Sparsity-based shrinkage approach for practicability improvement of H-LBP-based edge extraction

Energy Technology Data Exchange (ETDEWEB)

Zhao, Chenyi [School of Physics, Northeast Normal University, Changchun 130024 (China); Qiao, Shuang, E-mail: qiaos810@nenu.edu.cn [School of Physics, Northeast Normal University, Changchun 130024 (China); Sun, Jianing, E-mail: sunjn118@nenu.edu.cn [School of Mathematics and Statistics, Northeast Normal University, Changchun 130024 (China); Zhao, Ruikun; Wu, Wei [Jilin Cancer Hospital, Changchun 130021 (China)

2016-07-21

The local binary pattern with H function (H-LBP) technique enables fast and efficient edge extraction in digital radiography. In this paper, we reformulate the model of H-LBP and propose a novel sparsity-based shrinkage approach, in which the threshold can be adapted to the data sparsity. Using this model, we upgrade fast H-LBP framework and apply it to real digital radiography. The experiments show that the method improved using the new shrinkage approach can avoid elaborately artificial modulation of parameters and possess greater robustness in edge extraction compared with the other current methods without increasing processing time. - Highlights: • An novel sparsity-based shrinkage approach for edge extraction on digital radiography is proposed. • The threshold of SS-LBP can be adaptive to the data sparsity. • SS-LBP is the development of AH-LBP and H-LBP. • Without boosting processing time and losing processing efficiency, SS-LBP can avoid elaborately artificial modulation of parameters provides. • SS-LBP has more robust performance in edge extraction compared with the existing methods.

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

OpenAIRE

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

2015-01-01

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

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

Directory of Open Access Journals (Sweden)

Shouyi Yin

2015-01-01

Full Text Available Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Mobile Phone Based RIMS for Traffic Control a Case Study of Tanzania

OpenAIRE

Angela-Aida Karugila Runyoro; Jesuk Ko

2015-01-01

Vehicles saturation in transportation infrastructure causes traffic congestion, accidents, transportation delays and environment pollution. This problem can be resolved with proper management of traffic flow. Existing traffic management systems are challenged on capturing and processing real-time road data from wide area road networks. The main purpose of this study is to address the gap by implementing a mobile phone based Road Information Management System. The proposed...

Fast Drawing of Traffic Sign Using Mobile Mapping System

Science.gov (United States)

Yao, Q.; Tan, B.; Huang, Y.

2016-06-01

Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS) becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare event of having a

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

OpenAIRE

Yan Ge

2014-01-01

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

A Cooperative Traffic Control of Vehicle–Intersection (CTCVI) for the Reduction of Traffic Delays and Fuel Consumption

Science.gov (United States)

Li, Jinjian; Dridi, Mahjoub; El-Moudni, Abdellah

2016-01-01

The problem of reducing traffic delays and decreasing fuel consumption simultaneously in a network of intersections without traffic lights is solved by a cooperative traffic control algorithm, where the cooperation is executed based on the connection of Vehicle-to-Infrastructure (V2I). This resolution of the problem contains two main steps. The first step concerns the itinerary of which intersections are chosen by vehicles to arrive at their destination from their starting point. Based on the principle of minimal travel distance, each vehicle chooses its itinerary dynamically based on the traffic loads in the adjacent intersections. The second step is related to the following proposed cooperative procedures to allow vehicles to pass through each intersection rapidly and economically: on one hand, according to the real-time information sent by vehicles via V2I in the edge of the communication zone, each intersection applies Dynamic Programming (DP) to cooperatively optimize the vehicle passing sequence with minimal traffic delays so that the vehicles may rapidly pass the intersection under the relevant safety constraints; on the other hand, after receiving this sequence, each vehicle finds the optimal speed profiles with the minimal fuel consumption by an exhaustive search. The simulation results reveal that the proposed algorithm can significantly reduce both travel delays and fuel consumption compared with other papers under different traffic volumes. PMID:27999333

A Cooperative Traffic Control of Vehicle–Intersection (CTCVI for the Reduction of Traffic Delays and Fuel Consumption

Directory of Open Access Journals (Sweden)

Jinjian Li

2016-12-01

Full Text Available The problem of reducing traffic delays and decreasing fuel consumption simultaneously in a network of intersections without traffic lights is solved by a cooperative traffic control algorithm, where the cooperation is executed based on the connection of Vehicle-to-Infrastructure (V2I. This resolution of the problem contains two main steps. The first step concerns the itinerary of which intersections are chosen by vehicles to arrive at their destination from their starting point. Based on the principle of minimal travel distance, each vehicle chooses its itinerary dynamically based on the traffic loads in the adjacent intersections. The second step is related to the following proposed cooperative procedures to allow vehicles to pass through each intersection rapidly and economically: on one hand, according to the real-time information sent by vehicles via V2I in the edge of the communication zone, each intersection applies Dynamic Programming (DP to cooperatively optimize the vehicle passing sequence with minimal traffic delays so that the vehicles may rapidly pass the intersection under the relevant safety constraints; on the other hand, after receiving this sequence, each vehicle finds the optimal speed profiles with the minimal fuel consumption by an exhaustive search. The simulation results reveal that the proposed algorithm can significantly reduce both travel delays and fuel consumption compared with other papers under different traffic volumes.

Road Traffic Congestion Management Based on a Search-Allocation Approach

Directory of Open Access Journals (Sweden)

Raiyn Jamal

2017-03-01

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

Fast and accurate edge orientation processing during object manipulation

Science.gov (United States)

Flanagan, J Randall; Johansson, Roland S

2018-01-01

Quickly and accurately extracting information about a touched object’s orientation is a critical aspect of dexterous object manipulation. However, the speed and acuity of tactile edge orientation processing with respect to the fingertips as reported in previous perceptual studies appear inadequate in these respects. Here we directly establish the tactile system’s capacity to process edge-orientation information during dexterous manipulation. Participants extracted tactile information about edge orientation very quickly, using it within 200 ms of first touching the object. Participants were also strikingly accurate. With edges spanning the entire fingertip, edge-orientation resolution was better than 3° in our object manipulation task, which is several times better than reported in previous perceptual studies. Performance remained impressive even with edges as short as 2 mm, consistent with our ability to precisely manipulate very small objects. Taken together, our results radically redefine the spatial processing capacity of the tactile system. PMID:29611804

Fixed Point Learning Based Intelligent Traffic Control System

Science.gov (United States)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

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

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

Implementation of a FPGA-Based Feature Detection and Networking System for Real-time Traffic Monitoring

OpenAIRE

Chen, Jieshi; Schafer, Benjamin Carrion; Ho, Ivan Wang-Hei

2016-01-01

With the growing demand of real-time traffic monitoring nowadays, software-based image processing can hardly meet the real-time data processing requirement due to the serial data processing nature. In this paper, the implementation of a hardware-based feature detection and networking system prototype for real-time traffic monitoring as well as data transmission is presented. The hardware architecture of the proposed system is mainly composed of three parts: data collection, feature detection,...

Highway traffic noise prediction based on GIS

Science.gov (United States)

Zhao, Jianghua; Qin, Qiming

2014-05-01

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

FAST DRAWING OF TRAFFIC SIGN USING MOBILE MAPPING SYSTEM

Directory of Open Access Journals (Sweden)

Q. Yao

2016-06-01

Full Text Available Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare

Real-time traffic sign recognition based on a general purpose GPU and deep-learning.

Science.gov (United States)

Lim, Kwangyong; Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).

Singularity Processing Method of Microstrip Line Edge Based on LOD-FDTD

Directory of Open Access Journals (Sweden)

Lei Li

2014-01-01

Full Text Available In order to improve the performance of the accuracy and efficiency for analyzing the microstrip structure, a singularity processing method is proposed theoretically and experimentally based on the fundamental locally one-dimensional finite difference time domain (LOD-FDTD with second-order temporal accuracy (denoted as FLOD2-FDTD. The proposed method can highly improve the performance of the FLOD2-FDTD even when the conductor is embedded into more than half of the cell by the coordinate transformation. The experimental results showed that the proposed method can achieve higher accuracy when the time step size is less than or equal to 5 times of that the Courant-Friedrich-Levy (CFL condition allowed. In comparison with the previously reported methods, the proposed method for calculating electromagnetic field near microstrip line edge not only improves the efficiency, but also can provide a higher accuracy.

An Efficient MapReduce-Based Parallel Clustering Algorithm for Distributed Traffic Subarea Division

Directory of Open Access Journals (Sweden)

Dawen Xia

2015-01-01

Full Text Available Traffic subarea division is vital for traffic system management and traffic network analysis in intelligent transportation systems (ITSs. Since existing methods may not be suitable for big traffic data processing, this paper presents a MapReduce-based Parallel Three-Phase K-Means (Par3PKM algorithm for solving traffic subarea division problem on a widely adopted Hadoop distributed computing platform. Specifically, we first modify the distance metric and initialization strategy of K-Means and then employ a MapReduce paradigm to redesign the optimized K-Means algorithm for parallel clustering of large-scale taxi trajectories. Moreover, we propose a boundary identifying method to connect the borders of clustering results for each cluster. Finally, we divide traffic subarea of Beijing based on real-world trajectory data sets generated by 12,000 taxis in a period of one month using the proposed approach. Experimental evaluation results indicate that when compared with K-Means, Par2PK-Means, and ParCLARA, Par3PKM achieves higher efficiency, more accuracy, and better scalability and can effectively divide traffic subarea with big taxi trajectory data.

Influence of Intra-cell Traffic on the Output Power of Base Station in GSM

Directory of Open Access Journals (Sweden)

M. Mileusnic

2014-06-01

Full Text Available In this paper we analyze the influence of intracell traffic in a GSM cell on the base station output power. It is proved that intracell traffic increases this power. If offered traffic is small, the increase of output power is equal to the part of intracell traffic. When the offered traffic and, as the result, call loss increase, the increase of output power becomes less. The results of calculation are verified by the computer simulation of traffic process in the GSM cell. The calculation and the simulation consider the uniform distribution of mobile users in the cell, but the conclusions are of a general nature.

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

Science.gov (United States)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

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.

A new edge detection algorithm based on Canny idea

Science.gov (United States)

Feng, Yingke; Zhang, Jinmin; Wang, Siming

2017-10-01

The traditional Canny algorithm has poor self-adaptability threshold, and it is more sensitive to noise. In order to overcome these drawbacks, this paper proposed a new edge detection method based on Canny algorithm. Firstly, the media filtering and filtering based on the method of Euclidean distance are adopted to process it; secondly using the Frei-chen algorithm to calculate gradient amplitude; finally, using the Otsu algorithm to calculate partial gradient amplitude operation to get images of thresholds value, then find the average of all thresholds that had been calculated, half of the average is high threshold value, and the half of the high threshold value is low threshold value. Experiment results show that this new method can effectively suppress noise disturbance, keep the edge information, and also improve the edge detection accuracy.

Developing a Web-Based Advisory Expert System for Implementing Traffic Calming Strategies

Directory of Open Access Journals (Sweden)

Amir Falamarzi

2014-01-01

Full Text Available Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic safety problems. This expert system is developed to fill the gap between the traffic safety experts and people who seek to employ traffic calming strategies including decision makers, engineers, and students. In order to build the expert system, examining sources related to traffic calming studies as well as interviewing with domain experts have been carried out. The system includes above 150 rules and 200 images for different types of measures. The system has three main functions including classifying traffic calming measures, prioritizing traffic calming strategies, and presenting solutions for different traffic safety problems. Verifying, validating processes, and comparing the system with similar works have shown that the system is consistent and acceptable for practical uses. Finally, some recommendations for improving the system are presented.

Betweenness centrality and its applications from modeling traffic flows to network community detection

Science.gov (United States)

Ren, Yihui

As real-world complex networks are heterogeneous structures, not all their components such as nodes, edges and subgraphs carry the same role or importance in the functions performed by the networks: some elements are more critical than others. Understanding the roles of the components of a network is crucial for understanding the behavior of the network as a whole. One the most basic function of networks is transport; transport of vehicles/people, information, materials, forces, etc., and these quantities are transported along edges between source and destination nodes. For this reason, network path-based importance measures, also called centralities, play a crucial role in the understanding of the transport functions of the network and the network's structural and dynamical behavior in general. In this thesis we study the notion of betweenness centrality, which measures the fraction of lowest-cost (or shortest) paths running through a network component, in particular through a node or an edge. High betweenness centrality nodes/edges are those that will be frequently used by the entities transported through the network and thus they play a key role in the overall transport properties of the network. In the first part of the thesis we present a first-principles based method for traffic prediction using a cost-based generalization of the radiation model (emission/absorbtion model) for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. We then focus on studying the extent of changes in traffic flows in the wake of a localized damage or alteration to the

Modified Pagerank Algorithm Based Real-Time Metropolitan Vehicular Traffic Routing Using GPS Crowdsourcing Data

Directory of Open Access Journals (Sweden)

Adithya Guru Vaishnav.S

2015-08-01

Full Text Available This paper aims at providing a theoretical framework to find an optimized route from any source to destination considering the real-time traffic congestion issues. The distance of various possible routes from the source and destination are calculated and a PathRank is allocated in the descending order of distance to each possible path. Each intermediate locations are considered as nodes of a graph and the edges are represented by real-time traffic flow monitored using GoogleMaps GPS crowdsourcing data. The Page Rank is calculated for each intermediate node. From the values of PageRank and PathRank the minimum sum term is used to find an optimized route with minimal trade-off between shortest path and real-time traffic.

Self-Adapting Routing Overlay Network for Frequently Changing Application Traffic in Content-Based Publish/Subscribe System

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Meng Chi

2014-01-01

Full Text Available In the large-scale distributed simulation area, the topology of the overlay network cannot always rapidly adapt to frequently changing application traffic to reduce the overall traffic cost. In this paper, we propose a self-adapting routing strategy for frequently changing application traffic in content-based publish/subscribe system. The strategy firstly trains the traffic information and then uses this training information to predict the application traffic in the future. Finally, the strategy reconfigures the topology of the overlay network based on this predicting information to reduce the overall traffic cost. A predicting path is also introduced in this paper to reduce the reconfiguration numbers in the process of the reconfigurations. Compared to other strategies, the experimental results show that the strategy proposed in this paper could reduce the overall traffic cost of the publish/subscribe system in less reconfigurations.

D0 data processing within EDG/LCG

International Nuclear Information System (INIS)

Harenberg, Torsten; Wuppertal U.; Bos, Kors; NIKHEF, Amsterdam; Byrom, Rob; Fisher, Steve; Rutherford; Groep, David; van Leeuwen, Willem; NIKHEF, Amsterdam; Mattig, Peter; Wuppertal U.; Templon, Jeff; NIKHEF, Amsterdam

2004-01-01

In September 2003, the D0 experiment at TEvatron has launched a reprocessing effort. In total 519,212,822 of the experiment's events have been reprocessed to use the new perceptions of the detector's behavior. Out of these events 97,619,114 have been reprocessed at remote sites. For the first time, the European DataGRID has been used to re-process a part of these events as an evaluation of the EDG application testbed. They used EDG's own R-GMA database for monitoring and bookkeeping and constructed four tables: (1) submission table--records the submission of jobs to the Resource Broker; (2) job start table--holds the time the job started on a Worker Node together with process ID and many more; (3) job end table--information is published immediately before the job stops; and (4) command table--a command list table for debugging purposes. As D0 has its own data management system called ''SAM'', some sort of channel between SAM and the EDG data management system is required. The approach used is shown to the left, were a certain storage area, physically present on a back-end server machine, is visible both from a SAM-enabled machine (''SAM station'') and from EDG machines at the same site. This has bene achieved at NIKHEF. The D0 software has been adapted to run in the EDG framework. Only a few changes has to be made. Missing libraries were included and some extra packages were shipped (pyxml and Python 2.1). However, arounding wrapper scripts were written to handle the in- and output and put/get it from/to EDG's Data Management System (DMS)

Actinide L-line ED-XRF and Hybrid K-edge Densitometer Spectra Processing

International Nuclear Information System (INIS)

Esbelin, E.

2015-01-01

The analysis laboratory in the CEA Atalante complex at Marcoule (France) performs numerous R and D studies carried out in glove-boxes or in hot cells. Most of the samples are measured in liquid phase, aqueous or organic. The concentration of the main actinides of interest (U, Np, Pu, Am and Cm) are determined by XRF in a hot cell via their L-line X-ray between 13 and 15 keV. In order to limit the counting rate of many radioactive emitters (X-ray and gamma emitters) in the analysis solution and the continuous spectrum, a graphite monochromator is placed between the sample and detector. Commercial or free, the software packages available for processing X-ray spectra are designed and dedicated to a specific instrument and/or do not take into account the specific feature of our system, in other words, the presence of a monochromator. Therefore, a new X-ray analysis software programme was developed for this particular system which takes into account matrix effects corrections. For sample with U and/or Pu in high concentrations, the hybrid K-edge densitometer is used. A new software programme was also developed. For K-edge densitometry spectra processing, no calibration process is used. Spectra processing is based on theoretical equation and uses XCOM database for mass attenuation coefficients. Measured spectra on K-edge densitometer of Rokkasho Safeguards Analytical Laboratory were processed with this software and a very good agreement was found with IDTIMS results. The new graphical user interface allows to manually correct the defined edge. For the XRF spectra processing, new algorithms are used to define the base line and to find/integrate peaks. With these two analytical devices in laboratory, U and Pu concentrations can be measured from 0.5 mg/l to several hundred of g/l. (author)

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...

A FAST AND ROBUST ALGORITHM FOR ROAD EDGES EXTRACTION FROM LIDAR DATA

Directory of Open Access Journals (Sweden)

K. Qiu

2016-06-01

Full Text Available Fast mapping of roads plays an important role in many geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance. How to extract various road edges fast and robustly is a challenging task. In this paper, we present a fast and robust algorithm for the automatic road edges extraction from terrestrial mobile LiDAR data. The algorithm is based on a key observation: most roads around edges have difference in elevation and road edges with pavement are seen in two different planes. In our algorithm, we firstly extract a rough plane based on RANSAC algorithm, and then multiple refined planes which only contains pavement are extracted from the rough plane. The road edges are extracted based on these refined planes. In practice, there is a serious problem that the rough and refined planes usually extracted badly due to rough roads and different density of point cloud. To eliminate the influence of rough roads, the technology which is similar with the difference of DSM (digital surface model and DTM (digital terrain model is used, and we also propose a method which adjust the point clouds to a similar density to eliminate the influence of different density. Experiments show the validities of the proposed method with multiple datasets (e.g. urban road, highway, and some rural road. We use the same parameters through the experiments and our algorithm can achieve real-time processing speeds.

