumes that so much data size on the World Wide Web, to reduce the burden on the Internet and deduction of bandwidth consume by video so that the user can easily access the video data.For this, many video codecs are developed such as HEVC/H.265 and V9. Although after seeing codec like this one gets a dilemma of which would be improved technology in the manner of rate distortion and the coding standard.This paper gives a solution about the difficulty for getting low delay in video compression and video application e.g. ad-hoc video conferencing/streaming or observation by surveillance. Also this paper describes the benchmark of HEVC and V9 technique of video compression on subjective oral estimations of High Definition video content, playback on web browsers. Moreover, this gives the experimental ideology of dividing the video file into several segments for compression and putting back together to improve the efficiency of video compression on the web as well as on the offline mode.

Data Mining Meets Performance Evaluation: Fast Algorithms for Modeling Bursty Traffic

National Research Council Canada - National Science Library

Wang, Mengzhi; Madhyastha, Tara; Chan, Ngai H; Paradimitriou, Spiros; Faloutsos, Christos

2001-01-01

...]. However, we do want to model these types of traffic and to generate realistic traces, because of obvious applications for disk scheduling, network management, web server design. Previous models...

The Racing-Game Effect: Why Do Video Racing Games Increase Risk-Taking Inclinations?

OpenAIRE

Fischer, Peter; Greitemeyer, Tobias; Morton, Thomas; Kastenmüller, Andreas; Postmes, Tom; Frey, Dieter; Kubitzki, Jörg; Odenwälder, Jörg

2009-01-01

The present studies investigated why video racing games increase players’ risk-taking inclinations. Four studies reveal that playing video racing games increases risk taking in a subsequent simulated road traffic situation, as well as risk-promoting cognitions and emotions, blood pressure,sensation seeking, and attitudes toward reckless driving. Study 1 ruled out the role of experimental demand in creating such effects. Studies 2 and 3 showed that the effect of playing video racing games on r...

Web application and database modeling of traffic impact analysis using Google Maps

Science.gov (United States)

Yulianto, Budi; Setiono

2017-06-01

Traffic impact analysis (TIA) is a traffic study that aims at identifying the impact of traffic generated by development or change in land use. In addition to identifying the traffic impact, TIA is also equipped with mitigation measurement to minimize the arising traffic impact. TIA has been increasingly important since it was defined in the act as one of the requirements in the proposal of Building Permit. The act encourages a number of TIA studies in various cities in Indonesia, including Surakarta. For that reason, it is necessary to study the development of TIA by adopting the concept Transportation Impact Control (TIC) in the implementation of the TIA standard document and multimodal modeling. It includes TIA's standardization for technical guidelines, database and inspection by providing TIA checklists, monitoring and evaluation. The research was undertaken by collecting the historical data of junctions, modeling of the data in the form of relational database, building a user interface for CRUD (Create, Read, Update and Delete) the TIA data in the form of web programming with Google Maps libraries. The result research is a system that provides information that helps the improvement and repairment of TIA documents that exist today which is more transparent, reliable and credible.

A new lattice hydrodynamic traffic flow model with a consideration of multi-anticipation effect

International Nuclear Information System (INIS)

Tian Chuan; Sun Di-Hua; Yang Shu-Hong

2011-01-01

We present a new multi-anticipation lattice hydrodynamic model based on the traffic anticipation effect in the real world. Applying the linear stability theory, we obtain the linear stability condition of the model. Through nonlinear analysis, we derive the modified Korteweg-de Vries equation to describe the propagating behaviour of a traffic density wave near the critical point. The good agreement between the simulation results and the analytical results shows that the stability of traffic flow can be enhanced when the multi-anticipation effect is considered. (interdisciplinary physics and related areas of science and technology)

Modeling mechanical restriction differences between car and heavy truck in two-lane cellular automata traffic flow model

Science.gov (United States)

Li, Xin; Li, Xingang; Xiao, Yao; Jia, Bin

2016-06-01

Real traffic is heterogeneous with car and truck. Due to mechanical restrictions, the car and the truck have different limited deceleration capabilities, which are important factors in safety driving. This paper extends the single lane safety driving (SD) model with limited deceleration capability to two-lane SD model, in which car-truck heterogeneous traffic is considered. A car has a larger limited deceleration capability while a heavy truck has a smaller limited deceleration capability as a result of loaded goods. Then the safety driving conditions are different as the types of the following and the leading vehicles vary. In order to eliminate the well-known plug in heterogeneous two-lane traffic, it is assumed that heavy truck has active deceleration behavior when the heavy truck perceives the forming plug. The lane-changing decisions are also determined by the safety driving conditions. The fundamental diagram, spatiotemporal diagram, and lane-changing frequency were investigated to show the effect of mechanical restriction on heterogeneous traffic flow. It was shown that there would be still three traffic phases in heterogeneous traffic condition; the active deceleration of the heavy truck could well eliminate the plug; the lane-changing frequency was low in synchronized flow; the flow and velocity would decrease as the proportion of heavy truck grows or the limited deceleration capability of heavy truck drops; and the flow could be improved with lane control measures.

Literature review on risky driving videos on YouTube: Unknown effects and areas for concern?

Science.gov (United States)

Vingilis, Evelyn; Yıldırım-Yenier, Zümrüt; Vingilis-Jaremko, Larissa; Wickens, Christine; Seeley, Jane; Fleiter, Judy; Grushka, Daniel H

2017-08-18

Entry of terms reflective of extreme risky driving behaviors into the YouTube website yields millions of videos. The majority of the top 20 highly subscribed automotive YouTube websites are focused on high-performance vehicles, high speed, and often risky driving. Moreover, young men are the heaviest users of online video sharing sites, overall streaming more videos, and watching them longer than any other group. The purpose of this article is to review the literature on YouTube videos and risky driving. A systematic search was performed using the following specialized database sources-Scopus, PubMed, Web of Science, ERIC, and Google Scholar-for the years 2005-2015 for articles in the English language. Search words included "YouTube AND driving," "YouTube AND speeding," "YouTube AND racing." No published research was found on the content of risky driving videos or on the effects of these videos on viewers. This literature review presents the current state of our published knowledge on the topic, which includes a review of the effects of mass media on risky driving cognitions; attitudes and behavior; similarities and differences between mass and social media; information on the YouTube platform; psychological theories that could support YouTube's potential effects on driving behavior; and 2 examples of risky driving behaviors ("sidewalk skiing" and "ghost riding the whip") suggestive of varying levels of modeling behavior in subsequent YouTube videos. Every month about 1 billion individuals are reported to view YouTube videos (ebizMBA Guide 2015 ) and young men are the heaviest users, overall streaming more YouTube videos and watching them longer than women and other age groups (Nielsen 2011 ). This group is also the most dangerous group in traffic, engaging in more per capita violations and experiencing more per capita injuries and fatalities (e.g., Parker et al. 1995 ; Reason et al. 1990 ; Transport Canada 2015 ; World Health Organization 2015 ). YouTube also

Obtaining Application-based and Content-based Internet Traffic Statistics

DEFF Research Database (Denmark)

Bujlow, Tomasz; Pedersen, Jens Myrup

2012-01-01

the Volunteer-Based System for Research on the Internet, developed at Aalborg University, is capable of providing detailed statistics of Internet usage. Since an increasing amount of HTTP traffic has been observed during the last few years, the system also supports creating statistics of different kinds of HTTP...... traffic, like audio, video, file transfers, etc. All statistics can be obtained for individual users of the system, for groups of users, or for all users altogether. This paper presents results with real data collected from a limited number of real users over six months. We demonstrate that the system can...