Air Traffic Management Research at NASA Ames

Science.gov (United States)

Davis, Thomas J.

2012-01-01

The Aviation Systems Division at the NASA Ames Research Center conducts leading edge research in air traffic management concepts and technologies. This overview will present concepts and simulation results for research in traffic flow management, safe and efficient airport surface operations, super density terminal area operations, separation assurance and system wide modeling and simulation. A brief review of the ongoing air traffic management technology demonstration (ATD-1) will also be presented. A panel discussion, with Mr. Davis serving as a panelist, on air traffic research will follow the briefing.

Processes mediating expertise in air traffic control

NARCIS (Netherlands)

Van Meeuwen, Ludo; Jarodzka, Halszka; Brand-Gruwel, Saskia; Van Merriënboer, Jeroen; De Bock, Jeano; Kirschner, Paul A.

2011-01-01

Van Meeuwen, L. W., Jarodzka, H., Brand-Gruwel, S., Van Merriënboer, J. J. G., De Bock, J. J. P. R., & Kirschner, P. A. (2010, September). Processes mediating expertise in air traffic control. Poster presented at the European Association for Aviation Psychology Conference, Budapest.

Study on the Road Traffic Survey System Based on Micro-ferromagnetic Induction Coil Sensor

Directory of Open Access Journals (Sweden)

Liang Tong

2014-05-01

Full Text Available Road traffic information is the basis of road traffic management and control. Due to the special design of the sensor coil and ferromagnetic core, traffic survey system which uses micro ferromagnetic inductive coil vehicle detector, not only has the features of small size, simple installation and little road surface damage, but also has the advantages of output signal strength, simple signal processing circuit and obvious characteristics for output waveform corresponding vehicle feature. Based on the introduction of the sensor working principle, the construction of hardware and signal processing circuit for the traffic survey system is described in detail in the paper. Combined with the characteristics of the sensor output waveform, adaptive nearest neighbor clustering RBF neural network algorithm used to classify the vehicles is proposed and verified by experimental method. The result has a high vehicle classification rate and demonstrates the feasibility of the system.

Spatial correlation analysis of urban traffic state under a perspective of community detection

Science.gov (United States)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

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.

An auxiliary graph based dynamic traffic grooming algorithm in spatial division multiplexing enabled elastic optical networks with multi-core fibers

Science.gov (United States)

Zhao, Yongli; Tian, Rui; Yu, Xiaosong; Zhang, Jiawei; Zhang, Jie

2017-03-01

A proper traffic grooming strategy in dynamic optical networks can improve the utilization of bandwidth resources. An auxiliary graph (AG) is designed to solve the traffic grooming problem under a dynamic traffic scenario in spatial division multiplexing enabled elastic optical networks (SDM-EON) with multi-core fibers. Five traffic grooming policies achieved by adjusting the edge weights of an AG are proposed and evaluated through simulation: maximal electrical grooming (MEG), maximal optical grooming (MOG), maximal SDM grooming (MSG), minimize virtual hops (MVH), and minimize physical hops (MPH). Numeric results show that each traffic grooming policy has its own features. Among different traffic grooming policies, an MPH policy can achieve the lowest bandwidth blocking ratio, MEG can save the most transponders, and MSG can obtain the fewest cores for each request.

Expanding the Use of Time-Based Metering: Multi-Center Traffic Management Advisor

Science.gov (United States)

Landry, Steven J.; Farley, Todd; Hoang, Ty

2005-01-01

Time-based metering is an efficient air traffic management alternative to the more common practice of distance-based metering (or "miles-in-trail spacing"). Despite having demonstrated significant operational benefit to airspace users and service providers, time-based metering is used in the United States for arrivals to just nine airports and is not used at all for non-arrival traffic flows. The Multi-Center Traffic Management Advisor promises to bring time-based metering into the mainstream of air traffic management techniques. Not constrained to operate solely on arrival traffic, Multi-Center Traffic Management Advisor is flexible enough to work in highly congested or heavily partitioned airspace for any and all traffic flows in a region. This broader and more general application of time-based metering is expected to bring the operational benefits of time-based metering to a much wider pool of beneficiaries than is possible with existing technology. It also promises to facilitate more collaborative traffic management on a regional basis. This paper focuses on the operational concept of the Multi-Center Traffic Management Advisor, touching also on its system architecture, field test results, and prospects for near-term deployment to the United States National Airspace System.

Physics-based edge evaluation for improved color constancy

NARCIS (Netherlands)

Gijsenij, A.; Gevers, T.; van de Weijer, J.

2009-01-01

Edge-based color constancy makes use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as shadow, geometry, material and highlight edges. These different edge types may have a distinctive influence on the performance of the illuminant

Processes mediating expertise in air traffic control

NARCIS (Netherlands)

Van Meeuwen, Ludo; Jarodzka, Halszka; Brand-Gruwel, Saskia; Van Merriënboer, Jeroen; De Bock, Jeano; Kirschner, Paul A.

2010-01-01

Van Meeuwen, L., Jarodzka, H., Brand-Gruwel, S., Van Merriënboer, J. J. G., De Bock, J. J. P. R., & Kirschner, P. A. (2010, August). Processes mediating expertise in air traffic control. Meeting of the EARLI SIG6/7 Instructional Design and Learning and Instruction with Computers, Ulm, Germany.

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.

Accurate Multisteps Traffic Flow Prediction Based on SVM

Directory of Open Access Journals (Sweden)

Zhang Mingheng

2013-01-01

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

A GPS-based Real-time Road Traffic Monitoring System

Science.gov (United States)

Tanti, Kamal Kumar

In recent years, monitoring systems are astonishingly inclined towards ever more automatic; reliably interconnected, distributed and autonomous operation. Specifically, the measurement, logging, data processing and interpretation activities may be carried out by separate units at different locations in near real-time. The recent evolution of mobile communication devices and communication technologies has fostered a growing interest in the GIS & GPS-based location-aware systems and services. This paper describes a real-time road traffic monitoring system based on integrated mobile field devices (GPS/GSM/IOs) working in tandem with advanced GIS-based application software providing on-the-fly authentications for real-time monitoring and security enhancement. The described system is developed as a fully automated, continuous, real-time monitoring system that employs GPS sensors and Ethernet and/or serial port communication techniques are used to transfer data between GPS receivers at target points and a central processing computer. The data can be processed locally or remotely based on the requirements of client’s satisfaction. Due to the modular architecture of the system, other sensor types may be supported with minimal effort. Data on the distributed network & measurements are transmitted via cellular SIM cards to a Control Unit, which provides for post-processing and network management. The Control Unit may be remotely accessed via an Internet connection. The new system will not only provide more consistent data about the road traffic conditions but also will provide methods for integrating with other Intelligent Transportation Systems (ITS). For communication between the mobile device and central monitoring service GSM technology is used. The resulting system is characterized by autonomy, reliability and a high degree of automation.

Big-data-based edge biomarkers: study on dynamical drug sensitivity and resistance in individuals.

Science.gov (United States)

Zeng, Tao; Zhang, Wanwei; Yu, Xiangtian; Liu, Xiaoping; Li, Meiyi; Chen, Luonan

2016-07-01

Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically 'small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as 'large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression

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

Directory of Open Access Journals (Sweden)

Hua-pu Lu

2015-01-01

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

Fuzzy Logic Based Autonomous Traffic Control System

Directory of Open Access Journals (Sweden)

Muhammad ABBAS

2012-01-01

Full Text Available The aim of this paper is to design and implement fuzzy logic based traffic light Control system to solve the traffic congestion issues. In this system four input parameters: Arrival, Queue, Pedestrian and Emergency Vehicle and two output parameters: Extension in Green and Pedestrian Signals are used. Using Fuzzy Rule Base, the system extends or terminates the Green Signal according to the Traffic situation at the junction. On the presence of emergency vehicle, the system decides which signal(s should be red and how much an extension should be given to Green Signal for Emergency Vehicle. The system also monitors the density of people and makes decisions accordingly. In order to verify the proposed design algorithm MATLAB simulation is adopted and results obtained show concurrency to the calculated values according to the Mamdani Model of the Fuzzy Control System.

Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

Directory of Open Access Journals (Sweden)

Yiliang Zeng

Full Text Available Due to the rapid development of motor vehicle Driver Assistance Systems (DAS, the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

Accelerated H-LBP-based edge extraction method for digital radiography

Energy Technology Data Exchange (ETDEWEB)

Qiao, Shuang; Zhao, Chen-yi; Huang, Ji-peng [School of Physics, Northeast Normal University, Changchun 130024 (China); Sun, Jia-ning, E-mail: sunjn118@nenu.edu.cn [School of Mathematics and Statistics, Northeast Normal University, Changchun 130024 (China)

2015-01-11

With the goal of achieving real time and efficient edge extraction for digital radiography, an accelerated H-LBP-based edge extraction method (AH-LBP) is presented in this paper by improving the existing framework of local binary pattern with the H function (H-LBP). Since the proposed method avoids computationally expensive operations with no loss of quality, it possesses much lower computational complexity than H-LBP. Experimental results on real radiographies show desirable performance of our method. - Highlights: • An accelerated H-LBP method for edge extraction on digital radiography is proposed. • The novel AH-LBP relies on numerical analysis of the existing H-LBP method. • Aiming at accelerating, H-LBP is reformulated as a direct binary processing. • AH-LBP provides the same edge extraction result as H-LBP does. • AH-LBP has low computational complexity satisfying real time requirements.

CATS-based Air Traffic Controller Agents

Science.gov (United States)

Callantine, Todd J.

2002-01-01

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human

A safety assessment methodology applied to CNS/ATM-based air traffic control system

Energy Technology Data Exchange (ETDEWEB)

Vismari, Lucio Flavio, E-mail: lucio.vismari@usp.b [Safety Analysis Group (GAS), School of Engineering at University of Sao Paulo (Poli-USP), Av. Prof. Luciano Gualberto, Trav.3, n.158, Predio da Engenharia de Eletricidade, Sala C2-32, CEP 05508-900, Sao Paulo (Brazil); Batista Camargo Junior, Joao, E-mail: joaocamargo@usp.b [Safety Analysis Group (GAS), School of Engineering at University of Sao Paulo (Poli-USP), Av. Prof. Luciano Gualberto, Trav.3, n.158, Predio da Engenharia de Eletricidade, Sala C2-32, CEP 05508-900, Sao Paulo (Brazil)

2011-07-15

In the last decades, the air traffic system has been changing to adapt itself to new social demands, mainly the safe growth of worldwide traffic capacity. Those changes are ruled by the Communication, Navigation, Surveillance/Air Traffic Management (CNS/ATM) paradigm , based on digital communication technologies (mainly satellites) as a way of improving communication, surveillance, navigation and air traffic management services. However, CNS/ATM poses new challenges and needs, mainly related to the safety assessment process. In face of these new challenges, and considering the main characteristics of the CNS/ATM, a methodology is proposed at this work by combining 'absolute' and 'relative' safety assessment methods adopted by the International Civil Aviation Organization (ICAO) in ICAO Doc.9689 , using Fluid Stochastic Petri Nets (FSPN) as the modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed (in analysis) and the legacy system models. To demonstrate its usefulness, the proposed methodology was applied to the 'Automatic Dependent Surveillance-Broadcasting' (ADS-B) based air traffic control system. As conclusions, the proposed methodology assured to assess CNS/ATM system safety properties, in which FSPN formalism provides important modeling capabilities, and discrete event simulation allowing the estimation of the desired safety metric.

A safety assessment methodology applied to CNS/ATM-based air traffic control system

International Nuclear Information System (INIS)

Vismari, Lucio Flavio; Batista Camargo Junior, Joao

2011-01-01

In the last decades, the air traffic system has been changing to adapt itself to new social demands, mainly the safe growth of worldwide traffic capacity. Those changes are ruled by the Communication, Navigation, Surveillance/Air Traffic Management (CNS/ATM) paradigm , based on digital communication technologies (mainly satellites) as a way of improving communication, surveillance, navigation and air traffic management services. However, CNS/ATM poses new challenges and needs, mainly related to the safety assessment process. In face of these new challenges, and considering the main characteristics of the CNS/ATM, a methodology is proposed at this work by combining 'absolute' and 'relative' safety assessment methods adopted by the International Civil Aviation Organization (ICAO) in ICAO Doc.9689 , using Fluid Stochastic Petri Nets (FSPN) as the modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed (in analysis) and the legacy system models. To demonstrate its usefulness, the proposed methodology was applied to the 'Automatic Dependent Surveillance-Broadcasting' (ADS-B) based air traffic control system. As conclusions, the proposed methodology assured to assess CNS/ATM system safety properties, in which FSPN formalism provides important modeling capabilities, and discrete event simulation allowing the estimation of the desired safety metric.

Traffic speed data imputation method based on tensor completion.

Science.gov (United States)

Ran, Bin; Tan, Huachun; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

2015-01-01

Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

An efficient statistical-based approach for road traffic congestion monitoring

KAUST Repository

Abdelhafid, Zeroual

2017-12-14

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

An efficient statistical-based approach for road traffic congestion monitoring

KAUST Repository

Abdelhafid, Zeroual; Harrou, Fouzi; Sun, Ying

2017-01-01

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

Nonreference Medical Image Edge Map Measure

Directory of Open Access Journals (Sweden)

Karen Panetta

2014-01-01

Full Text Available Edge detection is a key step in medical image processing. It is widely used to extract features, perform segmentation, and further assist in diagnosis. A poor quality edge map can result in false alarms and misses in cancer detection algorithms. Therefore, it is necessary to have a reliable edge measure to assist in selecting the optimal edge map. Existing reference based edge measures require a ground truth edge map to evaluate the similarity between the generated edge map and the ground truth. However, the ground truth images are not available for medical images. Therefore, a nonreference edge measure is ideal for medical image processing applications. In this paper, a nonreference reconstruction based edge map evaluation (NREM is proposed. The theoretical basis is that a good edge map keeps the structure and details of the original image thus would yield a good reconstructed image. The NREM is based on comparing the similarity between the reconstructed image with the original image using this concept. The edge measure is used for selecting the optimal edge detection algorithm and optimal parameters for the algorithm. Experimental results show that the quantitative evaluations given by the edge measure have good correlations with human visual analysis.

Traffic Speed Data Imputation Method Based on Tensor Completion

Directory of Open Access Journals (Sweden)

Bin Ran

2015-01-01

Full Text Available Traffic speed data plays a key role in Intelligent Transportation Systems (ITS; however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS. In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC, an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

Leveraging spatial abstraction in traffic analysis and forecasting with visual analytics

OpenAIRE

Andrienko, N.; Andrienko, G.; Rinzivillo, S.

2016-01-01

A spatially abstracted transportation network is a graph where nodes are territory compartments (areas in geographic space) and edges, or links, are abstract constructs, each link representing all possible paths between two neighboring areas. By applying visual analytics techniques to vehicle traffic data from different territories, we discovered that the traffic intensity (a.k.a. traffic flow or traffic flux) and the mean velocity are interrelated in a spatially abstracted transportation net...

Theoretical Aspects of Erroneous Actions During the Process of Decision Making by Air Traffic Control

Directory of Open Access Journals (Sweden)

Andersone Silva

2017-08-01

Full Text Available The Theoretical Aspects of Erroneous Actions During the Process of Decision Making by Air Traffic Control evaluates the factors affecting the operational decision-making of a human air traffic controller, interacting in a dynamic environment with the flight crew, surrounding aircraft traffic and environmental conditions of the airspace. This article reviews the challenges of air traffic control in different conditions, ranging from normal and complex to emergency and catastrophic. Workload factors and operating conditions make an impact on air traffic controllers’ decision-making. The proposed model compares various operating conditions within an assumed air traffic control environment subsequently comparing them against a theoretically “perfect” air traffic control system. A mathematical model of flight safety assessment has been proposed for the quantitative assessment of various hazards arising during the process of Air Traffic Control. The model assumes events of various severity and probability ranging from high frequency and low severity up to less likely and catastrophic ones. Certain limitations of the model have been recognised and further improvements for effective hazard evaluation have been suggested.

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.

Assessing forest vulnerability to climate warming using a process-based model of tree growth: bad prospects for rear-edges.

Science.gov (United States)

Sánchez-Salguero, Raúl; Camarero, Jesus Julio; Gutiérrez, Emilia; González Rouco, Fidel; Gazol, Antonio; Sangüesa-Barreda, Gabriel; Andreu-Hayles, Laia; Linares, Juan Carlos; Seftigen, Kristina

2017-07-01

Growth models can be used to assess forest vulnerability to climate warming. If global warming amplifies water deficit in drought-prone areas, tree populations located at the driest and southernmost distribution limits (rear-edges) should be particularly threatened. Here, we address these statements by analyzing and projecting growth responses to climate of three major tree species (silver fir, Abies alba; Scots pine, Pinus sylvestris; and mountain pine, Pinus uncinata) in mountainous areas of NE Spain. This region is subjected to Mediterranean continental conditions, it encompasses wide climatic, topographic and environmental gradients, and, more importantly, it includes rear-edges of the continuous distributions of these tree species. We used tree-ring width data from a network of 110 forests in combination with the process-based Vaganov-Shashkin-Lite growth model and climate-growth analyses to forecast changes in tree growth during the 21st century. Climatic projections were based on four ensembles CO 2 emission scenarios. Warm and dry conditions during the growing season constrain silver fir and Scots pine growth, particularly at the species rear-edge. By contrast, growth of high-elevation mountain pine forests is enhanced by climate warming. The emission scenario (RCP 8.5) corresponding to the most pronounced warming (+1.4 to 4.8 °C) forecasted mean growth reductions of -10.7% and -16.4% in silver fir and Scots pine, respectively, after 2050. This indicates that rising temperatures could amplify drought stress and thus constrain the growth of silver fir and Scots pine rear-edge populations growing at xeric sites. Contrastingly, mountain pine growth is expected to increase by +12.5% due to a longer and warmer growing season. The projections of growth reduction in silver fir and Scots pine portend dieback and a contraction of their species distribution areas through potential local extinctions of the most vulnerable driest rear-edge stands. Our modeling

A Feature Selection Method for Large-Scale Network Traffic Classification Based on Spark

Directory of Open Access Journals (Sweden)

Yong Wang

2016-02-01

Full Text Available Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce framework have been proposed, the execution time was still unsatisfactory with numeral iterative computations during the processing. To address this issue, an efficient feature selection method for network traffic based on a new parallel computing framework called Spark is proposed in this paper. In our approach, the complete feature set is firstly preprocessed based on Fisher score, and a sequential forward search strategy is employed for subsets. The optimal feature subset is then selected using the continuous iterations of the Spark computing framework. The implementation demonstrates that, on the precondition of keeping the classification accuracy, our method reduces the time cost of modeling and classification, and improves the execution efficiency of feature selection significantly.

Edge-Based Image Compression with Homogeneous Diffusion

Science.gov (United States)

Mainberger, Markus; Weickert, Joachim

It is well-known that edges contain semantically important image information. In this paper we present a lossy compression method for cartoon-like images that exploits information at image edges. These edges are extracted with the Marr-Hildreth operator followed by hysteresis thresholding. Their locations are stored in a lossless way using JBIG. Moreover, we encode the grey or colour values at both sides of each edge by applying quantisation, subsampling and PAQ coding. In the decoding step, information outside these encoded data is recovered by solving the Laplace equation, i.e. we inpaint with the steady state of a homogeneous diffusion process. Our experiments show that the suggested method outperforms the widely-used JPEG standard and can even beat the advanced JPEG2000 standard for cartoon-like images.

Abnormal traffic flow data detection based on wavelet analysis

Directory of Open Access Journals (Sweden)

Xiao Qian

2016-01-01

Full Text Available In view of the traffic flow data of non-stationary, the abnormal data detection is difficult.proposed basing on the wavelet analysis and least squares method of abnormal traffic flow data detection in this paper.First using wavelet analysis to make the traffic flow data of high frequency and low frequency component and separation, and then, combined with least square method to find abnormal points in the reconstructed signal data.Wavelet analysis and least square method, the simulation results show that using wavelet analysis of abnormal traffic flow data detection, effectively reduce the detection results of misjudgment rate and false negative rate.

Preprint WebVRGIS Based Traffic Analysis and Visualization System

OpenAIRE

Li, Xiaoming; Lv, Zhihan; Wang, Weixi; Zhang, Baoyun; Hu, Jinxing; Yin, Ling; Feng, Shengzhong

2015-01-01

This is the preprint version of our paper on Advances in Engineering Software. With several characteristics, such as large scale, diverse predictability and timeliness, the city traffic data falls in the range of definition of Big Data. A Virtual Reality GIS based traffic analysis and visualization system is proposed as a promising and inspiring approach to manage and develop traffic big data. In addition to the basic GIS interaction functions, the proposed system also includes some intellige...

Material Discrimination Based on K-edge Characteristics

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Peng He

2013-01-01

Full Text Available Spectral/multienergy CT employing the state-of-the-art energy-discriminative photon-counting detector can identify absorption features in the multiple ranges of photon energies and has the potential to distinguish different materials based on K-edge characteristics. K-edge characteristics involve the sudden attenuation increase in the attenuation profile of a relatively high atomic number material. Hence, spectral CT can utilize material K-edge characteristics (sudden attenuation increase to capture images in available energy bins (levels/windows to distinguish different material components. In this paper, we propose an imaging model based on K-edge characteristics for maximum material discrimination with spectral CT. The wider the energy bin width is, the lower the noise level is, but the poorer the reconstructed image contrast is. Here, we introduce the contrast-to-noise ratio (CNR criterion to optimize the energy bin width after the K-edge jump for the maximum CNR. In the simulation, we analyze the reconstructed image quality in different energy bins and demonstrate that our proposed optimization approach can maximize CNR between target region and background region in reconstructed image.

Is vehicle automation enough to prevent crashes? Role of traffic operations in automated driving environments for traffic safety.

Science.gov (United States)

Jeong, Eunbi; Oh, Cheol; Lee, Seolyoung

2017-07-01

Automated driving systems (ADSs) are expected to prevent traffic accidents caused by driver carelessness on freeways. There is no doubt regarding this safety benefit if all vehicles in the transportation system were equipped with ADSs; however, it is implausible to expect that ADSs will reach 100% market penetration rate (MPR) in the near future. Therefore, the following question arises: 'Can ADSs, which consider only situations in the vicinity of an equipped vehicle, really contribute to a significant reduction in traffic accidents?' To address this issue, the interactions between equipped and unequipped vehicles must be investigated, which is the purpose of this study. This study evaluated traffic safety at different MPRs based on a proposed index to represent the overall rear-end crash risk of the traffic stream. Two approaches were evaluated for adjusting longitudinal vehicle maneuvers: vehicle safety-based maneuvering (VSM), which considers the crash risk of an equipped vehicle and its neighboring vehicles, and traffic safety-based maneuvering (TSM), which considers the overall crash risk in the traffic stream. TSM assumes that traffic operational agencies are able to monitor all the vehicles and to intervene in vehicle maneuvering. An optimization process, which attempts to obtain vehicle maneuvering control parameters to minimize the overall crash risk, is integrated into the proposed evaluation framework. The main purpose of employing the optimization process for vehicle maneuvering in this study is to identify opportunities to improve traffic safety through effective traffic management rather than developing a vehicle control algorithm that can be implemented in practice. The microscopic traffic simulator VISSIM was used to simulate the freeway traffic stream and to conduct systematic evaluations based on the proposed methodology. Both TSM and VSM achieved significant reductions in the potential for rear-end crashes. However, TSM obtained much greater

Edge-based correlation image registration for multispectral imaging

Science.gov (United States)

Nandy, Prabal [Albuquerque, NM

2009-11-17

Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

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

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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.

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

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Eunjeong Ko

2016-01-01

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

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...

Canny edge-based deformable image registration.

Science.gov (United States)

Kearney, Vasant; Huang, Yihui; Mao, Weihua; Yuan, Baohong; Tang, Liping

2017-02-07

This work focuses on developing a 2D Canny edge-based deformable image registration (Canny DIR) algorithm to register in vivo white light images taken at various time points. This method uses a sparse interpolation deformation algorithm to sparsely register regions of the image with strong edge information. A stability criterion is enforced which removes regions of edges that do not deform in a smooth uniform manner. Using a synthetic mouse surface ground truth model, the accuracy of the Canny DIR algorithm was evaluated under axial rotation in the presence of deformation. The accuracy was also tested using fluorescent dye injections, which were then used for gamma analysis to establish a second ground truth. The results indicate that the Canny DIR algorithm performs better than rigid registration, intensity corrected Demons, and distinctive features for all evaluation matrices and ground truth scenarios. In conclusion Canny DIR performs well in the presence of the unique lighting and shading variations associated with white-light-based image registration.

Surface versus Edge-Based Determinants of Visual Recognition.

Science.gov (United States)

Biederman, Irving; Ju, Ginny

1988-01-01

The latency at which objects could be identified by 126 subjects was compared through line drawings (edge-based) or color photography (surface depiction). The line drawing was identified about as quickly as the photograph; primal access to a mental representation of an object can be modeled from an edge-based description. (SLD)

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...

Increase the Safety of Road Traffic Accidents by Applying Clustering

Directory of Open Access Journals (Sweden)

Kos Goran

2013-12-01

Full Text Available In terms of continual increase of number of traffic accidents and alarming trend of increasing number of traffic accidents with catastrophic consequences for human life and health, it is necessary to actively research and develop methods to combat these trends. One of the measures is the implementation of advanced information systems in existing traffic environment. Accidents clusters, as databases of traffic accidents, introduce a new dimension in traffic systems in the form of experience, providing information on current accidents and the ones that have previously occurred in a given period. This paper proposes a new approach to predictive management of traffic processes, based on the collection of data in real time and is based on accidents clusters. The modern traffic information services collects road traffic status data from a wide variety of traffic sensing systems using modern ICT technologies, creating the most accurate road traffic situation awareness achieved so far. Road traffic situation awareness enhanced by accident clusters' data can be visualized and distributed in various ways (including the forms of dynamic heat maps and on various information platforms, suiting the requirements of the end-users. Accent is placed on their significant features that are based on additional knowledge about existing traffic processes and distribution of important traffic information in order to prevent and reduce traffic accidents.

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%.

Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting

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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.

An Edge-Based Macao License Plate Recognition System

Directory of Open Access Journals (Sweden)

Chi-Man Pun

2011-04-01

Full Text Available This paper presents a system to recognize Macao license plates. Sobel edge detector is employed to extract the vertical edges, and an edge composition algorithm is proposed to combine the edges into candidate plate regions. They are further examined on the existence of the character qMq by a verification algorithm. A row separation algorithm is also proposed to cater both one-row and two-row types of plates. Projection analysis and template matching methods are exploited to segment and recognize the characters. Various pre and post processing steps are proposed other than traditional implementation so as to improve the recognition accuracy. This work achieves a high recognition rate of 95%.

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.

The Use of Adaptive Traffic Signal Systems Based on Floating Car Data

Directory of Open Access Journals (Sweden)

Vittorio Astarita

2017-01-01

Full Text Available This paper presents a simple concept which has not been, up to now, thoroughly explored in scientific research: the use of information coming from the network of Internet connected mobile devices (on vehicles to regulate traffic light systems. Three large-scale changes are going to shape the future of transportation and could lead to the regulation of traffic signal system based on floating car data (FCD: (i the implementation of Internet connected cars with global navigation satellite (GNSS system receivers and the autonomous car revolution; (ii the spreading of mobile cooperative Web 2.0 and the extension to connected vehicles; (iii an increasing need for sustainability of transportation in terms of energy efficiency, traffic safety, and environmental issues. Up to now, the concept of floating car data (FCD has only been extensively used to obtain traffic information and estimate traffic parameters. Traffic lights regulation based on FCD technology has not been fully researched since the implementation requires new ideas and algorithms. This paper intends to provide a seminal insight into the important issue of adaptive traffic light based on FCD by presenting ideas that can be useful to researchers and engineers in the long-term task of developing new algorithms and systems that may revolutionize the way traffic lights are regulated.

A Method Based on Dial's Algorithm for Multi-time Dynamic Traffic Assignment

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Rongjie Kuang

2014-03-01

Full Text Available Due to static traffic assignment has poor performance in reflecting actual case and dynamic traffic assignment may incurs excessive compute cost, method of multi-time dynamic traffic assignment combining static and dynamic traffic assignment balances factors of precision and cost effectively. A method based on Dial's logit algorithm is proposed in the article to solve the dynamic stochastic user equilibrium problem in dynamic traffic assignment. Before that, a fitting function that can proximately reflect overloaded traffic condition of link is proposed and used to give corresponding model. Numerical example is given to illustrate heuristic procedure of method and to compare results with one of same example solved by other literature's algorithm. Results show that method based on Dial's algorithm is preferable to algorithm from others.

Intelligent Traffic Light Based on PLC Control

Science.gov (United States)

Mei, Lin; Zhang, Lijian; Wang, Lingling

2017-11-01

The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

Information processing in patterned magnetic nanostructures with edge spin waves.

Science.gov (United States)

Lara, Antonio; Robledo Moreno, Javier; Guslienko, Konstantin Y; Aliev, Farkhad G

2017-07-17

Low dissipation data processing with spins is one of the promising directions for future information and communication technologies. Despite a significant progress, the available magnonic devices are not broadband yet and have restricted capabilities to redirect spin waves. Here we propose a breakthrough approach to spin wave manipulation in patterned magnetic nanostructures with unmatched characteristics, which exploits a spin wave analogue to edge waves propagating along a water-wall boundary. Using theory, micromagnetic simulations and experiment we investigate spin waves propagating along the edges in magnetic structures, under an in-plane DC magnetic field inclined with respect to the edge. The proposed edge spin waves overcome important challenges faced by previous technologies such as the manipulation of the spin wave propagation direction, and they substantially improve the capability of transmitting information at frequencies exceeding 10 GHz. The concept of the edge spin waves allows to design a broad of logic devices such as splitters, interferometers, or edge spin wave transistors with unprecedented characteristics and a potentially strong impact on information technologies.

A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

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Yiliang Zeng

2014-01-01

Full Text Available A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

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.

Edge-based compression of cartoon-like images with homogeneous diffusion

DEFF Research Database (Denmark)

Mainberger, Markus; Bruhn, Andrés; Weickert, Joachim

2011-01-01

Edges provide semantically important image features. In this paper a lossy compression method for cartoon-like images is presented, which is based on edge information. Edges together with some adjacent grey/colour values are extracted and encoded using a classical edge detector, binary compressio...

Refining Lane-Based Traffic Signal Settings to Satisfy Spatial Lane Length Requirements

Directory of Open Access Journals (Sweden)

Yanping Liu

2017-01-01

Full Text Available In conventional lane-based signal optimization models, lane markings guiding road users in making turns are optimized with traffic signal settings in a unified framework to maximize the overall intersection capacity or minimize the total delay. The spatial queue requirements of road lanes should be considered to avoid overdesigns of green durations. Point queue system adopted in the conventional lane-based framework causes overflow in practice. Based on the optimization results from the original lane-based designs, a refinement is proposed to enhance the lane-based settings to ensure that spatial holding limits of the approaching traffic lanes are not exceeded. A solution heuristic is developed to modify the green start times, green durations, and cycle length by considering the vehicle queuing patterns and physical holding capacities along the approaching traffic lanes. To show the effectiveness of this traffic signal refinement, a case study of one of the busiest and most complicated intersections in Hong Kong is given for demonstration. A site survey was conducted to collect existing traffic demand patterns and existing traffic signal settings in peak periods. Results show that the proposed refinement method is effective to ensure that all vehicle queue lengths satisfy spatial lane capacity limits, including short lanes, for daily operation.

Decentralized Traffic Management: A Synchronization-Based Intersection Control --- Extended Version

OpenAIRE

Tlig , Mohamed; Buffet , Olivier; Simonin , Olivier

2014-01-01

Controlling the vehicle traffic in large networks remains an important challenge in urban environments and transportation systems. Autonomous vehicles are today considered as a promising approach to deal with traffic control. In this paper, we propose a synchronization-based intersection control mechanism to allow the autonomous vehicle-agents to cross without stopping, i.e., in order to avoid congestions (delays) and energy loss. We decentralize the problem by managing the traffic of each in...

A new smart traffic monitoring method using embedded cement-based piezoelectric sensors

International Nuclear Information System (INIS)

Zhang, Jinrui; Lu, Youyuan; Lu, Zeyu; Liu, Chao; Sun, Guoxing; Li, Zongjin

2015-01-01

Cement-based piezoelectric composites are employed as the sensing elements of a new smart traffic monitoring system. The piezoelectricity of the cement-based piezoelectric sensors enables powerful and accurate real-time detection of the pressure induced by the traffic flow. To describe the mechanical-electrical conversion mechanism between traffic flow and the electrical output of the embedded piezoelectric sensors, a mathematical model is established based on Duhamel’s integral, the constitutive law and the charge-leakage characteristics of the piezoelectric composite. Laboratory tests show that the voltage magnitude of the sensor is linearly proportional to the applied pressure, which ensures the reliability of the cement-based piezoelectric sensors for traffic monitoring. A series of on-site road tests by a 10 tonne truck and a 6.8 tonne van show that vehicle weight-in-motion can be predicted based on the mechanical-electrical model by taking into account the vehicle speed and the charge-leakage property of the piezoelectric sensor. In the speed range from 20 km h −1 to 70 km h −1 , the error of the repeated weigh-in-motion measurements of the 6.8 tonne van is less than 1 tonne. The results indicate that the embedded cement-based piezoelectric sensors and associated measurement setup have good capability of smart traffic monitoring, such as traffic flow detection, vehicle speed detection and weigh-in-motion measurement. (paper)

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.

Path-based Queries on Trajectory Data

DEFF Research Database (Denmark)

Krogh, Benjamin Bjerre; Pelekis, Nikos; Theodoridis, Yannis

2014-01-01

In traffic research, management, and planning a number of path-based analyses are heavily used, e.g., for computing turn-times, evaluating green waves, or studying traffic flow. These analyses require retrieving the trajectories that follow the full path being analyzed. Existing path queries cannot...... sufficiently support such path-based analyses because they retrieve all trajectories that touch any edge in the path. In this paper, we define and formalize the strict path query. This is a novel query type tailored to support path-based analysis, where trajectories must follow all edges in the path...... a specific path by only retrieving data from the first and last edge in the path. To correctly answer strict path queries existing network-constrained trajectory indexes must retrieve data from all edges in the path. An extensive performance study of NETTRA using a very large real-world trajectory data set...

Edge-preserving Intra mode for efficient depth map coding based on H.264/AVC

DEFF Research Database (Denmark)

Zamarin, Marco; Forchhammer, Søren

2014-01-01

Depth-image-based-rendering (DIBR) algorithms for 3D video communication systems based on the “multi-view video plus depth” format are very sensitive to the accuracy of depth information. Specifically, edge regions in the depth data should be preserved in the coding/decoding process to ensure good...... view synthesis performance, which directly affects the overall system performance. This paper proposes a novel scheme for edge-aware Intra depth compression based on the H.264/AVC framework enabled on both Intra (I) and Inter (P) slices. The proposed scheme includes a new Intra mode specifically...

IoT-B&B: Edge-Based NFV for IoT Devices with CPE Crowdsourcing

Directory of Open Access Journals (Sweden)

He Zhu

2018-01-01

Full Text Available For embracing the ubiquitous Internet-of-Things (IoT devices, edge computing and Network Function Virtualization (NFV have been enabled in branch offices and homes in the form of virtual Customer-Premises Equipment (vCPE. A Service Provider (SP deploys vCPE instances as Virtual Network Functions (VNFs on top of generic physical Customer-Premises Equipment (pCPE to ease administration. Upon a usage surge of IoT devices at a certain part of the network, vCPU, memory, and other resource limitations of a single pCPE node make it difficult to add new services handling the high demand. In this paper, we present IoT-B&B, a novel architecture featuring resource sharing of pCPE nodes. When a pCPE node has sharable resources available, the SP will utilize its free resources as a “bed-and-breakfast” place to deploy vCPE instances in need. A placement algorithm is also presented to assign vCPE instances to a cost-efficient pCPE node. By keeping vCPE instances at the network edge, their costs of hosting are reduced. Meanwhile, the transmission latencies are maintained at acceptable levels for processing real-time data burst from IoT devices. The traffic load to the remote, centralized cloud can be substantially reduced.