Travelers ability to observe changes in traffic intensities and traffic light settings

NARCIS (Netherlands)

Vreeswijk, Jacob Dirk; Do, Michael; Middag, Wilco; Martens, Marieke Hendrikje; van Berkum, Eric C.; van Arem, Bart; ITSC,

2011-01-01

Travel choice behavior is an important determinant in traffic and subject to human imperfection and bounded rationality. In decision-making processes travelers seldom act perfectly rational. Traffic models and traffic network management measure could become more realistic and effective, if

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.

Digital Video as a Personalized Learning Assignment: A Qualitative Study of Student Authored Video Using the ICSDR Model

Science.gov (United States)

Campbell, Laurie O.; Cox, Thomas D.

2018-01-01

Students within this study followed the ICSDR (Identify, Conceptualize/Connect, Storyboard, Develop, Review/Reflect/Revise) development model to create digital video, as a personalized and active learning assignment. The participants, graduate students in education, indicated that following the ICSDR framework for student-authored video guided…

Video Modeling and Prompting in Practice: Teaching Cooking Skills

Science.gov (United States)

Kellems, Ryan O.; Mourra, Kjerstin; Morgan, Robert L.; Riesen, Tim; Glasgow, Malinda; Huddleston, Robin

2016-01-01

This article discusses the creation of video modeling (VM) and video prompting (VP) interventions for teaching novel multi-step tasks to individuals with disabilities. This article reviews factors to consider when selecting skills to teach, and students for whom VM/VP may be successful, as well as the difference between VM and VP and circumstances…

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

Science.gov (United States)

Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming

2015-08-01

Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.

Effects of creating video-based modeling examples on learning and transfer

NARCIS (Netherlands)

Hoogerheide, Vincent; Loyens, Sofie M M; van Gog, Tamara

2014-01-01

Two experiments investigated whether acting as a peer model for a video-based modeling example, which entails studying a text with the intention to explain it to others and then actually explaining it on video, would foster learning and transfer. In both experiments, novices were instructed to study

A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

Energy Technology Data Exchange (ETDEWEB)

Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr [TECHNOLOGICAL RESEARCH INSTITUTE SYSTEMX (France); Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr [UPE/IFSTTAR-COSYS-GRETTIA (France)

2015-03-10

We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap scheme is introduced to numerically approximate the model’s flow equations.

Transforming GIS data into functional road models for large-scale traffic simulation.

Science.gov (United States)

Wilkie, David; Sewall, Jason; Lin, Ming C

2012-06-01

There exists a vast amount of geographic information system (GIS) data that model road networks around the world as polylines with attributes. In this form, the data are insufficient for applications such as simulation and 3D visualization-tools which will grow in power and demand as sensor data become more pervasive and as governments try to optimize their existing physical infrastructure. In this paper, we propose an efficient method for enhancing a road map from a GIS database to create a geometrically and topologically consistent 3D model to be used in real-time traffic simulation, interactive visualization of virtual worlds, and autonomous vehicle navigation. The resulting representation provides important road features for traffic simulations, including ramps, highways, overpasses, legal merge zones, and intersections with arbitrary states, and it is independent of the simulation methodologies. We test the 3D models of road networks generated by our algorithm on real-time traffic simulation using both macroscopic and microscopic techniques.

Video Modeling and Observational Learning to Teach Gaming Access to Students with ASD

Science.gov (United States)

Spriggs, Amy D.; Gast, David L.; Knight, Victoria F.

2016-01-01

The purpose of this study was to evaluate both video modeling and observational learning to teach age-appropriate recreation and leisure skills (i.e., accessing video games) to students with autism spectrum disorder. Effects of video modeling were evaluated via a multiple probe design across participants and criteria for mastery were based on…

Using Video Modeling as an Anti-bullying Intervention for Children with Autism Spectrum Disorder.

Science.gov (United States)

Rex, Catherine; Charlop, Marjorie H; Spector, Vicki

2018-03-07

In the present study, we used a multiple baseline design across participants to assess the efficacy of a video modeling intervention to teach six children with autism spectrum disorder (ASD) to assertively respond to bullying. During baseline, the children made few appropriate responses upon viewing video clips of bullying scenarios. During the video modeling intervention, participants viewed videos of models assertively responding to three types of bullying: physical, verbal bullying, and social exclusion. Results indicated that all six children learned through video modeling to make appropriate assertive responses to bullying scenarios. Four of the six children demonstrated learning in the in situ bullying probes. The results are discussed in terms of an intervention for victims of bullying with ASD.

Energy saving approaches for video streaming on smartphone based on QoE modeling

DEFF Research Database (Denmark)

Ballesteros, Luis Guillermo Martinez; Ickin, Selim; Fiedler, Markus

2016-01-01

In this paper, we study the influence of video stalling on QoE. We provide QoE models that are obtained in realistic scenarios on the smartphone, and provide energy-saving approaches for smartphone by leveraging the proposed QoE models in relation to energy. Results show that approximately 5J...... is saved in a 3 minutes video clip with an acceptable Mean Opinion Score (MOS) level when the video frames are skipped. If the video frames are not skipped, then it is suggested to avoid freezes during a video stream as the freezes highly increase the energy waste on the smartphones....

Player behavioural modelling for video games

NARCIS (Netherlands)

van Lankveld, G.; Spronck, P.H.M.; Bakkes, S.C.J.

2012-01-01

Player behavioural modelling has grown from a means to improve the playing strength of computer programs that play classic games (e.g., chess), to a means for impacting the player experience and satisfaction in video games, as well as in cross-domain applications such as interactive storytelling. In

A Dynamic Traffic Signal Timing Model and its Algorithm for Junction of Urban Road

DEFF Research Database (Denmark)

Cai, Yanguang; Cai, Hao

2012-01-01

As an important part of Intelligent Transportation System, the scientific traffic signal timing of junction can improve the efficiency of urban transport. This paper presents a novel dynamic traffic signal timing model. According to the characteristics of the model, hybrid chaotic quantum...... evolutionary algorithm is employed to solve it. The proposed model has simple structure, and only requires traffic inflow speed and outflow speed are bounded functions with at most finite number of discontinuity points. The condition is very loose and better meets the requirements of the practical real......-time and dynamic signal control of junction. To obtain the optimal solution of the model by hybrid chaotic quantum evolutionary algorithm, the model is converted to an easily solvable form. To simplify calculation, we give the expression of the partial derivative and change rate of the objective function...