Web-based Traffic Noise Control Support System for Sustainable Transportation

Science.gov (United States)

Fan, Lisa; Dai, Liming; Li, Anson

Traffic noise is considered as one of the major pollutions that will affect our communities in the future. This paper presents a framework of web-based traffic noise control support system (WTNCSS) for a sustainable transportation. WTNCSS is to provide the decision makers, engineers and publics a platform to efficiently access the information, and effectively making decisions related to traffic control. The system is based on a Service Oriented Architecture (SOA) which takes the advantages of the convenience of World Wide Web system with the data format of XML. The whole system is divided into different modules such as the prediction module, ontology-based expert module and dynamic online survey module. Each module of the system provides a distinct information service to the decision support center through the HTTP protocol.

Efficient graph-based dynamic load-balancing for parallel large-scale agent-based traffic simulation

NARCIS (Netherlands)

Xu, Y.; Cai, W.; Aydt, H.; Lees, M.; Tolk, A.; Diallo, S.Y.; Ryzhov, I.O.; Yilmaz, L.; Buckley, S.; Miller, J.A.

2014-01-01

One of the issues of parallelizing large-scale agent-based traffic simulations is partitioning and load-balancing. Traffic simulations are dynamic applications where the distribution of workload in the spatial domain constantly changes. Dynamic load-balancing at run-time has shown better efficiency

Edge responses are different in edges under natural versus anthropogenic influence: a meta-analysis using ground beetles.

Science.gov (United States)

Magura, Tibor; Lövei, Gábor L; Tóthmérész, Béla

2017-02-01

Most edges are anthropogenic in origin, but are distinguishable by their maintaining processes (natural vs. continued anthropogenic interventions: forestry, agriculture, urbanization). We hypothesized that the dissimilar edge histories will be reflected in the diversity and assemblage composition of inhabitants. Testing this "history-based edge effect" hypothesis, we evaluated published information on a common insect group, ground beetles (Coleoptera: Carabidae) in forest edges. A meta-analysis showed that the diversity-enhancing properties of edges significantly differed according to their history. Forest edges maintained by natural processes had significantly higher species richness than their interiors, while edges with continued anthropogenic influence did not. The filter function of edges was also essentially different depending on their history. For forest specialist species, edges maintained by natural processes were penetrable, allowing these species to move right through the edges, while edges still under anthropogenic interventions were impenetrable, preventing the dispersal of forest specialists out of the forest. For species inhabiting the surrounding matrix (open-habitat and generalist species), edges created by forestry activities were penetrable, and such species also invaded the forest interior. However, natural forest edges constituted a barrier and prevented the invasion of matrix species into the forest interior. Preserving and protecting all edges maintained by natural processes, and preventing anthropogenic changes to their structure, composition, and characteristics are key factors to sustain biodiversity in forests. Moreover, the increasing presence of anthropogenic edges in a landscape is to be avoided, as they contribute to the loss of biodiversity. Simultaneously, edges under continued anthropogenic disturbance should be restored by increasing habitat heterogeneity.

Measurements and modelling of base station power consumption under real traffic loads.

Science.gov (United States)

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads

Directory of Open Access Journals (Sweden)

Goran Petrovic

2012-03-01

Full Text Available Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications and UMTS (Universal Mobile Telecommunications System base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Development and application of traffic flow information collecting and analysis system based on multi-type video

Science.gov (United States)

Lu, Mujie; Shang, Wenjie; Ji, Xinkai; Hua, Mingzhuang; Cheng, Kuo

2015-12-01

Nowadays, intelligent transportation system (ITS) has already become the new direction of transportation development. Traffic data, as a fundamental part of intelligent transportation system, is having a more and more crucial status. In recent years, video observation technology has been widely used in the field of traffic information collecting. Traffic flow information contained in video data has many advantages which is comprehensive and can be stored for a long time, but there are still many problems, such as low precision and high cost in the process of collecting information. This paper aiming at these problems, proposes a kind of traffic target detection method with broad applicability. Based on three different ways of getting video data, such as aerial photography, fixed camera and handheld camera, we develop a kind of intelligent analysis software which can be used to extract the macroscopic, microscopic traffic flow information in the video, and the information can be used for traffic analysis and transportation planning. For road intersections, the system uses frame difference method to extract traffic information, for freeway sections, the system uses optical flow method to track the vehicles. The system was applied in Nanjing, Jiangsu province, and the application shows that the system for extracting different types of traffic flow information has a high accuracy, it can meet the needs of traffic engineering observations and has a good application prospect.

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.

An Efficient Traffic Congestion Monitoring System on Internet of Vehicles

Directory of Open Access Journals (Sweden)

Duc-Binh Nguyen

2018-01-01

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

Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

Directory of Open Access Journals (Sweden)

Li Wang

2013-01-01

Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

Entropy Based Analysis of DNS Query Traffic in the Campus Network

Directory of Open Access Journals (Sweden)

Dennis Arturo Ludeña Romaña

2008-10-01

Full Text Available We carried out the entropy based study on the DNS query traffic from the campus network in a university through January 1st, 2006 to March 31st, 2007. The results are summarized, as follows: (1 The source IP addresses- and query keyword-based entropies change symmetrically in the DNS query traffic from the outside of the campus network when detecting the spam bot activity on the campus network. On the other hand (2, the source IP addresses- and query keywordbased entropies change similarly each other when detecting big DNS query traffic caused by prescanning or distributed denial of service (DDoS attack from the campus network. Therefore, we can detect the spam bot and/or DDoS attack bot by only watching DNS query access traffic.

Three-dimensional parallel edge-based finite element modeling of electromagnetic data with field redatuming

DEFF Research Database (Denmark)

Cai, Hongzhu; Čuma, Martin; Zhdanov, Michael

2015-01-01

This paper presents a parallelized version of the edge-based finite element method with a novel post-processing approach for numerical modeling of an electromagnetic field in complex media. The method uses an unstructured tetrahedral mesh which can reduce the number of degrees of freedom signific......This paper presents a parallelized version of the edge-based finite element method with a novel post-processing approach for numerical modeling of an electromagnetic field in complex media. The method uses an unstructured tetrahedral mesh which can reduce the number of degrees of freedom...... significantly. The linear system of finite element equations is solved using parallel direct solvers which are robust for ill-conditioned systems and efficient for multiple source electromagnetic (EM) modeling. We also introduce a novel approach to compute the scalar components of the electric field from...... the tangential components along each edge based on field redatuming. The method can produce a more accurate result as compared to conventional approach. We have applied the developed algorithm to compute the EM response for a typical 3D anisotropic geoelectrical model of the off-shore HC reservoir with complex...

The historical town core and traffic in Novo mesto

Directory of Open Access Journals (Sweden)

Lilijana Jankovič

2001-01-01

Full Text Available The historical town core of Novo mesto is subject to intolerable traffic conditions. Individual car use is suffocating the town core, but simultaneously good access is essential for shopkeepers and other inhabitants since buses don’t go there. The project proposes changes to the traffic regime, its basic goals are to redesign the town square into a pedestrian place and to eliminate transitory traffic by rerouting vehicles to less burdened side roads. It introduces short-term parking, smaller parking garages in the core and larger parking spaces on the edge and routes the buses through the town core.

Monitoring individual traffic flows within the ATLAS TDAQ network

CERN Document Server

Sjoen, R; Ciobotaru, M; Batraneanu, S M; Leahu, L; Martin, B; Al-Shabibi, A

2010-01-01

The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities a...

Local-Area Based Traffic Splitter for Improving Performance Using Subnetting

Science.gov (United States)

Yadav, Meenakshi; Mittal, Mohit Kumar

2010-11-01

This document provides an overview of LAN traffic splitter. The tool "Local-Area based Traffic splitter" is based on subnetting techniques. It is basically used for calculating subnets for sub-dividing the LAN. Subnetting an IP Network can be done for a variety of reasons, including organization, use of different physical media (such as Ethernet, FDDI, WAN, etc.), preservation of address space, and security. The most common reason is to control network traffic. There are various techniques for calculating subnets that are considered by this tool. This paper will explore the various features of this tool and will also check the effect of subnetting after implementing it on the LAN. These instructions give you basic guidelines for preparing camera-ready papers for conference proceedings.

A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

OpenAIRE

Wang, Shuo; Zhang, Xing; Zhang, Yan; Wang, Lin; Yang, Juwo; Wang, Wenbo

2017-01-01

As the explosive growth of smart devices and the advent of many new applications, traffic volume has been growing exponentially. The traditional centralized network architecture cannot accommodate such user demands due to heavy burden on the backhaul links and long latency. Therefore, new architectures which bring network functions and contents to the network edge are proposed, i.e., mobile edge computing and caching. Mobile edge networks provide cloud computing and caching capabilities at th...

Agent-Based Collaborative Traffic Flow Management, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We propose agent-based game-theoretic approaches for simulation of strategies involved in multi-objective collaborative traffic flow management (CTFM). Intelligent...

Two-dimensional straightness measurement based on optical knife-edge sensing

Science.gov (United States)

Wang, Chen; Zhong, Fenghe; Ellis, Jonathan D.

2017-09-01

Straightness error is a parasitic translation along a perpendicular direction to the primary displacement axis of a linear stage. The parasitic translations could be coupled into other primary displacement directions of a multi-axis platform. Hence, its measurement and compensation are critical in precision multi-axis metrology, calibration, and manufacturing. This paper presents a two-dimensional (2D) straightness measurement configuration based on 2D optical knife-edge sensing, which is simple, light-weight, compact, and easy to align. It applies a 2D optical knife-edge to manipulate the diffraction pattern sensed by a quadrant photodetector, whose output voltages could derive 2D straightness errors after a calibration process. This paper analyzes the physical model of the configuration and performs simulations and experiments to study the system sensitivity, measurement nonlinearity, and error sources. The results demonstrate that the proposed configuration has higher sensitivity and insensitive to beam's vibration, compared with the conventional configurations without using the knife-edge, and could achieve ±0.25 μ m within a ±40 μ m measurement range along a 40 mm primary axial motion.

Probabilistic description of traffic flow

International Nuclear Information System (INIS)

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

2005-01-01

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

Tourism in protected areas: Disentangling road and traffic effects on intra-guild scavenging processes.

Science.gov (United States)

Donázar, José Antonio; Ceballos, Olga; Cortés-Avizanda, Ainara

2018-07-15

The expansion of road networks and the increase in traffic have emerged in recent years as key threats to the conservation of biodiversity. This is particularly concerning in many protected areas because the increase of recreational activities requiring the use of vehicles. Effects of roads and traffic within guild scenarios and ecological processes remain however poorly known. Here we examined how road proximity and traffic intensity influence patterns of resource use in an Old-World avian scavenger guild living in a protected natural park in northern Spain. We experimentally placed 130 carcasses at different distances from a scenic road in the centre of the park. Vehicles were recorded by means of traffic counters which revealed that maximum numbers were reached during weekends and holidays and during the middle hours of the day. Avian scavenger attendance at carcasses was recorded by means of camera-traps. Obligated scavengers, Eurasian griffon (Gyps fulvus) and Egyptian vultures (Neophron percnopterus) were frequently observed (59.4% and 37.7% of the consumed carcasses) together with five other facultative scavenger species. We found that the richness (number of species) and the probability of consumption of the resource were reduced the smaller the distance to the road and in days with higher traffic intensity. The same factors affected the probability of presence of all the scavenger species. Moreover, some of them, notably griffon vultures, showed hourly patterns of carcass attendance suggesting avoidance of maximum traffic levels. Our results highlight that roads and traffic would trigger consequences on the structure and functioning of scavenger food webs, which may be particularly concerning in protected areas with remarkable levels of biodiversity. Future regulations at protected areas should couple both traffic and tourist affluence with wildlife conservation. In this way important ecological processes would be preserved while maintaining a good

Autosolitons in applied physics and traffic flow

International Nuclear Information System (INIS)

Kerner, B.S.

1996-01-01

A review of investigations of autosolitons in nonlinear systems which are of interest for the applied physics and for the transportation research is presented. Autosolitons are solitary intrinsic states which can be formed in a broad class of physical, chemical, biological dissipative distributed media and in traffic flow. Properties of autosolitons which are general for physical systems and for traffic flow will be discussed. Based on results of recent investigations of traffic jams in traffic flow, a comparison of nonlinear characteristics of traffic jams and with nonlinear properties of autosolitons which can be formed in active systems with diffusion will be given. Forms, properties, processes of evolution of autosolitons in traffic flow, in semiconductors and in gas discharge plasma are considered. copyright 1996 American Institute of Physics

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.

Agent Based Individual Traffic guidance

DEFF Research Database (Denmark)

Wanscher, Jørgen Bundgaard

2004-01-01

When working with traffic planning or guidance it is common practice to view the vehicles as a combined mass. >From this models are employed to specify the vehicle supply and demand for each region. As the models are complex and the calculations are equally demanding the regions and the detail...... of the road network is aggregated. As a result the calculations reveal only what the mass of vehicles are doing and not what a single vehicle is doing. This is the crucial difference to ABIT (Agent Based Individual Trafficguidance). ABIT is based on the fact that information on the destination of each vehicle...

The rheology and processing of “edge sheared” colloidal polymer opals

International Nuclear Information System (INIS)

Wong, Hon Sum; Mackley, Malcolm; Butler, Simon; Baumberg, Jeremy; Snoswell, David; Finlayson, Chris; Zhao, Qibin

2014-01-01

This paper is concerned with the rheology and processing of solvent-free core shell “polymer opals” that consist of a soft outer shell grafted to hard colloidal polymer core particles. Strong iridescent colors can be produced by shearing the material in a certain way that causes the initially disordered spheres to rearrange into ordered crystalline structures and produce colors by diffraction and interference of multiple light scattering, similar to gemstone opals. The basic linear viscoelastic rheology of a polymer opal sample was determined as a function of temperature, and the material was found to be highly viscoelastic at all tested temperatures. A Cambridge multipass rheometer was specifically modified in order to make controlled mechanical measurements of initially disordered polymer opal tapes that were sandwiched between protective polyethylene terephthalate sheets. Axial extension, simple shear, and a novel “edge shearing” geometry were all evaluated, and multiple successive experiments of the edge shearing test were carried out at different temperatures. The optical development of colloidal ordering, measured as optical opalescence, was quantified by spectroscopy using visible backscattered light. The development of opalescence was found to be sensitive to the geometry of deformation and a number of process variables suggesting a complex interaction of parameters that caused the opalescence. In order to identify aspects of the deformation mechanism of the edge shearing experiment, a separate series of in situ optical experiments were carried out and this helped indicate the extent of simple shear generated with each edge shear deformation. The results show that strong ordering can be induced by successive edge shearing deformation. The results are relevant to polymer opal rheology, processing, and mechanisms relating to ordering within complex viscoelastic fluids

The rheology and processing of “edge sheared” colloidal polymer opals

Energy Technology Data Exchange (ETDEWEB)

Wong, Hon Sum; Mackley, Malcolm, E-mail: mrm5@cam.ac.uk; Butler, Simon [Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB2 3RA (United Kingdom); Baumberg, Jeremy; Snoswell, David; Finlayson, Chris; Zhao, Qibin [Cavendish Laboratory, NanoPhotonics Centre, University of Cambridge, Cambridge CB3 OHE (United Kingdom)

2014-03-15

This paper is concerned with the rheology and processing of solvent-free core shell “polymer opals” that consist of a soft outer shell grafted to hard colloidal polymer core particles. Strong iridescent colors can be produced by shearing the material in a certain way that causes the initially disordered spheres to rearrange into ordered crystalline structures and produce colors by diffraction and interference of multiple light scattering, similar to gemstone opals. The basic linear viscoelastic rheology of a polymer opal sample was determined as a function of temperature, and the material was found to be highly viscoelastic at all tested temperatures. A Cambridge multipass rheometer was specifically modified in order to make controlled mechanical measurements of initially disordered polymer opal tapes that were sandwiched between protective polyethylene terephthalate sheets. Axial extension, simple shear, and a novel “edge shearing” geometry were all evaluated, and multiple successive experiments of the edge shearing test were carried out at different temperatures. The optical development of colloidal ordering, measured as optical opalescence, was quantified by spectroscopy using visible backscattered light. The development of opalescence was found to be sensitive to the geometry of deformation and a number of process variables suggesting a complex interaction of parameters that caused the opalescence. In order to identify aspects of the deformation mechanism of the edge shearing experiment, a separate series of in situ optical experiments were carried out and this helped indicate the extent of simple shear generated with each edge shear deformation. The results show that strong ordering can be induced by successive edge shearing deformation. The results are relevant to polymer opal rheology, processing, and mechanisms relating to ordering within complex viscoelastic fluids.

Traffic characterization and modeling of wavelet-based VBR encoded video

Energy Technology Data Exchange (ETDEWEB)

Yu Kuo; Jabbari, B. [George Mason Univ., Fairfax, VA (United States); Zafar, S. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

1997-07-01

Wavelet-based video codecs provide a hierarchical structure for the encoded data, which can cater to a wide variety of applications such as multimedia systems. The characteristics of such an encoder and its output, however, have not been well examined. In this paper, the authors investigate the output characteristics of a wavelet-based video codec and develop a composite model to capture the traffic behavior of its output video data. Wavelet decomposition transforms the input video in a hierarchical structure with a number of subimages at different resolutions and scales. the top-level wavelet in this structure contains most of the signal energy. They first describe the characteristics of traffic generated by each subimage and the effect of dropping various subimages at the encoder on the signal-to-noise ratio at the receiver. They then develop an N-state Markov model to describe the traffic behavior of the top wavelet. The behavior of the remaining wavelets are then obtained through estimation, based on the correlations between these subimages at the same level of resolution and those wavelets located at an immediate higher level. In this paper, a three-state Markov model is developed. The resulting traffic behavior described by various statistical properties, such as moments and correlations, etc., is then utilized to validate their model.

Temporal-Spatial Analysis of Traffic Congestion Based on Modified CTM

Directory of Open Access Journals (Sweden)

Chenglong Chu

2015-01-01

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

Sliding Window Based Feature Extraction and Traffic Clustering for Green Mobile Cyberphysical Systems

Directory of Open Access Journals (Sweden)

Jiao Zhang

2017-01-01

Full Text Available Both the densification of small base stations and the diversity of user activities bring huge challenges for today’s heterogeneous networks, either heavy burdens on base stations or serious energy waste. In order to ensure coverage of the network while reducing the total energy consumption, we adopt a green mobile cyberphysical system (MCPS to handle this problem. In this paper, we propose a feature extraction method using sliding window to extract the distribution feature of mobile user equipment (UE, and a case study is presented to demonstrate that the method is efficacious in reserving the clustering distribution feature. Furthermore, we present traffic clustering analysis to categorize collected traffic distribution samples into a limited set of traffic patterns, where the patterns and corresponding optimized control strategies are used to similar traffic distributions for the rapid control of base station state. Experimental results show that the sliding window is more superior in enabling higher UE coverage over the grid method. Besides, the optimized control strategy obtained from the traffic pattern is capable of achieving a high coverage that can well serve over 98% of all mobile UE for similar traffic distributions.

Wavelet based edge detection algorithm for web surface inspection of coated board web

Energy Technology Data Exchange (ETDEWEB)

Barjaktarovic, M; Petricevic, S, E-mail: slobodan@etf.bg.ac.r [School of Electrical Engineering, Bulevar Kralja Aleksandra 73, 11000 Belgrade (Serbia)

2010-07-15

This paper presents significant improvement of the already installed vision system. System was designed for real time coated board inspection. The improvement is achieved with development of a new algorithm for edge detection. The algorithm is based on the redundant (undecimated) wavelet transform. Compared to the existing algorithm better delineation of edges is achieved. This yields to better defect detection probability and more accurate geometrical classification, which will provide additional reduction of waste. Also, algorithm will provide detailed classification and more reliably tracking of defects. This improvement requires minimal changes in processing hardware, only a replacement of the graphic card would be needed, adding only negligibly to the system cost. Other changes are accomplished entirely in the image processing software.

Throughput-Based Traffic Steering in LTE-Advanced HetNet Deployments

DEFF Research Database (Denmark)

Gimenez, Lucas Chavarria; Kovacs, Istvan Z.; Wigard, Jeroen

2015-01-01

The objective of this paper is to propose traffic steering solutions that aim at optimizing the end-user throughput. Two different implementations of an active mode throughput-based traffic steering algorithm for Heterogeneous Networks (HetNet) are introduced. One that always forces handover of t...... throughput is generally higher, reaching values of 36% and 18% for the medium- and high-load conditions....

Image edge detection based tool condition monitoring with morphological component analysis.

Science.gov (United States)

Yu, Xiaolong; Lin, Xin; Dai, Yiquan; Zhu, Kunpeng

2017-07-01

The measurement and monitoring of tool condition are keys to the product precision in the automated manufacturing. To meet the need, this study proposes a novel tool wear monitoring approach based on the monitored image edge detection. Image edge detection has been a fundamental tool to obtain features of images. This approach extracts the tool edge with morphological component analysis. Through the decomposition of original tool wear image, the approach reduces the influence of texture and noise for edge measurement. Based on the target image sparse representation and edge detection, the approach could accurately extract the tool wear edge with continuous and complete contour, and is convenient in charactering tool conditions. Compared to the celebrated algorithms developed in the literature, this approach improves the integrity and connectivity of edges, and the results have shown that it achieves better geometry accuracy and lower error rate in the estimation of tool conditions. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Algorithm for image retrieval based on edge gradient orientation statistical code.

Science.gov (United States)

Zeng, Jiexian; Zhao, Yonggang; Li, Weiye; Fu, Xiang

2014-01-01

Image edge gradient direction not only contains important information of the shape, but also has a simple, lower complexity characteristic. Considering that the edge gradient direction histograms and edge direction autocorrelogram do not have the rotation invariance, we put forward the image retrieval algorithm which is based on edge gradient orientation statistical code (hereinafter referred to as EGOSC) by sharing the application of the statistics method in the edge direction of the chain code in eight neighborhoods to the statistics of the edge gradient direction. Firstly, we construct the n-direction vector and make maximal summation restriction on EGOSC to make sure this algorithm is invariable for rotation effectively. Then, we use Euclidean distance of edge gradient direction entropy to measure shape similarity, so that this method is not sensitive to scaling, color, and illumination change. The experimental results and the algorithm analysis demonstrate that the algorithm can be used for content-based image retrieval and has good retrieval results.

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.

Study on edge-extraction of remote sensing image

International Nuclear Information System (INIS)

Wen Jianguang; Xiao Qing; Xu Huiping

2005-01-01

Image edge-extraction is an important step in image processing and recognition, and also a hot spot in science study. In this paper, based on primary methods of the remote sensing image edge-extraction, authors, for the first time, have proposed several elements which should be considered before processing. Then, the qualities of several methods in remote sensing image edge-extraction are systematically summarized. At last, taking Near Nasca area (Peru) as an example the edge-extraction of Magmatic Range is analysed. (authors)

Correlation dimension based nonlinear analysis of network traffics with different application protocols

International Nuclear Information System (INIS)

Wang Jun-Song; Yuan Jing; Li Qiang; Yuan Rui-Xi

2011-01-01

This paper uses a correlation dimension based nonlinear analysis approach to analyse the dynamics of network traffics with three different application protocols—HTTP, FTP and SMTP. First, the phase space is reconstructed and the embedding parameters are obtained by the mutual information method. Secondly, the correlation dimensions of three different traffics are calculated and the results of analysis have demonstrated that the dynamics of the three different application protocol traffics is different from each other in nature, i.e. HTTP and FTP traffics are chaotic, furthermore, the former is more complex than the later; on the other hand, SMTP traffic is stochastic. It is shown that correlation dimension approach is an efficient method to understand and to characterize the nonlinear dynamics of HTTP, FTP and SMTP protocol network traffics. This analysis provided insight into and a more accurate understanding of nonlinear dynamics of internet traffics which have a complex mixture of chaotic and stochastic components. (general)

Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights.

Science.gov (United States)

Arita, Chikashi; Foulaadvand, M Ebrahim; Santen, Ludger

2017-03-01

We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

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.

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.

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

Edge detection based on computational ghost imaging with structured illuminations

Science.gov (United States)

Yuan, Sheng; Xiang, Dong; Liu, Xuemei; Zhou, Xin; Bing, Pibin

2018-03-01

Edge detection is one of the most important tools to recognize the features of an object. In this paper, we propose an optical edge detection method based on computational ghost imaging (CGI) with structured illuminations which are generated by an interference system. The structured intensity patterns are designed to make the edge of an object be directly imaged from detected data in CGI. This edge detection method can extract the boundaries for both binary and grayscale objects in any direction at one time. We also numerically test the influence of distance deviations in the interference system on edge extraction, i.e., the tolerance of the optical edge detection system to distance deviation. Hopefully, it may provide a guideline for scholars to build an experimental system.

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.

A knowledge-based system for controlling automobile traffic

Science.gov (United States)

Maravas, Alexander; Stengel, Robert F.

1994-01-01

Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

Models for discrete-time self-similar vector processes with application to network traffic

Science.gov (United States)

Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh

2003-07-01

The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

Background Traffic-Based Retransmission Algorithm for Multimedia Streaming Transfer over Concurrent Multipaths

Directory of Open Access Journals (Sweden)

Yuanlong Cao

2012-01-01

Full Text Available The content-rich multimedia streaming will be the most attractive services in the next-generation networks. With function of distribute data across multipath end-to-end paths based on SCTP's multihoming feature, concurrent multipath transfer SCTP (CMT-SCTP has been regarded as the most promising technology for the efficient multimedia streaming transmission. However, the current researches on CMT-SCTP mainly focus on the algorithms related to the data delivery performance while they seldom consider the background traffic factors. Actually, background traffic of realistic network environments has an important impact on the performance of CMT-SCTP. In this paper, we firstly investigate the effect of background traffic on the performance of CMT-SCTP based on a close realistic simulation topology with reasonable background traffic in NS2, and then based on the localness nature of background flow, a further improved retransmission algorithm, named RTX_CSI, is proposed to reach more benefits in terms of average throughput and achieve high users' experience of quality for multimedia streaming services.

Air Traffic Control: Immature Software Acquisition Processes Increase FAA System Acquisition Risks

Science.gov (United States)

1997-03-01

The General Accounting Office (GAO) at the request of Congress reviewed (1) : the maturity of Federal Aviation Administration's (FAA's) Air Traffic Control : (ATC) modernization software acquisition processes, and (2) the steps/actions : FAA has unde...

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

Science.gov (United States)

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

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

A video-based approach to calibrating car-following parameters in VISSIM for urban traffic

Directory of Open Access Journals (Sweden)

Zhengyang Lu

2016-08-01

Full Text Available Microscopic simulation models need to be calibrated to represent realistic local traffic conditions. Traditional calibration methods are conducted by searching for the model parameter set that minimizes the discrepancies of certain macroscopic metrics between simulation results and field observations. However, this process could easily lead to inappropriate selection of calibration parameters and thus erroneous simulation results. This paper proposes a video-based approach to incorporate direct measurements of car-following parameters into the process of VISSIM model calibration. The proposed method applies automated video processing techniques to extract vehicle trajectory data and utilizes the trajectory data to determine values of certain car-following parameters in VISSIM. This paper first describes the calibration procedure step by step, and then applies the method to a case study of simulating traffic at a signalized intersection in VISSIM. From the field-collected video footage, trajectories of 1229 through-movement vehicles were extracted and analyzed to calibrate three car-following parameters regarding desired speed, desired acceleration, and safe following distance, respectively. The case study demonstrates the advantages and feasibility of the proposed approach.

Triangulation-based edge measurement using polyview optics

Science.gov (United States)

Li, Yinan; Kästner, Markus; Reithmeier, Eduard

2018-04-01

Laser triangulation sensors as non-contact measurement devices are widely used in industry and research for profile measurements and quantitative inspections. Some technical applications e.g. edge measurements usually require a configuration of a single sensor and a translation stage or a configuration of multiple sensors, so that they can measure a large measurement range that is out of the scope of a single sensor. However, the cost of both configurations is high, due to the additional rotational axis or additional sensor. This paper provides a special measurement system for measurement of great curved surfaces based on a single sensor configuration. Utilizing a self-designed polyview optics and calibration process, the proposed measurement system allows an over 180° FOV (field of view) with a precise measurement accuracy as well as an advantage of low cost. The detailed capability of this measurement system based on experimental data is discussed in this paper.

Novel welding image processing method based on fractal theory

Institute of Scientific and Technical Information of China (English)

陈强; 孙振国; 肖勇; 路井荣

2002-01-01

Computer vision has come into used in the fields of welding process control and automation. In order to improve precision and rapidity of welding image processing, a novel method based on fractal theory has been put forward in this paper. Compared with traditional methods, the image is preliminarily processed in the macroscopic regions then thoroughly analyzed in the microscopic regions in the new method. With which, an image is divided up to some regions according to the different fractal characters of image edge, and the fuzzy regions including image edges are detected out, then image edges are identified with Sobel operator and curved by LSM (Lease Square Method). Since the data to be processed have been decreased and the noise of image has been reduced, it has been testified through experiments that edges of weld seam or weld pool could be recognized correctly and quickly.

Prevalence and regional correlates of road traffic injury among Chinese urban residents: A 21-city population-based study.

Science.gov (United States)

Rockett, Ian R H; Jiang, Shuhan; Yang, Qian; Yang, Tingzhong; Yang, Xiaozhao Y; Peng, Sihui; Yu, Lingwei

2017-08-18

This study estimated the prevalence of road traffic injury among Chinese urban residents and examined individual and regional-level correlates. A cross-sectional multistage process was used to sample residents from 21 selected cities in China. Survey respondents reported their history of road traffic injury in the past 12 months through a community survey. Multilevel, multivariable logistic regression analysis was used to identify injury correlates. Based on a retrospective 12-month reporting window, road traffic injury prevalence among urban residents was 13.2%. Prevalence of road traffic injury, by type, was 8.7, 8.7, 8.5, and 7.7% in the automobile, bicycle, motorcycle, and pedestrian categories, respectively. Multilevel analysis showed that prevalence of road traffic injury was positively associated with minority status, income, and mental health disorder score at the individual level. Regionally, road traffic injury was associated with geographic location of residence and prevalence of mental health disorders. Both individual and regional-level variables were associated with road traffic injury among Chinese urban residents, a finding whose implications transcend wholesale imported generic solutions. This descriptive research demonstrates an urgent need for longitudinal studies across China on risk and protective factors, in order to inform injury etiology, surveillance, prevention, treatment, and evaluation.

Real-time biscuit tile image segmentation method based on edge detection.

Science.gov (United States)

Matić, Tomislav; Aleksi, Ivan; Hocenski, Željko; Kraus, Dieter

2018-05-01

In this paper we propose a novel real-time Biscuit Tile Segmentation (BTS) method for images from ceramic tile production line. BTS method is based on signal change detection and contour tracing with a main goal of separating tile pixels from background in images captured on the production line. Usually, human operators are visually inspecting and classifying produced ceramic tiles. Computer vision and image processing techniques can automate visual inspection process if they fulfill real-time requirements. Important step in this process is a real-time tile pixels segmentation. BTS method is implemented for parallel execution on a GPU device to satisfy the real-time constraints of tile production line. BTS method outperforms 2D threshold-based methods, 1D edge detection methods and contour-based methods. Proposed BTS method is in use in the biscuit tile production line. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Edge detection of solid motor' CT image based on gravitation model

International Nuclear Information System (INIS)

Yu Guanghui; Lu Hongyi; Zhu Min; Liu Xudong; Hou Zhiqiang

2012-01-01

In order to detect the edge of solid motor' CT image much better, a new edge detection operator base on gravitation model was put forward. The edge of CT image is got by the new operator. The superiority turned out by comparing the edge got by ordinary operator. The comparison among operators with different size shows that higher quality CT images need smaller size operator while the lower need the larger. (authors)

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems.

Science.gov (United States)

Ma, Xingpo; Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-02-10

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data are processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems

Science.gov (United States)

Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-01-01

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems. PMID:29439442

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems

Directory of Open Access Journals (Sweden)

Xingpo Ma

2018-02-01

Full Text Available In the post-Cloud era, the proliferation of Internet of Things (IoT has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.

Discovering urban mobility patterns with PageRank based traffic modeling and prediction

Science.gov (United States)

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

2017-11-01

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

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.

Application of the user-centred design process according ISO 9241-210 in air traffic control.

Science.gov (United States)

König, Christina; Hofmann, Thomas; Bruder, Ralph

2012-01-01

Designing a usable human machine interface for air traffic control is challenging and should follow approved methods. The ISO 9241-210 standard promises high usability of products by integrating future users and following an iterative process. This contribution describes the proceeding and first results of the analysis and application of ISO 9241-210 to develop a planning tool for air traffic controllers.

DRAWING FOR TRAFFIC MARKING USING BIDIRECTIONAL GRADIENT-BASED DETECTION WITH MMS LIDAR INTENSITY

Directory of Open Access Journals (Sweden)

G. Takahashi

2016-06-01

Full Text Available Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS equipped with high-density Laser imaging Detection and Ranging (LiDAR scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014. The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

Drawing for Traffic Marking Using Bidirectional Gradient-Based Detection with MMS LIDAR Intensity

Science.gov (United States)

Takahashi, G.; Takeda, H.; Nakamura, K.

2016-06-01

Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS) equipped with high-density Laser imaging Detection and Ranging (LiDAR) scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014). The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

Traffic Infrastructure in the Development of the Croatian Traffic System

Directory of Open Access Journals (Sweden)

Damir Šimulčik

2012-10-01

Full Text Available The absence of a long-term traffic policy and of the policyof financing the constntction and maintenance of traffic infrastructurefacilities, represents a synthesis of numerous unresolvedrelations whose negative effects are felt in the overalleconomic and traffic development and consequently theevaluation of national potentials in the field. Adverse aspectcaused by the lack of a clear and feasible policy of financing thetraffic infrastructure facilities, is also a result of not having definedan adequate traffic policy, programme and strategiccourses of development, nor financing models that would be inaccordance with the market and economy system.This indicates that it is necessary to determine a policy forfinancing the constntction and maintenance of traffic infrastntcture,which has to be based on scientific development,team work, availability of plans and programmes to scientistsand experts, determined methodology based on marketing andeconomic logic in defining the programme and strategic tasksand assignments so as to make them feasible.In the near future, intensive preparations for investments inthe overall traffic sysiem are necessary, especially regarding thetraffic infrastntcture facilities - the pivotal points in the processof evaluating the traffic in our national tenitory. Croatia needsto define clearly its strategy in constructing and maintaining thegeneral traffic infrastructure, appointing at the same time thosewho will carry out the given tasks.

Intelligent Control in Automation Based on Wireless Traffic Analysis

Energy Technology Data Exchange (ETDEWEB)

Kurt Derr; Milos Manic

2007-08-01

Wireless technology is a central component of many factory automation infrastructures in both the commercial and government sectors, providing connectivity among various components in industrial realms (distributed sensors, machines, mobile process controllers). However wireless technologies provide more threats to computer security than wired environments. The advantageous features of Bluetooth technology resulted in Bluetooth units shipments climbing to five million per week at the end of 2005 [1, 2]. This is why the real-time interpretation and understanding of Bluetooth traffic behavior is critical in both maintaining the integrity of computer systems and increasing the efficient use of this technology in control type applications. Although neuro-fuzzy approaches have been applied to wireless 802.11 behavior analysis in the past, a significantly different Bluetooth protocol framework has not been extensively explored using this technology. This paper presents a new neurofuzzy traffic analysis algorithm of this still new territory of Bluetooth traffic. Further enhancements of this algorithm are presented along with the comparison against the traditional, numerical approach. Through test examples, interesting Bluetooth traffic behavior characteristics were captured, and the comparative elegance of this computationally inexpensive approach was demonstrated. This analysis can be used to provide directions for future development and use of this prevailing technology in various control type applications, as well as making the use of it more secure.