Bayesian Modeling of Temporal Coherence in Videos for Entity Discovery and Summarization.

Science.gov (United States)

Mitra, Adway; Biswas, Soma; Bhattacharyya, Chiranjib

2017-03-01

A video is understood by users in terms of entities present in it. Entity Discovery is the task of building appearance model for each entity (e.g., a person), and finding all its occurrences in the video. We represent a video as a sequence of tracklets, each spanning 10-20 frames, and associated with one entity. We pose Entity Discovery as tracklet clustering, and approach it by leveraging Temporal Coherence (TC): the property that temporally neighboring tracklets are likely to be associated with the same entity. Our major contributions are the first Bayesian nonparametric models for TC at tracklet-level. We extend Chinese Restaurant Process (CRP) to TC-CRP, and further to Temporally Coherent Chinese Restaurant Franchise (TC-CRF) to jointly model entities and temporal segments using mixture components and sparse distributions. For discovering persons in TV serial videos without meta-data like scripts, these methods show considerable improvement over state-of-the-art approaches to tracklet clustering in terms of clustering accuracy, cluster purity and entity coverage. The proposed methods can perform online tracklet clustering on streaming videos unlike existing approaches, and can automatically reject false tracklets. Finally we discuss entity-driven video summarization- where temporal segments of the video are selected based on the discovered entities, to create a semantically meaningful summary.

Reviewing Instructional Studies Conducted Using Video Modeling to Children with Autism

Science.gov (United States)

Acar, Cimen; Diken, Ibrahim H.

2012-01-01

This study explored 31 instructional research articles written using video modeling to children with autism and published in peer-reviewed journals. The studies in this research have been reached by searching EBSCO, Academic Search Complete, ERIC and other Anadolu University online search engines and using keywords such as "autism, video modeling,…

No-Reference Video Quality Assessment Model for Distortion Caused by Packet Loss in the Real-Time Mobile Video Services

Directory of Open Access Journals (Sweden)

Jiarun Song

2014-01-01

Full Text Available Packet loss will make severe errors due to the corruption of related video data. For most video streams, because the predictive coding structures are employed, the transmission errors in one frame will not only cause decoding failure of itself at the receiver side, but also propagate to its subsequent frames along the motion prediction path, which will bring a significant degradation of end-to-end video quality. To quantify the effects of packet loss on video quality, a no-reference objective quality assessment model is presented in this paper. Considering the fact that the degradation of video quality significantly relies on the video content, the temporal complexity is estimated to reflect the varying characteristic of video content, using the macroblocks with different motion activities in each frame. Then, the quality of the frame affected by the reference frame loss, by error propagation, or by both of them is evaluated, respectively. Utilizing a two-level temporal pooling scheme, the video quality is finally obtained. Extensive experimental results show that the video quality estimated by the proposed method matches well with the subjective quality.

Power consumption analysis of constant bit rate video transmission over 3G networks

DEFF Research Database (Denmark)

Ukhanova, Ann; Belyaev, Evgeny; Wang, Le

2012-01-01

This paper presents an analysis of the power consumption of video data transmission with constant bit rate over 3G mobile wireless networks. The work includes the description of the radio resource control transition state machine in 3G networks, followed by a detailed power consumption analysis...... and measurements of the radio link power consumption. Based on this description and analysis, we propose our power consumption model. The power model was evaluated on a smartphone Nokia N900, which follows 3GPP Release 5 and 6 supporting HSDPA/HSUPA data bearers. We also propose a method for parameter selection...... for the 3GPP transition state machine that allows to decrease power consumption on a mobile device taking signaling traffic, buffer size and latency restrictions into account. Furthermore, we discuss the gain in power consumption vs. PSNR for transmitted video and show the possibility of performing power...

When Video Games Tell Stories: A Model of Video Game Narrative Architectures

Directory of Open Access Journals (Sweden)

Marcello Arnaldo Picucci

2014-11-01

Full Text Available In the present study a model is proposed offering a comprehensive categorization of video game narrative structures intended as the methods and techniques used by game designers and allowed by the medium to deliver the story content throughout the gameplay in collaboration with the players. A case is first made for the presence of narrative in video games and its growth of importance as a central component in game design. An in-depth analysis ensues focusing on how games tell stories, guided by the criteria of linearity/nonlinearity, interactivity and randomness. Light is shed upon the fundamental architectures through which stories are told as well as the essential boundaries posed by the close link between narrative and game AI.

High-level traffic-violation detection for embedded traffic analysis

NARCIS (Netherlands)

Vijverberg, J.A.; de Koning, A.H.M.; Han, Jungong; de With, P.H.N.; Cornelissen, D.

2007-01-01

This paper presents the design of a robust and real-time traffic-violation detection system for cameras on intersections. We use background segmentation and a novel road-model to obtain the candidate traffic participants. A region-based tracking system, equipped with static occlusion-reasoning,

Modeling carbon emissions from urban traffic system using mobile monitoring.

Science.gov (United States)

Sun, Daniel Jian; Zhang, Ying; Xue, Rui; Zhang, Yi

2017-12-01

Comprehensive analyses of urban traffic carbon emissions are critical in achieving low-carbon transportation. This paper started from the architecture design of a carbon emission mobile monitoring system using multiple sets of equipment and collected the corresponding data about traffic flow, meteorological conditions, vehicular carbon emissions and driving characteristics on typical roads in Shanghai and Wuxi, Jiangsu province. Based on these data, the emission model MOVES was calibrated and used with various sensitivity and correlation evaluation indices to analyze the traffic carbon emissions at microscopic, mesoscopic and macroscopic levels, respectively. The major factors that influence urban traffic carbon emissions were investigated, so that emission factors of CO, CO 2 and HC were calculated by taking representative passenger cars as a case study. As a result, the urban traffic carbon emissions were assessed quantitatively, and the total amounts of CO, CO 2 and HC emission from passenger cars in Shanghai were estimated as 76.95kt, 8271.91kt, and 2.13kt, respectively. Arterial roads were found as the primary line source, accounting for 50.49% carbon emissions. In additional to the overall major factors identified, the mobile monitoring system and carbon emission quantification method proposed in this study are of rather guiding significance for the further urban low-carbon transportation development. Copyright © 2017 Elsevier B.V. All rights reserved.

A spring-mass-damper system dynamics-based driver-vehicle integrated model for representing heterogeneous traffic

Science.gov (United States)

Munigety, Caleb Ronald

2018-04-01

The traditional traffic microscopic simulation models consider driver and vehicle as a single unit to represent the movements of drivers in a traffic stream. Due to this very fact, the traditional car-following models have the driver behavior related parameters, but ignore the vehicle related aspects. This approach is appropriate for homogeneous traffic conditions where car is the major vehicle type. However, in heterogeneous traffic conditions where multiple vehicle types are present, it becomes important to incorporate the vehicle related parameters exclusively to account for the varying dynamic and static characteristics. Thus, this paper presents a driver-vehicle integrated model hinged on the principles involved in physics-based spring-mass-damper mechanical system. While the spring constant represents the driver’s aggressiveness, the damping constant and the mass component take care of the stability and size/weight related aspects, respectively. The proposed model when tested, behaved pragmatically in representing the vehicle-type dependent longitudinal movements of vehicles.

Video processing for human perceptual visual quality-oriented video coding.

Science.gov (United States)

Oh, Hyungsuk; Kim, Wonha

2013-04-01

We have developed a video processing method that achieves human perceptual visual quality-oriented video coding. The patterns of moving objects are modeled by considering the limited human capacity for spatial-temporal resolution and the visual sensory memory together, and an online moving pattern classifier is devised by using the Hedge algorithm. The moving pattern classifier is embedded in the existing visual saliency with the purpose of providing a human perceptual video quality saliency model. In order to apply the developed saliency model to video coding, the conventional foveation filtering method is extended. The proposed foveation filter can smooth and enhance the video signals locally, in conformance with the developed saliency model, without causing any artifacts. The performance evaluation results confirm that the proposed video processing method shows reliable improvements in the perceptual quality for various sequences and at various bandwidths, compared to existing saliency-based video coding methods.

Strategies for Teaching Children with Autism to Imitate Response Chains Using Video Modeling

Science.gov (United States)

Tereshko, Lisa; MacDonald, Rebecca; Ahearn, William H.

2010-01-01

Video modeling has been found to be an effective procedure for teaching a variety of skills to persons with autism, however, some individuals do not learn through video instruction. The purpose of the current investigation was to teach children with autism, who initially did not imitate a video model, to construct three toy structures through the…

Modeling Mixed Bicycle Traffic Flow: A Comparative Study on the Cellular Automata Approach

Directory of Open Access Journals (Sweden)

Dan Zhou

2015-01-01

Full Text Available Simulation, as a powerful tool for evaluating transportation systems, has been widely used in transportation planning, management, and operations. Most of the simulation models are focused on motorized vehicles, and the modeling of nonmotorized vehicles is ignored. The cellular automata (CA model is a very important simulation approach and is widely used for motorized vehicle traffic. The Nagel-Schreckenberg (NS CA model and the multivalue CA (M-CA model are two categories of CA model that have been used in previous studies on bicycle traffic flow. This paper improves on these two CA models and also compares their characteristics. It introduces a two-lane NS CA model and M-CA model for both regular bicycles (RBs and electric bicycles (EBs. In the research for this paper, many cases, featuring different values for the slowing down probability, lane-changing probability, and proportion of EBs, were simulated, while the fundamental diagrams and capacities of the proposed models were analyzed and compared between the two models. Field data were collected for the evaluation of the two models. The results show that the M-CA model exhibits more stable performance than the two-lane NS model and provides results that are closer to real bicycle traffic.

A time-varying subjective quality model for mobile streaming videos with stalling events

Science.gov (United States)

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C.

2015-09-01

Over-the-top mobile video streaming is invariably influenced by volatile network conditions which cause playback interruptions (stalling events), thereby impairing users' quality of experience (QoE). Developing models that can accurately predict users' QoE could enable the more efficient design of quality-control protocols for video streaming networks that reduce network operational costs while still delivering high-quality video content to the customers. Existing objective models that predict QoE are based on global video features, such as the number of stall events and their lengths, and are trained and validated on a small pool of ad hoc video datasets, most of which are not publicly available. The model we propose in this work goes beyond previous models as it also accounts for the fundamental effect that a viewer's recent level of satisfaction or dissatisfaction has on their overall viewing experience. In other words, the proposed model accounts for and adapts to the recency, or hysteresis effect caused by a stall event in addition to accounting for the lengths, frequency of occurrence, and the positions of stall events - factors that interact in a complex way to affect a user's QoE. On the recently introduced LIVE-Avvasi Mobile Video Database, which consists of 180 distorted videos of varied content that are afflicted solely with over 25 unique realistic stalling events, we trained and validated our model to accurately predict the QoE, attaining standout QoE prediction performance.

Multicast traffic grooming in flexible optical WDM networks

Science.gov (United States)

Patel, Ankitkumar N.; Ji, Philip N.; Jue, Jason P.; Wang, Ting

2012-12-01

In Metropolitan Area Networks (MANs), point-to-multipoint applications, such as IPTV, video-on-demand, distance learning, and content distribution, can be efficiently supported through light-tree-based multicastcommunications instead of lightpath-based unicast-communications. The application of multicasting for such traffic is justified by its inherent benefits of reduced control and management overhead and elimination of redundant resource provisioning. Supporting such multicast traffic in Flexible optical WDM (FWDM) networks that can provision light-trees using optimum amount of spectrum within flexible channel spacing leads to higher wavelength and spectral efficiencies compared to the conventional ITU-T fixed grid networks. However, in spite of such flexibility, the residual channel capacity of stranded channels may not be utilized if the network does not offer channels with arbitrary line rates. Additionally, the spectrum allocated to guard bands used to isolate finer granularity channels remains unutilized. These limitations can be addressed by using traffic grooming in which low-rate multicast connections are aggregated and switched over high capacity light-trees. In this paper, we address the multicast traffic grooming problem in FWDM networks, and propose a novel auxiliary graph-based algorithm for the first time. The performance of multicast traffic grooming is evaluated in terms of spectral, cost, and energy efficiencies compared to lightpath-based transparent FWDM networks, lightpathbased traffic grooming-capable FWDM networks, multicast-enabled transparent FWDM networks, and multicast traffic grooming-capable fixed grid networks. Simulation results demonstrate that multicast traffic grooming in FWDM networks not only improves spectral efficiency, but also cost, and energy efficiencies compared to other multicast traffic provisioning approaches of FWDM and fixed grid networks.

A geographic approach to modelling human exposure to traffic air pollution using GIS

Energy Technology Data Exchange (ETDEWEB)

Solvang Jensen, S.

1998-10-01

A new exposure model has been developed that is based on a physical, single media (air) and single source (traffic) micro environmental approach that estimates traffic related exposures geographically with the postal address as exposure indicator. The micro environments: residence, workplace and street (road user exposure) may be considered. The model estimates outdoor levels for selected ambient air pollutants (benzene, CO, NO{sub 2} and O{sub 3}). The influence of outdoor air pollution on indoor levels can be estimated using average (I/O-ratios. The model has a very high spatial resolution (the address), a high temporal resolution (one hour) and may be used to predict past, present and future exposures. The model may be used for impact assessment of control measures provided that the changes to the model inputs are obtained. The exposure model takes advantage of a standard Geographic Information System (GIS) (ArcView and Avenue) for generation of inputs, for visualisation of input and output, and uses available digital maps, national administrative registers and a local traffic database, and the Danish Operational Street Pollution Model (OSPM). The exposure model presents a new approach to exposure determination by integration of digital maps, administrative registers, a street pollution model and GIS. New methods have been developed to generate the required input parameters for the OSPM model: to geocode buildings using cadastral maps and address points, to automatically generate street configuration data based on digital maps, the BBR and GIS; to predict the temporal variation in traffic and related parameters; and to provide hourly background levels for the OSPM model. (EG) 109 refs.