Intelligent Control in Automation Based on Wireless Traffic Analysis

Energy Technology Data Exchange (ETDEWEB)

Kurt Derr; Milos Manic

2007-09-01

Wireless technology is a central component of many factory automation infrastructures in both the commercial and government sectors, providing connectivity among various components in industrial realms (distributed sensors, machines, mobile process controllers). However wireless technologies provide more threats to computer security than wired environments. The advantageous features of Bluetooth technology resulted in Bluetooth units shipments climbing to five million per week at the end of 2005 [1, 2]. This is why the real-time interpretation and understanding of Bluetooth traffic behavior is critical in both maintaining the integrity of computer systems and increasing the efficient use of this technology in control type applications. Although neuro-fuzzy approaches have been applied to wireless 802.11 behavior analysis in the past, a significantly different Bluetooth protocol framework has not been extensively explored using this technology. This paper presents a new neurofuzzy traffic analysis algorithm of this still new territory of Bluetooth traffic. Further enhancements of this algorithm are presented along with the comparison against the traditional, numerical approach. Through test examples, interesting Bluetooth traffic behavior characteristics were captured, and the comparative elegance of this computationally inexpensive approach was demonstrated. This analysis can be used to provide directions for future development and use of this prevailing technology in various control type applications, as well as making the use of it more secure.

WAP Based An Alternative Solution for Traffic Transportation Problem in Sidoarjo Surrounding Area Using AHP

Directory of Open Access Journals (Sweden)

Arna Fariza

2009-08-01

Full Text Available In line with the increasing interest on Lapindo mud disaster which causes several roadway covered by mud, there is a need to give an alternative solution for traffic transportation problem in surrounding area. The possible criteria for the solution of this road way are length, surface, traffic, and width of the road. Types of vehicle across the road also give a contribution to the criteria. By using Geography Information System (GIS, it is easy to all drivers to take decision which way has to be chosen based on the real condition. GIS is used to visualize the alternative road, which is possible to take. Analytic Hierarchy Processing (AHP is a decision method which is based on many criteria and alternatives. The input of AHP can be a preference or real value. Applied AHP to decide value of each alternative is based on application of Wireless Application Protocol (WAP assessment.

A robust sub-pixel edge detection method of infrared image based on tremor-based retinal receptive field model

Science.gov (United States)

Gao, Kun; Yang, Hu; Chen, Xiaomei; Ni, Guoqiang

2008-03-01

Because of complex thermal objects in an infrared image, the prevalent image edge detection operators are often suitable for a certain scene and extract too wide edges sometimes. From a biological point of view, the image edge detection operators work reliably when assuming a convolution-based receptive field architecture. A DoG (Difference-of- Gaussians) model filter based on ON-center retinal ganglion cell receptive field architecture with artificial eye tremors introduced is proposed for the image contour detection. Aiming at the blurred edges of an infrared image, the subsequent orthogonal polynomial interpolation and sub-pixel level edge detection in rough edge pixel neighborhood is adopted to locate the foregoing rough edges in sub-pixel level. Numerical simulations show that this method can locate the target edge accurately and robustly.

An Interactive Procedure to Preserve the Desired Edges during the Image Processing of Noise Reduction

Directory of Open Access Journals (Sweden)

Lin-Tsang Lee

2010-01-01

Full Text Available The paper propose a new procedure including four stages in order to preserve the desired edges during the image processing of noise reduction. A denoised image can be obtained from a noisy image at the first stage of the procedure. At the second stage, an edge map can be obtained by the Canny edge detector to find the edges of the object contours. Manual modification of an edge map at the third stage is optional to capture all the desired edges of the object contours. At the final stage, a new method called Edge Preserved Inhomogeneous Diffusion Equation (EPIDE is used to smooth the noisy images or the previously denoised image at the first stage for achieving the edge preservation. The Optical Character Recognition (OCR results in the experiments show that the proposed procedure has the best recognition result because of the capability of edge preservation.

The Traffic Signal Acquisition System Based on GPS and SD Card Storage

Directory of Open Access Journals (Sweden)

LIU Chang-yuan

2017-06-01

Full Text Available In terms of the issues where traffic lights’ positions and traffic status information cannot be managed automatically，in this system，STC12C5A60S2 microcontroller can be used as the master chip in conjunction with the GPS position module，Neo-5Q. The wireless transceiver module，PT2262 /2272 and the portable installing SD card are used to design a new type of real-time information acquisition solution for positions of traffic lights and signal status. And the system can determine the traffic lights’ positions and the process of lighting in a real time. Then the data will be stored in SD card by the SD card module. Furthermore，the equipment can be implemented on existing facilities with a simple circuit. According to the result of experiments，the system contains a convenient storage，works in a real time and it is also advisable to help with the data reading and analysis. Thus， implementation of the system is of great significance to acquire and analyze the traffic status information in recent times.

Knowledge-based driver assistance systems traffic situation description and situation feature relevance

CERN Document Server

Huelsen, Michael

2014-01-01

The comprehension of a traffic situation plays a major role in driving a vehicle. Interpretable information forms a basis for future projection, decision making and action performing, such as navigating, maneuvering and driving control. Michael Huelsen provides an ontology-based generic traffic situation description capable of supplying various advanced driver assistance systems with relevant information about the current traffic situation of a vehicle and its environment. These systems are enabled to perform reasonable actions and approach visionary goals such as injury and accident free driv

Time-based collision risk modeling for air traffic management

Science.gov (United States)

Bell, Alan E.

Since the emergence of commercial aviation in the early part of last century, economic forces have driven a steadily increasing demand for air transportation. Increasing density of aircraft operating in a finite volume of airspace is accompanied by a corresponding increase in the risk of collision, and in response to a growing number of incidents and accidents involving collisions between aircraft, governments worldwide have developed air traffic control systems and procedures to mitigate this risk. The objective of any collision risk management system is to project conflicts and provide operators with sufficient opportunity to recognize potential collisions and take necessary actions to avoid them. It is therefore the assertion of this research that the currency of collision risk management is time. Future Air Traffic Management Systems are being designed around the foundational principle of four dimensional trajectory based operations, a method that replaces legacy first-come, first-served sequencing priorities with time-based reservations throughout the airspace system. This research will demonstrate that if aircraft are to be sequenced in four dimensions, they must also be separated in four dimensions. In order to separate aircraft in four dimensions, time must emerge as the primary tool by which air traffic is managed. A functional relationship exists between the time-based performance of aircraft, the interval between aircraft scheduled to cross some three dimensional point in space, and the risk of collision. This research models that relationship and presents two key findings. First, a method is developed by which the ability of an aircraft to meet a required time of arrival may be expressed as a robust standard for both industry and operations. Second, a method by which airspace system capacity may be increased while maintaining an acceptable level of collision risk is presented and demonstrated for the purpose of formulating recommendations for procedures

Simulation-based MDP verification for leading-edge masks

Science.gov (United States)

Su, Bo; Syrel, Oleg; Pomerantsev, Michael; Hagiwara, Kazuyuki; Pearman, Ryan; Pang, Leo; Fujimara, Aki

2017-07-01

For IC design starts below the 20nm technology node, the assist features on photomasks shrink well below 60nm and the printed patterns of those features on masks written by VSB eBeam writers start to show a large deviation from the mask designs. Traditional geometry-based fracturing starts to show large errors for those small features. As a result, other mask data preparation (MDP) methods have become available and adopted, such as rule-based Mask Process Correction (MPC), model-based MPC and eventually model-based MDP. The new MDP methods may place shot edges slightly differently from target to compensate for mask process effects, so that the final patterns on a mask are much closer to the design (which can be viewed as the ideal mask), especially for those assist features. Such an alteration generally produces better masks that are closer to the intended mask design. Traditional XOR-based MDP verification cannot detect problems caused by eBeam effects. Much like model-based OPC verification which became a necessity for OPC a decade ago, we see the same trend in MDP today. Simulation-based MDP verification solution requires a GPU-accelerated computational geometry engine with simulation capabilities. To have a meaningful simulation-based mask check, a good mask process model is needed. The TrueModel® system is a field tested physical mask model developed by D2S. The GPU-accelerated D2S Computational Design Platform (CDP) is used to run simulation-based mask check, as well as model-based MDP. In addition to simulation-based checks such as mask EPE or dose margin, geometry-based rules are also available to detect quality issues such as slivers or CD splits. Dose margin related hotspots can also be detected by setting a correct detection threshold. In this paper, we will demonstrate GPU-acceleration for geometry processing, and give examples of mask check results and performance data. GPU-acceleration is necessary to make simulation-based mask MDP verification

Development of a Gridded Maritime Traffic DB for e-Navigation

Directory of Open Access Journals (Sweden)

Kwang-Il Kim

2014-12-01

Full Text Available In the era of e-Navigation, it is important to deliver maritime traffic information from a shore based station to all navigating vessels. However, in a vessel boarding system, there is a limit to the amount of raw traffic data that can be processed. In this paper, we used the Automatic Identification System (AIS data as metadata to build up the maritime traffic gridded database by projecting traffic data on a geographic coordinate system. In order to apply this database to the image layer for transferring to the ship efficiently, we have developed a maritime traffic display layer and route traffic information layer. All simulated data was collected and analyzed with the AIS in a Vessel Traffic Service(VTS center.

Power supply of Eurotunnel. Optimisation based on traffic and simulation studies

Energy Technology Data Exchange (ETDEWEB)

Marie, Stephane [SNCF, Direction de l' Ingenierie, Saint-Denis (France). Dept. des Installations Fixes de Traction Electrique; Dupont, Jean-Pierre; Findinier, Bertrand; Maquaire, Christian [Eurotunnel, Coquelles (France)

2010-12-15

In order to reduce electrical power costs and also to cope with the significant traffic increase, a new study was carried on feeding the tunnel section from the French power station, thus improving and reinforcing the existing network. Based on a design study established by SNCF engineering department, EUROTUNNEL chose a new electrical scheme to cope with the traffic increase and optimise investments. (orig.)

Transit Traffic Analysis Zone Delineating Method Based on Thiessen Polygon

Directory of Open Access Journals (Sweden)

Shuwei Wang

2014-04-01

Full Text Available A green transportation system composed of transit, busses and bicycles could be a significant in alleviating traffic congestion. However, the inaccuracy of current transit ridership forecasting methods is imposing a negative impact on the development of urban transit systems. Traffic Analysis Zone (TAZ delineating is a fundamental and essential step in ridership forecasting, existing delineating method in four-step models have some problems in reflecting the travel characteristics of urban transit. This paper aims to come up with a Transit Traffic Analysis Zone delineation method as supplement of traditional TAZs in transit service analysis. The deficiencies of current TAZ delineating methods were analyzed, and the requirements of Transit Traffic Analysis Zone (TTAZ were summarized. Considering these requirements, Thiessen Polygon was introduced into TTAZ delineating. In order to validate its feasibility, Beijing was then taken as an example to delineate TTAZs, followed by a spatial analysis of office buildings within a TTAZ and transit station departure passengers. Analysis result shows that the TTAZs based on Thiessen polygon could reflect the transit travel characteristic and is of in-depth research value.

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...

Research on reducing the edge effect in magnetorheological finishing.

Science.gov (United States)

Hu, Hao; Dai, Yifan; Peng, Xiaoqiang; Wang, Jianmin

2011-03-20

The edge effect could not be avoided in most optical manufacturing methods based on the theory of computer controlled optical surfacing. The difference between the removal function at the workpiece edge and that inside it is also the primary cause for edge effect in magnetorheological finishing (MRF). The change of physical dimension and removal ratio of the removal function is investigated through experiments. The results demonstrate that the situation is different when MRF "spot" is at the leading edge or at the trailing edge. Two methods for reducing the edge effect are put into practice after analysis of the processing results. One is adopting a small removal function for dealing with the workpiece edge, and the other is utilizing the removal function compensation. The actual processing results show that these two ways are both effective on reducing the edge effect in MRF.

Edge-preserving Intra Depth Coding based on Context-coding and H.264/AVC

DEFF Research Database (Denmark)

Zamarin, Marco; Salmistraro, Matteo; Forchhammer, Søren

2013-01-01

Depth map coding plays a crucial role in 3D Video communication systems based on the “Multi-view Video plus Depth” representation as view synthesis performance is strongly affected by the accuracy of depth information, especially at edges in the depth map image. In this paper an efficient algorithm...... for edge-preserving intra depth compression based on H.264/AVC is presented. The proposed method introduces a new Intra mode specifically targeted to depth macroblocks with arbitrarily shaped edges, which are typically not efficiently represented by DCT. Edge macroblocks are partitioned into two regions...... each approximated by a flat surface. Edge information is encoded by means of contextcoding with an adaptive template. As a novel element, the proposed method allows exploiting the edge structure of previously encoded edge macroblocks during the context-coding step to further increase compression...

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)

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.

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

Science.gov (United States)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

Edge Detection Algorithm Based on Fuzzy Logic Theory for a Local Vision System of Robocup Humanoid League

Directory of Open Access Journals (Sweden)

Andrea K. Perez-Hernandez

2013-06-01

Full Text Available At this paper we shown the development of an algorithm to perform edges extraction based on fuzzy logic theory. This method allows recognizing landmarks on the game field for Humanoid League of RoboCup. The proposed algorithm describes the creation of a fuzzy inference system that permit evaluate the existent relationship between image pixels, finding variations on grey levels of related neighbor pixels. Subsequently, it shows an implementation of OTSU method to binarize an image that was obtained from fuzzy process and so generate an image containing only extracted edges, validating the algorithm with Humanoid League images. Later, we analyze obtained results that evidence a good performance of algorithm, considering that this proposal only takes an extra 35% processing time that will be required by traditional methods, whereas extracted edges are 52% less noise susceptible.

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.

Monitoring individual traffic flows within the ATLAS TDAQ network

International Nuclear Information System (INIS)

Sjoen, R; Batraneanu, S M; Leahu, L; Martin, B; Al-Shabibi, A; Stancu, S; Ciobotaru, M

2010-01-01

The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities and limitations of this diagnostic tool, giving an example of its use in solving system problems that arise during the ATLAS data taking.

A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

Directory of Open Access Journals (Sweden)

Meng Fan-Bo

2016-01-01

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

Use of agent based simulation for traffic safety assessment

CSIR Research Space (South Africa)

Conradie, Dirk CU

2008-07-01

Full Text Available This paper describes the development of an agent based Computational Building Simulation (CBS) tool, termed KRONOS that is being used to work on advanced research questions such as traffic safety assessment and user behaviour in buildings...

The ship edge feature detection based on high and low threshold for remote sensing image

Science.gov (United States)

Li, Xuan; Li, Shengyang

2018-05-01

In this paper, a method based on high and low threshold is proposed to detect the ship edge feature due to the low accuracy rate caused by the noise. Analyze the relationship between human vision system and the target features, and to determine the ship target by detecting the edge feature. Firstly, using the second-order differential method to enhance the quality of image; Secondly, to improvement the edge operator, we introduction of high and low threshold contrast to enhancement image edge and non-edge points, and the edge as the foreground image, non-edge as a background image using image segmentation to achieve edge detection, and remove the false edges; Finally, the edge features are described based on the result of edge features detection, and determine the ship target. The experimental results show that the proposed method can effectively reduce the number of false edges in edge detection, and has the high accuracy of remote sensing ship edge detection.

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.

Edge sealing for low cost stability enhancement of roll-to-roll processed flexible polymer solar cell modules

DEFF Research Database (Denmark)

Tanenbaum, David M.; Dam, Henrik Friis; Rösch, R.

2012-01-01

Fully roll-to-roll processed polymer solar cell modules were prepared, characterized, and laminated. Cell modules were cut from the roll and matched pairs were selected, one module with exposed cut edges, the other laminated again with the same materials and adhesive sealing fully around the cut...... edges. The edge sealing rim was 10 mm wide. Cell modules were characterized by periodic measurements of IV curves over extended periods in a variety of conditions, as well as by a variety of spatial imaging techniques. Data show significant stability benefits of the edge sealing process. The results...

Energy Savings in Cellular Networks Based on Space-Time Structure of Traffic Loads

Science.gov (United States)

Sun, Jingbo; Wang, Yue; Yuan, Jian; Shan, Xiuming

Since most of energy consumed by the telecommunication infrastructure is due to the Base Transceiver Station (BTS), switching off BTSs when traffic load is low has been recognized as an effective way of saving energy. In this letter, an energy saving scheme is proposed to minimize the number of active BTSs based on the space-time structure of traffic loads as determined by principal component analysis. Compared to existing methods, our approach models traffic loads more accurately, and has a much smaller input size. As it is implemented in an off-line manner, our scheme also avoids excessive communications and computing overheads. Simulation results show that the proposed method has a comparable performance in energy savings.

Fuzzy Logic Based Edge Detection in Smooth and Noisy Clinical Images.

Directory of Open Access Journals (Sweden)

Izhar Haq

Full Text Available Edge detection has beneficial applications in the fields such as machine vision, pattern recognition and biomedical imaging etc. Edge detection highlights high frequency components in the image. Edge detection is a challenging task. It becomes more arduous when it comes to noisy images. This study focuses on fuzzy logic based edge detection in smooth and noisy clinical images. The proposed method (in noisy images employs a 3 × 3 mask guided by fuzzy rule set. Moreover, in case of smooth clinical images, an extra mask of contrast adjustment is integrated with edge detection mask to intensify the smooth images. The developed method was tested on noise-free, smooth and noisy images. The results were compared with other established edge detection techniques like Sobel, Prewitt, Laplacian of Gaussian (LOG, Roberts and Canny. When the developed edge detection technique was applied to a smooth clinical image of size 270 × 290 pixels having 24 dB 'salt and pepper' noise, it detected very few (22 false edge pixels, compared to Sobel (1931, Prewitt (2741, LOG (3102, Roberts (1451 and Canny (1045 false edge pixels. Therefore it is evident that the developed method offers improved solution to the edge detection problem in smooth and noisy clinical images.