Systems approach to modeling the Token Bucket algorithm in computer networks

Directory of Open Access Journals (Sweden)

Ahmed N. U.

2002-01-01

Full Text Available In this paper, we construct a new dynamic model for the Token Bucket (TB algorithm used in computer networks and use systems approach for its analysis. This model is then augmented by adding a dynamic model for a multiplexor at an access node where the TB exercises a policing function. In the model, traffic policing, multiplexing and network utilization are formally defined. Based on the model, we study such issues as (quality of service QoS, traffic sizing and network dimensioning. Also we propose an algorithm using feedback control to improve QoS and network utilization. Applying MPEG video traces as the input traffic to the model, we verify the usefulness and effectiveness of our model.

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.

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...

Urban Road Traffic Simulation Techniques

Directory of Open Access Journals (Sweden)

Ana Maria Nicoleta Mocofan

2011-09-01

Full Text Available For achieving a reliable traffic control system it is necessary to first establish a network parameter evaluation system and also a simulation system for the traffic lights plan. In 40 years of history, the computer aided traffic simulation has developed from a small research group to a large scale technology for traffic systems planning and development. In the following thesis, a presentation of the main modeling and simulation road traffic applications will be provided, along with their utility, as well as the practical application of one of the models in a case study.

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.

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.

An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management.

Science.gov (United States)

Bongiorno, Christian; Miccichè, Salvatore; Mantegna, Rosario N

2017-01-01

We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers' operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast.

An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management.

Directory of Open Access Journals (Sweden)

Christian Bongiorno

Full Text Available We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers' operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i in the presence of perfect forecast ability of controllers, and (ii in the presence of some degree of uncertainty in flight trajectory forecast.

Heavy traffic analysis of polling models by mean value analysis

NARCIS (Netherlands)

Mei, van der R.D.; Winands, E.M.M.

2008-01-01

In this paper we present a new approach to derive heavy-traffic asymptotics for polling models. We consider the classical cyclic polling model with exhaustive or gated service at each queue, and with general service-time and switch-over time distributions, and study its behavior when the load tends

Urban traffic noise assessment by combining measurement and model results

NARCIS (Netherlands)

Eerden, F.J.M. van der; Graafland, F.; Wessels, P.W.; Basten, T.G.H.

2013-01-01

A model based monitoring system is applied on a local scale in an urban area to obtain a better understanding of the traffic noise situation. The system consists of a scalable sensor network and an engineering model. A better understanding is needed to take appropriate and cost efficient measures,

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

Topical video object discovery from key frames by modeling word co-occurrence prior.

Science.gov (United States)

Zhao, Gangqiang; Yuan, Junsong; Hua, Gang; Yang, Jiong

2015-12-01

A topical video object refers to an object, that is, frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames. Previous work using topic models, such as latent Dirichelet allocation (LDA), for video object discovery often takes a bag-of-visual-words representation, which ignored important co-occurrence information among the local features. We show that such data driven co-occurrence information from bottom-up can conveniently be incorporated in LDA with a Gaussian Markov prior, which combines top-down probabilistic topic modeling with bottom-up priors in a unified model. Our experiments on challenging videos demonstrate that the proposed approach can discover different types of topical objects despite variations in scale, view-point, color and lighting changes, or even partial occlusions. The efficacy of the co-occurrence prior is clearly demonstrated when compared with topic models without such priors.

SVC VIDEO STREAM ALLOCATION AND ADAPTATION IN HETEROGENEOUS NETWORK

Directory of Open Access Journals (Sweden)

E. A. Pakulova

2016-07-01

Full Text Available The paper deals with video data transmission in format H.264/SVC standard with QoS requirements satisfaction. The Sender-Side Path Scheduling (SSPS algorithm and Sender-Side Video Adaptation (SSVA algorithm were developed. SSPS algorithm gives the possibility to allocate video traffic among several interfaces while SSVA algorithm dynamically changes the quality of video sequence in relation to QoS requirements. It was shown that common usage of two developed algorithms enables to aggregate throughput of access networks, increase parameters of Quality of Experience and decrease losses in comparison with Round Robin algorithm. For evaluation of proposed solution, the set-up was made. The trace files with throughput of existing public networks were used in experiments. Based on this information the throughputs of networks were limited and losses for paths were set. The results of research may be used for study and transmission of video data in heterogeneous wireless networks.

An extended car-following model to describe connected traffic dynamics under cyberattacks

Science.gov (United States)

Wang, Pengcheng; Yu, Guizhen; Wu, Xinkai; Qin, Hongmao; Wang, Yunpeng

2018-04-01

In this paper, the impacts of the potential cyberattacks on vehicles are modeled through an extended car-following model. To better understand the mechanism of traffic disturbance under cyberattacks, the linear and nonlinear stability analysis are conducted respectively. Particularly, linear stability analysis is performed to obtain different neutral stability conditions with various parameters; and nonlinear stability analysis is carried out by using reductive perturbation method to derive the soliton solution of the modified Korteweg de Vries equation (mKdV) near the critical point, which is used to draw coexisting stability lines. Furthermore, by applying linear and nonlinear stability analysis, traffic flow state can be divided into three states, i.e., stable, metastable and unstable states which are useful to describe shockwave dynamics and driving behaviors under cyberattacks. The theoretical results show that the proposed car-following model is capable of successfully describing the car-following behavior of connected vehicles with cyberattacks. Finally, numerical simulation using real values has confirmed the validity of theoretical analysis. The results further demonstrate our model can be used to help avoid collisions and relieve traffic congestion with cybersecurity threats.

A Collaborative Video Sketching Model in the Making

DEFF Research Database (Denmark)

Gundersen, Peter Bukovica; Ørngreen, Rikke; Hautopp, Heidi

model, where we explore the relation between the educational research design team, their sketching and video sketching activities. The results show how sketching can be done in different modes and how it supports thinking, communication, reflection and distributed cognition in design teams when......The literature on design research emphasizes working in iterative cycles that investigate and explore many ideas and alternative designs. However, these cycles are seldom applied or documented in educational research papers. In this paper, we illustrate the development process of a video sketching...

A collaborative video sketching model in the making

DEFF Research Database (Denmark)

Gundersen, Peter; Ørngreen, Rikke; Henningsen, Birgitte

2018-01-01

model, where we explore the relation between the educational research design team, their sketching and video sketching activities. The results show how sketching can be done in different modes and how it supports thinking, communication, reflection and distributed cognition in design teams when......The literature on design research emphasizes working in iterative cycles that investigate and explore many ideas and alternative designs. However, these cycles are seldom applied or documented in educational research papers. In this paper, we illustrate the development process of a video sketching...

Modeling DNP3 Traffic Characteristics of Field Devices in SCADA Systems of the Smart Grid

Energy Technology Data Exchange (ETDEWEB)

Yang, Huan [Lehigh Univ., Bethlehem, PA (United States); Cheng, Liang [Lehigh Univ., Bethlehem, PA (United States); Chuah, Mooi Choo [Lehigh Univ., Bethlehem, PA (United States)

2017-03-08

In the generation, transmission, and distribution sectors of the smart grid, intelligence of field devices is realized by programmable logic controllers (PLCs). Many smart-grid subsystems are essentially cyber-physical energy systems (CPES): For instance, the power system process (i.e., the physical part) within a substation is monitored and controlled by a SCADA network with hosts running miscellaneous applications (i.e., the cyber part). To study the interactions between the cyber and physical components of a CPES, several co-simulation platforms have been proposed. However, the network simulators/emulators of these platforms do not include a detailed traffic model that takes into account the impacts of the execution model of PLCs on traffic characteristics. As a result, network traces generated by co-simulation only reveal the impacts of the physical process on the contents of the traffic generated by SCADA hosts, whereas the distinction between PLCs and computing nodes (e.g., a hardened computer running a process visualization application) has been overlooked. To generate realistic network traces using co-simulation for the design and evaluation of applications relying on accurate traffic profiles, it is necessary to establish a traffic model for PLCs. In this work, we propose a parameterized model for PLCs that can be incorporated into existing co-simulation platforms. We focus on the DNP3 subsystem of slave PLCs, which automates the processing of packets from the DNP3 master. To validate our approach, we extract model parameters from both the configuration and network traces of real PLCs. Simulated network traces are generated and compared against those from PLCs. Our evaluation shows that our proposed model captures the essential traffic characteristics of DNP3 slave PLCs, which can be used to extend existing co-simulation platforms and gain further insights into the behaviors of CPES.

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.

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.

Models of Social Exploitation with Special Emphasis on Slovenc Traffic Economics

Directory of Open Access Journals (Sweden)

Iztok Ostan

2005-01-01

Full Text Available In order to decipher the organisational behaviour operatingin the transport sector of the economy it is necessary to discoverthe prevalent patterns of social exploitation at work. PreliminaJyresults of a study of experienced irregular traffic studentsshow that, according to them there is no significant differencein Slovenia between exploitation in traffic and other sectors.Thus, general models of exploitation could be used to explainthe behaviour in the traffic sector. Empirical research amongSlovene students showed that according to their statements inthe 90s the managerial and capitalistic types of exploitation prevailedin Slovenia over non-exploitative types of economic behaviour.It also showed that statements of students do not differmuch from those of the general public regarding this question,nor from the statements of irregular students with extensivework experience. It was also found that there were no substantialdifferences between the statements of Italian and Slovenestudents regarding the type of exploitation operative in theircountries. Students of traffic are basically of the same opinionregarding this topic as students in general, though slightly morecritical, especially towards business managers and politicians.

Modeling annual benzene, toluene, NO2, and soot concentrations on the basis of road traffic characteristics

International Nuclear Information System (INIS)

Carr, David; Ehrenstein, Ondine von; Weiland, Stephan; Wagner, Claudia; Wellie, Oliver; Nicolai, Thomas; Mutius, Erika von

2002-01-01

The investigation of potential adverse health effects of urban traffic-related air pollution is hampered by difficulties encountered with exposure assessment. Usually public measuring sites are few and thereby do not adequately describe spatial variation of pollutant levels over an urban area. In turn, individual monitoring of pollution exposure among study subjects is laborious and expensive. We therefore investigated whether traffic characteristics can be used to adequately predict benzene, NO 2 , and soot concentrations at individual addresses of study subjects in the city area of Munich, Germany. For all road segments with expected traffic volumes of at least 4000 vehicles a day (n=1840), all vehicles were counted manually or a single weekday in 1995. The proportion of vehicles in 'stop-go' mode, n estimate of traffic jam, was determined. Furthermore, annual concentrations of benzene, NO 2 , and soot from 18 high-concentration sites means: 8.7, 65.8, and 12.9 μg/m 3 , respectively) and from 16 school sites with moderate concentrations (means: 2.6, 32.2, and 5.7 μg/m 3 , respectively) were measured from 1996 to 1998. Statistical analysis of the data was performed using components of two different statistical models recently used to predict air pollution levels in comparable settings. Two traffic characteristics, traffic volume and traffic jam percentage, adequately described air pollutant concentrations (R 2 : 0.76-0.80, P=0.0001). This study shows that air pollutant concentrations can be accurately predicted by two traffic characteristics and that these models compare favorably with other more complex models in the literature

Operation quality assessment model for video conference system

Science.gov (United States)

Du, Bangshi; Qi, Feng; Shao, Sujie; Wang, Ying; Li, Weijian

2018-01-01

Video conference system has become an important support platform for smart grid operation and management, its operation quality is gradually concerning grid enterprise. First, the evaluation indicator system covering network, business and operation maintenance aspects was established on basis of video conference system's operation statistics. Then, the operation quality assessment model combining genetic algorithm with regularized BP neural network was proposed, which outputs operation quality level of the system within a time period and provides company manager with some optimization advice. The simulation results show that the proposed evaluation model offers the advantages of fast convergence and high prediction accuracy in contrast with regularized BP neural network, and its generalization ability is superior to LM-BP neural network and Bayesian BP neural network.

Water surface modeling from a single viewpoint video.

Science.gov (United States)

Li, Chuan; Pickup, David; Saunders, Thomas; Cosker, Darren; Marshall, David; Hall, Peter; Willis, Philip

2013-07-01

We introduce a video-based approach for producing water surface models. Recent advances in this field output high-quality results but require dedicated capturing devices and only work in limited conditions. In contrast, our method achieves a good tradeoff between the visual quality and the production cost: It automatically produces a visually plausible animation using a single viewpoint video as the input. Our approach is based on two discoveries: first, shape from shading (SFS) is adequate to capture the appearance and dynamic behavior of the example water; second, shallow water model can be used to estimate a velocity field that produces complex surface dynamics. We will provide qualitative evaluation of our method and demonstrate its good performance across a wide range of scenes.

Traffic Management for Next Generation Transport Networks

DEFF Research Database (Denmark)

Yu, Hao

required by the next generation transport network to provide Quality-of-Service (QoS) guaranteed video services. Augmenting network capacity and upgrading network nodes indicate long deployment period, replacement of equipment and thus significant cost to the network service providers. This challenge may...... slacken the steps of some network operators towards providing IPTV services. In this dissertation, the topology-based hierarchical scheduling scheme is proposed to tackle the problem addressed. The scheme simplifies the deployment process by placing an intelligent switch with centralized traffic...... management functions at the edge of the network, scheduling traffic on behalf of the other nodes. The topology-based hierarchical scheduling scheme is able to provide outstanding flow isolation due to its centralized scheduling ability, which is essential for providing IPTV services. In order to reduce...