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

Energy-efficient multicast traffic grooming strategy based on light-tree splitting for elastic optical networks

Science.gov (United States)

Liu, Huanlin; Yin, Yarui; Chen, Yong

2017-07-01

In order to address the problem of optimizing the spectrum resources and power consumption in elastic optical networks (EONs), we investigate the potential gains by jointly employing the light-tree splitting and traffic grooming for multicast requests. An energy-efficient multicast traffic grooming strategy based on light-tree splitting (EED-MTGS-LS) is proposed in this paper. Firstly, we design a traffic pre-processing mechanism to decide the multicast requests' routing order, which considers the request's bandwidth requirement and physical hops synthetically. Then, by dividing a light-tree to some sub-light-trees and grooming the request to these sub-light-trees, the light-tree sharing ratios of multicast requests can be improved. What's more, a priority scheduling vector is constructed, which aims to improve the success rate of spectrum assignment for grooming requests. Finally, a grooming strategy is designed to optimize the total power consumption by reducing the use of transponders and IP routers during routing. Simulation results show that the proposed strategy can significantly improve the spectrum utilization and save the power consumption.

Traffic Dynamics of Computer Networks

Science.gov (United States)

Fekete, Attila

2008-10-01

Two important aspects of the Internet, namely the properties of its topology and the characteristics of its data traffic, have attracted growing attention of the physics community. My thesis has considered problems of both aspects. First I studied the stochastic behavior of TCP, the primary algorithm governing traffic in the current Internet, in an elementary network scenario consisting of a standalone infinite-sized buffer and an access link. The effect of the fast recovery and fast retransmission (FR/FR) algorithms is also considered. I showed that my model can be extended further to involve the effect of link propagation delay, characteristic of WAN. I continued my thesis with the investigation of finite-sized semi-bottleneck buffers, where packets can be dropped not only at the link, but also at the buffer. I demonstrated that the behavior of the system depends only on a certain combination of the parameters. Moreover, an analytic formula was derived that gives the ratio of packet loss rate at the buffer to the total packet loss rate. This formula makes it possible to treat buffer-losses as if they were link-losses. Finally, I studied computer networks from a structural perspective. I demonstrated through fluid simulations that the distribution of resources, specifically the link bandwidth, has a serious impact on the global performance of the network. Then I analyzed the distribution of edge betweenness in a growing scale-free tree under the condition that a local property, the in-degree of the "younger" node of an arbitrary edge, is known in order to find an optimum distribution of link capacity. The derived formula is exact even for finite-sized networks. I also calculated the conditional expectation of edge betweenness, rescaled for infinite networks.

A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks

Directory of Open Access Journals (Sweden)

Nadia Adnan Shiltagh

2015-11-01

Full Text Available Wireless Multimedia Sensor Networks (WMSNs are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC. The Modify Spike Neural Network controller (MSNC can calculate the appropriate traffic load parameter μ for each parent node and then use in the EWPBRC algorithm to estimate the transmission rate of parent nodes and then assign a suitable transmission rate for each child node. A comparative study between (MSNTLP with EWBPRC and fuzzy logic controller for traffic load parameter with Exponential Weight of Priority Based Rate Control algorithm (FTLP with EWBPRC algorithm shows that the (MSNTLP with EWBPRC is more efficient than (FTLP with EWBPRC algorithm in terms of packet loss, queue delay and throughput. Another comparative study between (MSNTLP with EWBPRC and EWBPRC with fixed traffic load parameter (µ shows that the MSNTLP with EWBPRC is more efficient than EWBPRC with fixed traffic load parameter (µ in terms of packet loss ratio and queue delay. A simulation process is developed and tested using the network simulator _2 (NS2 in a computer having the following properties: windows 7 (64-bit, core i7, RAM 8GB, hard 1TB.

Effects of experimentally elevated traffic noise on nestling white-crowned sparrow stress physiology, immune function and life history.

Science.gov (United States)

Crino, Ondi L; Johnson, Erin E; Blickley, Jessica L; Patricelli, Gail L; Breuner, Creagh W

2013-06-01

Roads have been associated with behavioral and physiological changes in wildlife. In birds, roads decrease reproductive success and biodiversity and increase physiological stress. Although the consequences of roads on individuals and communities have been well described, the mechanisms through which roads affect birds remain largely unexplored. Here, we examine one mechanism through which roads could affect birds: traffic noise. We exposed nestling mountain white-crowned sparrows (Zonotrichia leucophrys oriantha) to experimentally elevated traffic noise for 5 days during the nestling period. Following exposure to traffic noise we measured nestling stress physiology, immune function, body size, condition and survival. Based on prior studies, we expected the traffic noise treatment to result in elevated stress hormones (glucocorticoids), and declines in immune function, body size, condition and survival. Surprisingly, nestlings exposed to traffic noise had lower glucocorticoid levels and improved condition relative to control nests. These results indicate that traffic noise does affect physiology and development in white-crowned sparrows, but not at all as predicted. Therefore, when evaluating the mechanisms through which roads affect avian populations, other factors (e.g. edge effects, pollution and mechanical vibration) may be more important than traffic noise in explaining elevated nestling stress responses in this species.

Smart Traffic Management Protocol Based on VANET architecture

Directory of Open Access Journals (Sweden)

Amilcare Francesco Santamaria

2014-01-01

Full Text Available Nowadays one of the hottest theme in wireless environments research is the application of the newest technologies to road safety problems and traffic management exploiting the (VANET architecture. In this work, a novel protocol that aims to achieve a better traffic management is proposed. The overal system is able to reduce traffic level inside the city exploiting inter-communication among vehicles and support infrastructures also known as (V2V and (V2I communications. We design a network protocol called (STMP that takes advantages of IEEE 802.11p standard. On each road several sensors system are placed and they are responsible of monitoring. Gathered data are spread in the network exploiting ad-hoc protocol messages. The increasing knowledge about environment conditions make possible to take preventive actions. Moreover, having a realtime monitoring of the lanes it is possible to reveal roads and city blocks congestions in a shorter time. An external entity to the (VANET is responsible to manage traffic and rearrange traffic along the lanes of the city avoiding huge traffic levels.

Modeling the Acid-Base Properties of Montmorillonite Edge Surfaces.

Science.gov (United States)

Tournassat, Christophe; Davis, James A; Chiaberge, Christophe; Grangeon, Sylvain; Bourg, Ian C

2016-12-20

The surface reactivity of clay minerals remains challenging to characterize because of a duality of adsorption surfaces and mechanisms that does not exist in the case of simple oxide surfaces: edge surfaces of clay minerals have a variable proton surface charge arising from hydroxyl functional groups, whereas basal surfaces have a permanent negative charge arising from isomorphic substitutions. Hence, the relationship between surface charge and surface potential on edge surfaces cannot be described using the Gouy-Chapman relation, because of a spillover of negative electrostatic potential from the basal surface onto the edge surface. While surface complexation models can be modified to account for these features, a predictive fit of experimental data was not possible until recently, because of uncertainty regarding the densities and intrinsic pK a values of edge functional groups. Here, we reexamine this problem in light of new knowledge on intrinsic pK a values obtained over the past decade using ab initio molecular dynamics simulations, and we propose a new formalism to describe edge functional groups. Our simulation results yield reasonable predictions of the best available experimental acid-base titration data.

Urbanization Impacts on Mammals across Urban-Forest Edges and a Predictive Model of Edge Effects

OpenAIRE

Villaseñor, Nélida R.; Driscoll, Don A.; Escobar, Martín A. H.; Gibbons, Philip; Lindenmayer, David B.

2014-01-01

With accelerating rates of urbanization worldwide, a better understanding of ecological processes at the wildland-urban interface is critical to conserve biodiversity. We explored the effects of high and low-density housing developments on forest-dwelling mammals. Based on habitat characteristics, we expected a gradual decline in species abundance across forest-urban edges and an increased decline rate in higher contrast edges. We surveyed arboreal mammals in sites of high and low housing den...

Actual situation analyses of rat-run traffic on community streets based on car probe data

Science.gov (United States)

Sakuragi, Yuki; Matsuo, Kojiro; Sugiki, Nao

2017-10-01

Lowering of so-called "rat-run" traffic on community streets has been one of significant challenges for improving the living environment of neighborhood. However, it has been difficult to quantitatively grasp the actual situation of rat-run traffic by the traditional surveys such as point observations. This study aims to develop a method for extracting rat-run traffic based on car probe data. In addition, based on the extracted rat-run traffic in Toyohashi city, Japan, we try to analyze the actual situation such as time and location distribution of the rat-run traffic. As a result, in Toyohashi city, the rate of using rat-run route increases in peak time period. Focusing on the location distribution of rat-run traffic, in addition, they pass through a variety of community streets. There is no great inter-district bias of the route frequently used as rat-run traffic. Next, we focused on some trips passing through a heavily used route as rat-run traffic. As a result, we found the possibility that they habitually use the route as rat-run because their trips had some commonalities. We also found that they tend to use the rat-run route due to shorter distance than using the alternative highway route, and that the travel speeds were faster than using the alternative highway route. In conclusions, we confirmed that the proposed method can quantitatively grasp the actual situation and the phenomenal tendencies of the rat-run traffic.

Traffic Light Options

DEFF Research Database (Denmark)

Jørgensen, Peter Løchte

This paper introduces, prices, and analyzes traffic light options. The traffic light option is an innovative structured OTC derivative developed independently by several London-based investment banks to suit the needs of Danish life and pension (L&P) companies, which must comply with the traffic...... 2006, and supervisory authorities in many other European countries have implemented similar regulation. Traffic light options are therefore likely to attract the attention of a wider audience of pension fund managers in the future. Focusing on the valuation of the traffic light option we set up a Black...... light scenarios. These stress scenarios entail drops in interest rates as well as in stock prices, and traffic light options are thus designed to pay off and preserve sufficient capital when interest rates and stock prices fall simultaneously. Sweden's FSA implemented a traffic light system in January...

Traffic Light Options

DEFF Research Database (Denmark)

Jørgensen, Peter Løchte

2007-01-01

This paper introduces, prices, and analyzes traffic light options. The traffic light option is an innovative structured OTC derivative developed independently by several London-based investment banks to suit the needs of Danish life and pension (L&P) companies, which must comply with the traffic...... 2006, and supervisory authorities in many other European countries have implemented similar regulation. Traffic light options are therefore likely to attract the attention of a wider audience of pension fund managers in the future. Focusing on the valuation of the traffic light option we set up a Black...... light scenarios. These stress scenarios entail drops in interest rates as well as in stock prices, and traffic light options are thus designed to pay off and preserve sufficient capital when interest rates and stock prices fall simultaneously. Sweden's FSA implemented a traffic light system in January...

Autonomic urban traffic optimization using data analytics

OpenAIRE

Garriga Porqueras, Albert

2017-01-01

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

Traffic analysis and signal processing in optical packet switched networks

DEFF Research Database (Denmark)

Fjelde, Tina

2002-01-01

/s optical packet switched network exploiting the best of optics and electronics, is used as a thread throughout the thesis. An overview of the DAVID network architecture is given, focussing on the MAN and WAN architecture as well as the MPLS-based network hierarchy. Subsequently, the traffic performance...... of the DAVID core optical packet router, which exploits wavelength conversion and fibre delay-line buffers for contention resolution, is analysed using a numerical model developed for that purpose. The robustness of the shared recirculating loop buffer with respect to´bursty traffic is demonstrated...... the injection of an additional clock signal into the IWC is presented. Results show very good transmission capabilities combined with a high-speed response. It is argued that signal regeneration is an inherent attribute of the IWC employed as a wavelength converter due to the sinusoidal transfer function...

Right-­turn traffic volume adjustment in traffic signal warrant analysis : final report.

Science.gov (United States)

2016-05-06

This report was based on the research project, Right-Turn Traffic Volume Adjustment in Traffic Signal Warrants, sponsored by the Nevada Department of Transportation (NDOT) and SOLARIS. Right-turn traffic does not affect intersection performance in th...

A Multi-Classification Method of Improved SVM-based Information Fusion for Traffic Parameters Forecasting

Directory of Open Access Journals (Sweden)

Hongzhuan Zhao

2016-04-01

Full Text Available With the enrichment of perception methods, modern transportation system has many physical objects whose states are influenced by many information factors so that it is a typical Cyber-Physical System (CPS. Thus, the traffic information is generally multi-sourced, heterogeneous and hierarchical. Existing research results show that the multisourced traffic information through accurate classification in the process of information fusion can achieve better parameters forecasting performance. For solving the problem of traffic information accurate classification, via analysing the characteristics of the multi-sourced traffic information and using redefined binary tree to overcome the shortcomings of the original Support Vector Machine (SVM classification in information fusion, a multi-classification method using improved SVM in information fusion for traffic parameters forecasting is proposed. The experiment was conducted to examine the performance of the proposed scheme, and the results reveal that the method can get more accurate and practical outcomes.

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

Science.gov (United States)

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

Assessment of traffic noise levels in urban areas using different soft computing techniques.

Science.gov (United States)

Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D

2016-10-01

Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.

Automatic comic page image understanding based on edge segment analysis

Science.gov (United States)

Liu, Dong; Wang, Yongtao; Tang, Zhi; Li, Luyuan; Gao, Liangcai

2013-12-01

Comic page image understanding aims to analyse the layout of the comic page images by detecting the storyboards and identifying the reading order automatically. It is the key technique to produce the digital comic documents suitable for reading on mobile devices. In this paper, we propose a novel comic page image understanding method based on edge segment analysis. First, we propose an efficient edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input comic page image; second, we propose a top-down scheme to detect line segments within each obtained edge segment; third, we develop a novel method to detect the storyboards by selecting the border lines and further identify the reading order of these storyboards. The proposed method is performed on a data set consisting of 2000 comic page images from ten printed comic series. The experimental results demonstrate that the proposed method achieves satisfactory results on different comics and outperforms the existing methods.

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.

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,

Magnetism of Nanographene-Based Microporous Carbon and Its Applications: Interplay of Edge Geometry and Chemistry Details in the Edge State

Science.gov (United States)

Enoki, Toshiaki; Kiguchi, Manabu

2018-03-01

magnetic moments of nanographenes. For applications, the edge-state spins in nanographene-based microporous carbon can be a good tool as a molecule sensor in detecting molecules having different chemical properties and sizes. The on-off magnetic switching phenomena upon the adsorption of H2O and other OH-containing molecules offers a molecule sensor. A He sensor, in which the edge-state spins is employed as a probe, is also proposed on the basis of a huge condensation of He into ultramicropores.

A novel fair active queue management algorithm based on traffic delay jitter

Science.gov (United States)

Wang, Xue-Shun; Yu, Shao-Hua; Dai, Jin-You; Luo, Ting

2009-11-01

In order to guarantee the quantity of data traffic delivered in the network, congestion control strategy is adopted. According to the study of many active queue management (AQM) algorithms, this paper proposes a novel active queue management algorithm named JFED. JFED can stabilize queue length at a desirable level by adjusting output traffic rate and adopting a reasonable calculation of packet drop probability based on buffer queue length and traffic jitter; and it support burst packet traffic through the packet delay jitter, so that it can traffic flow medium data. JFED impose effective punishment upon non-responsible flow with a full stateless method. To verify the performance of JFED, it is implemented in NS2 and is compared with RED and CHOKe with respect to different performance metrics. Simulation results show that the proposed JFED algorithm outperforms RED and CHOKe in stabilizing instantaneous queue length and in fairness. It is also shown that JFED enables the link capacity to be fully utilized by stabilizing the queue length at a desirable level, while not incurring excessive packet loss ratio.

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

A novel solution for car traffic control based on radiometric microwave devices

Science.gov (United States)

Soldovieri, Francesco; Denisov, Alexander; Speziale, Victor

2014-05-01

The significant problem of traffic in big cities, connected with huge and building up quantity of automobile cars, demands for novel strategies, based on nonconventional solutions, in order to improve system traffic control, especially at crossroads. As well known, the usual solution is based on the time relay, which requires the installation of a fixed traffic interval (signal light switching) at a crossroad; this solution is low cost, but does not account for the actual traffic conditions. Therefore, in the recent years, attention is towards to new designs, where the monitoring of the and control of traffic is carried out by using various methods including, optical, the infrared, magnetic, radar tracking, acoustical ones. In this work, we discuss the deployment of high sensitivity radiometric systems and radiometers(sensor) in the microwave range [1, 2]. In fact, the radiometer as "sensor" can provide an always updated information about the car traffic in any weather condition and in absence or low visibility conditions. In fact, the radiometric sensor detects the cars thanks to the different behavior of the car roofs which reflect the cold sky whereas the road asphalt is visible as warm object (at around outside temperature). [1] A. G. Denisov, V. P. Gorishnyak, S. E. Kuzmin et al., "Some experiments concerning resolution of 32 sensors passive 8mm wave imaging system," in Proceedings of the International Symposium on Space Terahertz Technology (ISSTT '09), Charlottesville, Va, USA, April 2009. [2] F. Soldovieri, A. Natale, V. Gorishnyak, A. Pavluchenko, A. Denisov, and L. Chen, "Radiometric Imaging for Monitoring and Surveillance Issues," International Journal of Antennas and Propagation, vol. 2013, Article ID 272561, 8 pages, 2013. doi:10.1155/2013/272561.

Study on Detection and Localization Algorithm of Traffic Signs from Natural Scenes

Directory of Open Access Journals (Sweden)

Xian-Zhong Han

2014-08-01

Full Text Available Automatic detection and location of traffic signs is an important part of intelligent transportation, especially for unmanned vehicle technology research. For the morphological feature of China road traffic signs, we propose a traffic sign detection method based on color segmentation and shape analysis. Firstly, in order to solve the problems of traffic signs color cast, distortion, and cross-color in natural scenes, the images are processed by white balance, Retinex color enhancement, and affine transformation. Then, the type of traffic signs is discriminated and detected, according to the color and shape characteristics of traffic signs. The experimental results show that this method can effectively detect and recognize traffic signs.

Determination of traffic intensity from camera images using image processing and pattern recognition techniques

Science.gov (United States)

Mehrübeoğlu, Mehrübe; McLauchlan, Lifford

2006-02-01

The goal of this project was to detect the intensity of traffic on a road at different times of the day during daytime. Although the work presented utilized images from a section of a highway, the results of this project are intended for making decisions on the type of intervention necessary on any given road at different times for traffic control, such as installation of traffic signals, duration of red, green and yellow lights at intersections, and assignment of traffic control officers near school zones or other relevant locations. In this project, directional patterns are used to detect and count the number of cars in traffic images over a fixed area of the road to determine local traffic intensity. Directional patterns are chosen because they are simple and common to almost all moving vehicles. Perspective vision effects specific to each camera orientation has to be considered, as they affect the size and direction of patterns to be recognized. In this work, a simple and fast algorithm has been developed based on horizontal directional pattern matching and perspective vision adjustment. The results of the algorithm under various conditions are presented and compared in this paper. Using the developed algorithm, the traffic intensity can accurately be determined on clear days with average sized cars. The accuracy is reduced on rainy days when the camera lens contains raindrops, when there are very long vehicles, such as trucks or tankers, in the view, and when there is very low light around dusk or dawn.