Using Video Modeling to Teach Young Children with Autism Developmentally Appropriate Play and Connected Speech

Science.gov (United States)

Scheflen, Sarah Clifford; Freeman, Stephanny F. N.; Paparella, Tanya

2012-01-01

Four children with autism were taught play skills through the use of video modeling. Video instruction was used to model play and appropriate language through a developmental sequence of play levels integrated with language techniques. Results showed that children with autism could successfully use video modeling to learn how to play appropriately…

The relative efficiency of Iranian's rural traffic police: a three-stage DEA model.

Science.gov (United States)

Rahimi, Habibollah; Soori, Hamid; Nazari, Seyed Saeed Hashemi; Motevalian, Seyed Abbas; Azar, Adel; Momeni, Eskandar; Javartani, Mehdi

2017-10-13

Road traffic Injuries (RTIs) as a health problem imposes governments to implement different interventions. Target achievement in this issue required effective and efficient measures. Efficiency evaluation of traffic police as one of the responsible administrators is necessary for resource management. Therefore, this study conducted to measure Iran's rural traffic police efficiency. This was an ecological study. To obtain pure efficiency score, three-stage DEA model was conducted with seven inputs and three output variables. At the first stage, crude efficiency score was measured with BCC-O model. Next, to extract the effects of socioeconomic, demographic, traffic count and road infrastructure as the environmental variables and statistical noise, the Stochastic Frontier Analysis (SFA) model was applied and the output values were modified according to similar environment and statistical noise conditions. Then, the pure efficiency score was measured using modified outputs and BCC-O model. In total, the efficiency score of 198 police stations from 24 provinces of 31 provinces were measured. The annual means (standard deviation) of damage, injury and fatal accidents were 247.7 (258.4), 184.9 (176.9), and 28.7 (19.5), respectively. Input averages were 5.9 (3.0) patrol teams, 0.5% (0.2) manpower proportions, 7.5 (2.9) patrol cars, 0.5 (1.3) motorcycles, 77,279.1 (46,794.7) penalties, 90.9 (2.8) cultural and educational activity score, 0.7 (2.4) speed cameras. The SFA model showed non-significant differences between police station performances and the most differences attributed to the environmental and random error. One-way main road, by road, traffic count and the number of household owning motorcycle had significant positive relations with inefficiency score. The length of freeway/highway and literacy rate variables had negative relations, significantly. Pure efficiency score was with mean of 0.95 and SD of 0.09. Iran's traffic police has potential opportunity to reduce

A new stochastic cellular automaton model on traffic flow and its jamming phase transition

International Nuclear Information System (INIS)

Sakai, Satoshi; Nishinari, Katsuhiro; Iida, Shinji

2006-01-01

A general stochastic traffic cellular automaton (CA) model, which includes the slow-to-start effect and driver's perspective, is proposed in this paper. It is shown that this model includes well-known traffic CA models such as the Nagel-Schreckenberg model, the quick-start model and the slow-to-start model as specific cases. Fundamental diagrams of this new model clearly show metastable states around the critical density even when the stochastic effect is present. We also obtain analytic expressions of the phase transition curve in phase diagrams by using approximate flow-density relations at boundaries. These phase transition curves are in excellent agreement with numerical results

Scheduling Heuristics for Live Video Transcoding on Cloud Edges

Institute of Scientific and Technical Information of China (English)

Panagiotis Oikonomou; Maria G. Koziri; Nikos Tziritas; Thanasis Loukopoulos; XU Cheng-Zhong

2017-01-01

Efficient video delivery involves the transcoding of the original sequence into various resolutions, bitrates and standards, in order to match viewers 'capabilities. Since video coding and transcoding are computationally demanding, performing a portion of these tasks at the network edges promises to decrease both the workload and network traffic towards the data centers of media provid-ers. Motivated by the increasing popularity of live casting on social media platforms, in this paper we focus on the case of live vid-eo transcoding. Specifically, we investigate scheduling heuristics that decide on which jobs should be assigned to an edge mini-datacenter and which to a backend datacenter. Through simulation experiments with different QoS requirements we conclude on the best alternative.

Modelling Vessel Traffic Service to understand resilience in everyday operations

International Nuclear Information System (INIS)

Praetorius, Gesa; Hollnagel, Erik; Dahlman, Joakim

2015-01-01

Vessel Traffic Service (VTS) is a service to promote traffic fluency and safety in the entrance to ports. This article's purpose has been to explore everyday operations of the VTS system to gain insights in how it contributes to safe and efficient traffic movements. Interviews, focus groups and an observation have been conducted to collect data about everyday operations, as well as to grasp how the VTS system adapts to changing operational conditions. The results show that work within the VTS domain is highly complex and that the two systems modelled realise their services vastly differently, which in turn affects the systems' ability to monitor, respond and anticipate. This is of great importance to consider whenever changes are planned and implemented within the VTS domain. Only if everyday operations are properly analysed and understood, it can be estimated how alterations to technology and organisation will affect the overall system performance

Traffic Management of Video on Demand: An Analysis of Investments for Improving the End User’s Quality of Experience

Directory of Open Access Journals (Sweden)

Francesca Di Pillo

2016-05-01

Full Text Available The current escalation in user demand for web contents, particularly Video on Demand (VoD, is causing a continu‐ ing increase in both the types of web traffic and the volumes of data transmitted. The greater demand arises from the new means of communication employed by individuals and companies, as well as the development of readily usable applications distributed by ‘app stores’. In this paper, we suggest that the stakeholders of a VoD frame‐ work, the Content Providers (CPs and the Internet Service Providers (telcos/ISPs, should guarantee a solid Quality of Experience (QoE to the end user through two potential investments: either in ultra-broadband (UBB or in the technologies for the acceleration of web content, known as the Content Delivery Network (CDN and Transparent Internet Caching (TIC. The aim of the paper is to analyse these investments in terms of providers' profits. The base hypothesis is that the investments are subsidized by the CPs, which, in recent years, have indeed been directing a large part of their revenues towards investments in network infrastructure.

Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model

Directory of Open Access Journals (Sweden)

Yuqi Guo

2017-08-01

Full Text Available In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM, the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.

Urban scale air quality modelling using detailed traffic emissions estimates

Science.gov (United States)

Borrego, C.; Amorim, J. H.; Tchepel, O.; Dias, D.; Rafael, S.; Sá, E.; Pimentel, C.; Fontes, T.; Fernandes, P.; Pereira, S. R.; Bandeira, J. M.; Coelho, M. C.

2016-04-01

The atmospheric dispersion of NOx and PM10 was simulated with a second generation Gaussian model over a medium-size south-European city. Microscopic traffic models calibrated with GPS data were used to derive typical driving cycles for each road link, while instantaneous emissions were estimated applying a combined Vehicle Specific Power/Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (VSP/EMEP) methodology. Site-specific background concentrations were estimated using time series analysis and a low-pass filter applied to local observations. Air quality modelling results are compared against measurements at two locations for a 1 week period. 78% of the results are within a factor of two of the observations for 1-h average concentrations, increasing to 94% for daily averages. Correlation significantly improves when background is added, with an average of 0.89 for the 24 h record. The results highlight the potential of detailed traffic and instantaneous exhaust emissions estimates, together with filtered urban background, to provide accurate input data to Gaussian models applied at the urban scale.

The Effects of Video Self-Modeling on High School Students with Emotional and Behavioral Disturbances

Science.gov (United States)

Chu, Szu-Yin; Baker, Sonia

2015-01-01

Video self-modeling has been proven to be effective with other populations with challenging behaviors, but only a few studies of video self-modeling have been conducted with high school students with emotional and behavioral disorders. This study aimed to focus on analyzing the effects of video self-modeling on four high school students with…

Improved virtual channel noise model for transform domain Wyner-Ziv video coding

DEFF Research Database (Denmark)

Huang, Xin; Forchhammer, Søren

2009-01-01

Distributed video coding (DVC) has been proposed as a new video coding paradigm to deal with lossy source coding using side information to exploit the statistics at the decoder to reduce computational demands at the encoder. A virtual channel noise model is utilized at the decoder to estimate...... the noise distribution between the side information frame and the original frame. This is one of the most important aspects influencing the coding performance of DVC. Noise models with different granularity have been proposed. In this paper, an improved noise model for transform domain Wyner-Ziv video...... coding is proposed, which utilizes cross-band correlation to estimate the Laplacian parameters more accurately. Experimental results show that the proposed noise model can improve the rate-distortion (RD) performance....

Video Self-Modelling: An Intervention for Children with Behavioural Difficulties

Science.gov (United States)

Regan, Helen; Howe, Julia

2017-01-01

There has recently been a growth in interest in the use of video technology in the practice of educational psychologists. This research explores the effects of a video self-modelling (VSM) intervention on the behaviours of a child in mainstream education using a single case study design set within a behaviourist paradigm. VSM is a behavioural…

Teaching physical activities to students with significant disabilities using video modeling.

Science.gov (United States)

Cannella-Malone, Helen I; Mizrachi, Sharona V; Sabielny, Linsey M; Jimenez, Eliseo D

2013-06-01

The objective of this study was to examine the effectiveness of video modeling on teaching physical activities to three adolescents with significant disabilities. The study implemented a multiple baseline across six physical activities (three per student): jumping rope, scooter board with cones, ladder drill (i.e., feet going in and out), ladder design (i.e., multiple steps), shuttle run, and disc ride. Additional prompt procedures (i.e., verbal, gestural, visual cues, and modeling) were implemented within the study. After the students mastered the physical activities, we tested to see if they would link the skills together (i.e., complete an obstacle course). All three students made progress learning the physical activities, but only one learned them with video modeling alone (i.e., without error correction). Video modeling can be an effective tool for teaching students with significant disabilities various physical activities, though additional prompting procedures may be needed.

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...

Software defined multi-OLT passive optical network for flexible traffic allocation

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Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Zhang, Jiawei; Li, Hui

2016-10-01

With the rapid growth of 4G mobile network and vehicular network services mobile terminal users have increasing demand on data sharing among different radio remote units (RRUs) and roadside units (RSUs). Meanwhile, commercial video-streaming, video/voice conference applications delivered through peer-to-peer (P2P) technology are still keep on stimulating the sharp increment of bandwidth demand in both business and residential subscribers. However, a significant issue is that, although wavelength division multiplexing (WDM) and orthogonal frequency division multiplexing (OFDM) technology have been proposed to fulfil the ever-increasing bandwidth demand in access network, the bandwidth of optical fiber is not unlimited due to the restriction of optical component properties and modulation/demodulation technology, and blindly increase the wavelength cannot meet the cost-sensitive characteristic of the access network. In this paper, we propose a software defined multi-OLT PON architecture to support efficient scheduling of access network traffic. By introducing software defined networking technology and wavelength selective switch into TWDM PON system in central office, multiple OLTs can be considered as a bandwidth resource pool and support flexible traffic allocation for optical network units (ONUs). Moreover, under the configuration of the control plane, ONUs have the capability of changing affiliation between different OLTs under different traffic situations, thus the inter-OLT traffic can be localized and the data exchange pressure of the core network can be released. Considering this architecture is designed to be maximum following the TWDM PON specification, the existing optical distribution network (ODN) investment can be saved and conventional EPON/GPON equipment can be compatible with the proposed architecture. What's more, based on this architecture, we propose a dynamic wavelength scheduling algorithm, which can be deployed as an application on control plane

Ranking Highlights in Personal Videos by Analyzing Edited Videos.

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Sun, Min; Farhadi, Ali; Chen, Tseng-Hung; Seitz, Steve

2016-11-01

We present a fully automatic system for ranking domain-specific highlights in unconstrained personal videos by analyzing online edited videos. A novel latent linear ranking model is proposed to handle noisy training data harvested online. Specifically, given a targeted domain such as "surfing," our system mines the YouTube database to find pairs of raw and their corresponding edited videos. Leveraging the assumption that an edited video is more likely to contain highlights than the trimmed parts of the raw video, we obtain pair-wise ranking constraints to train our model. The learning task is challenging due to the amount of noise and variation in the mined data. Hence, a latent loss function is incorporated to mitigate the issues caused by the noise. We efficiently learn the latent model on a large number of videos (about 870 min in total) using a novel EM-like procedure. Our latent ranking model outperforms its classification counterpart and is fairly competitive compared with a fully supervised ranking system that requires labels from Amazon Mechanical Turk. We further show that a state-of-the-art audio feature mel-frequency cepstral coefficients is inferior to a state-of-the-art visual feature. By combining both audio-visual features, we obtain the best performance in dog activity, surfing, skating, and viral video domains. Finally, we show that impressive highlights can be detected without additional human supervision for seven domains (i.e., skating, surfing, skiing, gymnastics, parkour, dog activity, and viral video) in unconstrained personal videos.

Accounting for anthropic energy flux of traffic in winter urban road surface temperature simulations with TEB model

Science.gov (United States)

Khalifa, A.; Marchetti, M.; Bouilloud, L.; Martin, E.; Bues, M.; Chancibaut, K.

2015-06-01

A forecast of the snowfall helps winter coordination operating services, reducing the cost of the maintenance actions, and the environmental impacts caused by an inappropriate use of de-icing. In order to determine the possible accumulation of snow on pavement, the forecast of the road surface temperature (RST) is mandatory. Physical numerical models provide such forecast, and do need an accurate description of the infrastructure along with meteorological parameters. The objective of this study was to build a reliable urban RST forecast with a detailed integration of traffic in the Town Energy Balance (TEB) numerical model for winter maintenance. The study first consisted in generating a physical and consistent description of traffic in the model with all the energy interactions, with two approaches to evaluate the traffic incidence on RST. Experiments were then conducted to measure the traffic effect on RST increase with respect to non circulated areas. These field data were then used for comparison with forecast provided by this traffic-implemented TEB version.

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.

Adaptive Noise Model for Transform Domain Wyner-Ziv Video using Clustering of DCT Blocks

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