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.

From crisis to development--analysis of air traffic control work processes.

Science.gov (United States)

Teperi, Anna-Maria; Leppänen, Anneli

2011-03-01

In this study an intervention to improve work processes in air traffic control (ATC) is evaluated. The background was the Finnish air traffic controllers' strike of 1999. The old ways of thinking and acting did not support development of ATC prompting a need for a new kind of working culture in the organisation. Several actions were started. In one of these, ATC work processes were modelled by personnel and development plans concerning work were delivered to top management. Different actors (management, trade union, stakeholders) were interviewed before (n=16) and after the project (n=7). The intervention supported systematic co-operation between different actors in the organisation. However, a follow-up revealed that only a few participants had adopted the idea of continuous work development. Mastery of human factors is crucial in a high reliability work environment such as ATC. But how is the analytical and co-operative aspect kept alive in an organisation that is run by strict international regulation and has a strong technical competence, but is not that strong in collaborative and human aspects? Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Analysis of factors temporarily impacting traffic sign readability

Directory of Open Access Journals (Sweden)

Majid Khalilikhah

2016-10-01

Full Text Available Traffic sign readability can be affected by the existence of dirt on traffic sign faces. However, among damaged signs, dirty traffic signs are unique since their damage is not permanent and they just can be cleaned instead of replaced. This study aimed to identify the most important factors contributing to traffic sign dirt. To do so, a large number of traffic signs in Utah were measured by deploying a vehicle instrumented with mobile LiDAR imaging and digital photolog technologies. Each individual daytime digital image was inspected for dirt. Location and climate observations obtained from official sources were compiled using ArcGIS throughout the process. To identify contributing factors to traffic sign dirt, the chi-square test was employed. To analyze the data and rank all of the factors based on their importance to the sign dirt, Random forests statistical model was utilized. After analyzing the data, it can be concluded that ground elevation, sign mount height, and air pollution had the highest effect on making traffic signs dirty. The findings of this investigation assist transportation agencies in determining traffic signs with a higher likelihood of sign dirt. In this way, agencies would schedule to clean such traffic signs more frequently.

Electrically tunable robust edge states in graphene-based topological photonic crystal slabs

Science.gov (United States)

Song, Zidong; Liu, HongJun; Huang, Nan; Wang, ZhaoLu

2018-03-01

Topological photonic crystals are optical structures supporting topologically protected unidirectional edge states that exhibit robustness against defects. Here, we propose a graphene-based all-dielectric photonic crystal slab structure that supports two-dimensionally confined topological edge states. These topological edge states can be confined in the out-of-plane direction by two parallel graphene sheets. In the structure, the excitation frequency range of topological edge states can be dynamically and continuously tuned by varying bias voltage across the two parallel graphene sheets. Utilizing this kind of architecture, we construct Z-shaped channels to realize topological edge transmission with diffrerent frequencies. The proposal provides a new degree of freedom to dynamically control topological edge states and potential applications for robust integrated photonic devices and optical communication systems.

Online Traffic Condition Evaluation Method for Connected Vehicles Based on Multisource Data Fusion

Directory of Open Access Journals (Sweden)

Pang-wei Wang

2017-01-01

Full Text Available With the development of connected vehicle (CV and Vehicle to X (V2X communication, more traffic data is being collected from the road network. In order to predict future traffic condition from connected vehicles’ data in real-time, we present an online traffic condition evaluation model utilizing V2X communication. This model employs the Analytic Hierarchy Process (AHP and the multilevel fuzzy set theory to fuse multiple sources of information for prediction. First, the contemporary vehicle data from the On Board Diagnostic (OBD is fused with the static road data in the Road Side Unit (RSU. Then, the real-time traffic evaluation scores are calculated using the variable membership model. The real data collected by OBU in field test demonstrates the feasibility of the evaluation model. Compared with traditional evaluation systems, the proposed model can handle more types of data but demands less data transfer.

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...

Fast Image Edge Detection based on Faber Schauder Wavelet and Otsu Threshold

Directory of Open Access Journals (Sweden)

Assma Azeroual

2017-12-01

Full Text Available Edge detection is a critical stage in many computer vision systems, such as image segmentation and object detection. As it is difficult to detect image edges with precision and with low complexity, it is appropriate to find new methods for edge detection. In this paper, we take advantage of Faber Schauder Wavelet (FSW and Otsu threshold to detect edges in a multi-scale way with low complexity, since the extrema coefficients of this wavelet are located on edge points and contain only arithmetic operations. First, the image is smoothed using bilateral filter depending on noise estimation. Second, the FSW extrema coefficients are selected based on Otsu threshold. Finally, the edge points are linked using a predictive edge linking algorithm to get the image edges. The effectiveness of the proposed method is supported by the experimental results which prove that our method is faster than many competing state-of-the-art approaches and can be used in real-time applications.

Next generation network based carrier ethernet test bed for IPTV traffic

DEFF Research Database (Denmark)

Fu, Rong; Berger, Michael Stübert; Zheng, Yu

2009-01-01

This paper presents a Carrier Ethernet (CE) test bed based on the Next Generation Network (NGN) framework. After the concept of CE carried out by Metro Ethernet Forum (MEF), the carrier-grade Ethernet are obtaining more and more interests and being investigated as the low cost and high performanc...... services of transport network to carry the IPTV traffic. This test bed is approaching to support the research on providing a high performance carrier-grade Ethernet transport network for IPTV traffic....

Piloted simulation of an air-ground profile negotiation process in a time-based Air Traffic Control environment

Science.gov (United States)

Williams, David H.; Green, Steven M.

1993-01-01

Historically, development of airborne flight management systems (FMS) and ground-based air traffic control (ATC) systems has tended to focus on different objectives with little consideration for operational integration. A joint program, between NASA's Ames Research Center (Ames) and Langley Research Center (Langley), is underway to investigate the issues of, and develop systems for, the integration of ATC and airborne automation systems. A simulation study was conducted to evaluate a profile negotiation process (PNP) between the Center/TRACON Automation System (CTAS) and an aircraft equipped with a four-dimensional flight management system (4D FMS). Prototype procedures were developed to support the functional implementation of this process. The PNP was designed to provide an arrival trajectory solution which satisfies the separation requirements of ATC while remaining as close as possible to the aircraft's preferred trajectory. Results from the experiment indicate the potential for successful incorporation of aircraft-preferred arrival trajectories in the CTAS automation environment. Fuel savings on the order of 2 percent to 8 percent, compared to fuel required for the baseline CTAS arrival speed strategy, were achieved in the test scenarios. The data link procedures and clearances developed for this experiment, while providing the necessary functionality, were found to be operationally unacceptable to the pilots. In particular, additional pilot control and understanding of the proposed aircraft-preferred trajectory, and a simplified clearance procedure were cited as necessary for operational implementation of the concept.

Proportional fair scheduling algorithm based on traffic in satellite communication system

Science.gov (United States)

Pan, Cheng-Sheng; Sui, Shi-Long; Liu, Chun-ling; Shi, Yu-Xin

2018-02-01

In the satellite communication network system, in order to solve the problem of low system capacity and user fairness in multi-user access to satellite communication network in the downlink, combined with the characteristics of user data service, an algorithm study on throughput capacity and user fairness scheduling is proposed - Proportional Fairness Algorithm Based on Traffic(B-PF). The algorithm is improved on the basis of the proportional fairness algorithm in the wireless communication system, taking into account the user channel condition and caching traffic information. The user outgoing traffic is considered as the adjustment factor of the scheduling priority and presents the concept of traffic satisfaction. Firstly,the algorithm calculates the priority of the user according to the scheduling algorithm and dispatches the users with the highest priority. Secondly, when a scheduled user is the business satisfied user, the system dispatches the next priority user. The simulation results show that compared with the PF algorithm, B-PF can improve the system throughput, the business satisfaction and fairness.

Intelligent Testing of Traffic Light Programs: Validation in Smart Mobility Scenarios

OpenAIRE

Javier Ferrer; José García-Nieto; Enrique Alba; Francisco Chicano

2016-01-01

In smart cities, the use of intelligent automatic techniques to find efficient cycle programs of traffic lights is becoming an innovative front for traffic flow management. However, this automatic programming of traffic lights requires a validation process of the generated solutions, since they can affect the mobility (and security) of millions of citizens. In this paper, we propose a validation strategy based on genetic algorithms and feature models for the automatic generation of different ...

SOME EMPIRICAL RELATIONS BETWEEN TRAVEL SPEED, TRAFFIC VOLUME AND TRAFFIC COMPOSITION IN URBAN ARTERIALS

Directory of Open Access Journals (Sweden)

Eleni I. VLAHOGIANNI, Ph.D.

2007-01-01

Full Text Available The effects of traffic mix (the percentage of cars, trucks, buses and so on are of particular interest in the speed-volume relationship in urban signalized arterials under various geometric and control characteristics. The paper presents some empirical observations on the relation between travel speed, traffic volume and traffic composition in urban signalized arterials. A methodology based on emerging self-organizing structures of neural networks to identify regions in the speed-volume relationship with respect to traffic composition and Bayesian networks to evaluate the effect of different types of motorized vehicles on prevailing traffic conditions is proposed. Results based on data from a large urban network indicate that the variability in traffic conditions can be described by eight regions in speed-volume relationship with respect to traffic composition. Further evaluation of the effect of motorized vehicles in each region separately indicates that the effect of traffic composition decreases with the onset of congestion. Moreover, taxis and motorcycles are the primary affecting parameter of the form of the speed-volume relationship in urban arterials.

Right-\\0xADturn traffic volume adjustment in traffic signal warrant analysis : final report.

Science.gov (United States)

2016-05-06

This report was based on the research project, Right-Turn Traffic Volume Adjustment in : Traffic Signal Warrants, sponsored by the Nevada Department of Transportation (NDOT) : and SOLARIS. Right-turn traffic does not affect intersection performance i...

Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective

Energy Technology Data Exchange (ETDEWEB)

Wang, Hong [Pacific Northwest National Laboratory (PNNL); Aziz, H M Abdul [ORNL; Young, Stan [National Renewable Energy Laboratory (NREL); Patil, Sagar [Pacific Northwest National Laboratory (PNNL)

2017-10-01

Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections. In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.

Edge effects in vertically-oriented graphene based electric double-layer capacitors

Science.gov (United States)

Yang, Huachao; Yang, Jinyuan; Bo, Zheng; Zhang, Shuo; Yan, Jianhua; Cen, Kefa

2016-08-01

Vertically-oriented graphenes (VGs) have been demonstrated as a promising active material for electric double-layer capacitors (EDLCs), partially due to their edge-enriched structure. In this work, the 'edge effects', i.e., edges as the promoters of high capacitance, in VG based EDLCs are investigated with experimental research and numerical simulations. VGs with diverse heights (i.e., edge-to-basal ratios) and edge densities are prepared with varying the plasma-enabled growth time and employing different plasma sources. Electrochemical measurements show that the edges play a predominant role on the charge storage behavior of VGs. A simulation is further conducted to unveil the roles of the edges on the separation and adsorption of ions within VG channels. The initial charge distribution of a VG plane is obtained with density functional theory (DFT) calculations, which is subsequently applied to a molecular dynamics (MD) simulation system to gain the insights into the microscope EDLC structures. Compared with the basal planes, the edges present higher initial charge density (by 4.2 times), higher ion packing density (by 2.6 times), closer ion packing location (by 0.8 Å), and larger ion separation degree (by 14%). The as-obtained findings will be instructive in designing the morphology and structure of VGs for enhanced capacitive performances.

Calculating Traffic based on Road Sensor Data

NARCIS (Netherlands)

Bisseling, Rob; Gao, Fengnan; Hafkenscheid, Patrick; Idema, Reijer; Jetka, Tomasz; Guerra Ones, Valia; Rata, Debanshu; Sikora, Monika

2014-01-01

Road sensors gather a lot of statistical data about traffic. In this paper, we discuss how a measure for the amount of traffic on the roads can be derived from this data, such that the measure is independent of the number and placement of sensors, and the calculations can be performed quickly for

Enhancement of Edge-based Image Quality Measures Using Entropy for Histogram Equalization-based Contrast Enhancement Techniques

Directory of Open Access Journals (Sweden)

H. T. R. Kurmasha

2017-12-01

Full Text Available An Edge-based image quality measure (IQM technique for the assessment of histogram equalization (HE-based contrast enhancement techniques has been proposed that outperforms the Absolute Mean Brightness Error (AMBE and Entropy which are the most commonly used IQMs to evaluate Histogram Equalization based techniques, and also the two prominent fidelity-based IQMs which are Multi-Scale Structural Similarity (MSSIM and Information Fidelity Criterion-based (IFC measures. The statistical evaluation results show that the Edge-based IQM, which was designed for detecting noise artifacts distortion, has a Person Correlation Coefficient (PCC > 0.86 while the others have poor or fair correlation to human opinion, considering the Human Visual Perception (HVP. Based on HVP, this paper propose an enhancement to classic Edge-based IQM by taking into account the brightness saturation distortion which is the most prominent distortion in HE-based contrast enhancement techniques. It is tested and found to have significantly well correlation (PCC > 0.87, Spearman rank order correlation coefficient (SROCC > 0.92, Root Mean Squared Error (RMSE < 0.1054, and Outlier Ratio (OR = 0%.

A time-based concept for terminal-area traffic management

Science.gov (United States)

Erzberger, Heinz; Tobias, Leonard

1986-01-01

An automated air-traffic-management concept that has the potential for significantly increasing the efficiency of traffic flows in high-density terminal areas is discussed. The concept's implementation depends on techniques for controlling the landing time of all aircraft entering the terminal area, both those that are equipped with on-board four-dimensional (4D) guidance systems as well as those aircraft types that are conventionally equipped. The two major ground-based elements of the system are a scheduler which assigns conflict-free landing times and a profile descent advisor. Landing time provided by the scheduler is uplinked to equipped aircraft and translated into the appropriate 4D trajectory by the-board flight-management system. The controller issues descent advisories to unequipped aircraft to help them achieve the assigned landing times. Air traffic control simulations have established that the concept provides an efficient method for controlling various mixes of 4D-equipped and unequipped, as well as low- and high-performance, aircraft. Piloted simulations of profiles flown with the aid of advisories have verified the ability to meet specified descent times with prescribed accuracy.

Traffic-induced changes and processes in forest road aggregate particle-size distributions

Science.gov (United States)

Hakjun Rhee; James Fridley; Deborah Page-Dumroese

2018-01-01

Traffic can alter forest road aggregate material in various ways, such as by crushing, mixing it with subgrade material, and sweeping large-size, loose particles (gravel) toward the outside of the road. Understanding the changes and physical processes of the aggregate is essential to mitigate sediment production from forest roads and reduce road maintenance efforts. We...

Efficient IP Traffic over Optical Network Based on Wavelength Translation Switching

DEFF Research Database (Denmark)

Jha, Vikas; Kalia, Kartik; Chowdhary, Bhawani Shankar

2016-01-01

With the advent of TCP/IP protocol suite the overall era of communication technologies had been redefined. Now, we can’t ignore the presence of huge amount of IP traffic; data, voice or video increasing day by day creating more pressure on existing communicating media and supporting back bone....... With the humongous popularity of Internet the overall traffic on Internet has the same story. Focusing on transmission of IP traffic in an optical network with signals remaining in their optical nature generated at particular wavelength, proposed is the switching of optically generated IP packets through optical...... cross connects based on translation of wavelength when an IP packet is crossing the optical cross connect. Adding the concepts of layer 3 routing protocols along with the wavelength translation scheme, will help in spanning the overall optical network for a larger area....

Traffic Congestion Detection System through Connected Vehicles and Big Data

Directory of Open Access Journals (Sweden)

Néstor Cárdenas-Benítez

2016-04-01

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

Traffic Congestion Detection System through Connected Vehicles and Big Data.

Science.gov (United States)

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

2016-04-28

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

Automated and observer based light field indicator edge evaluation in diagnostic X-ray equipment

International Nuclear Information System (INIS)

Bottaro, Marcio; Nagy, Balazs Vince; Soares, Fernanda Cristina Salvador; Rosendo, Danilo Cabral

2017-01-01

Introduction: To analyze edge detection and optical contrast calculation of light field-indicators used in X-ray via automated- and observer-based methods, and comparison with current standard approaches, which do not give exact definition for light field edge determination. Methods: Automated light sensor array was used to measure the penumbra zone of the edge in the standard X-ray equipment, while trained and naive human observers were asked to mark the light field edge according to their own determination. Different interpretations of the contrast were then calculated and compared. Results: In contrast to automated measurements of edge definition and detection, measurements by human observers showed large inter-observer variation independent of their training with X-ray equipment. Different contrast calculations considering the different edge definitions gave very different contrast values. Conclusion: As the main conclusion, we propose a more exact edge definition of the X-ray light field, corresponding well to the average human observer's edge determination. The new edge definition method with automated systems would reduce human variability in edge determination. Such errors could potentially affect the approval of X-ray equipment, and also increase the radiation dose. The automated measurement based on human observers’ edge definition and the corresponding contrast calculation may lead to a more precise light field calibration, which enables reduced irradiation doses on radiology patients. (author)

Automated and observer based light field indicator edge evaluation in diagnostic X-ray equipment

Directory of Open Access Journals (Sweden)

Márcio Bottaro

Full Text Available Abstract Introduction To analyze edge detection and optical contrast calculation of light field-indicators used in X-ray via automated- and observer-based methods, and comparison with current standard approaches, which do not give exact definition for light field edge determination. Methods Automated light sensor array was used to measure the penumbra zone of the edge in the standard X-ray equipment, while trained and naïve human observers were asked to mark the light field edge according to their own determination. Different interpretations of the contrast were then calculated and compared. Results In contrast to automated measurements of edge definition and detection, measurements by human observers showed large inter-observer variation independent of their training with X-ray equipment. Different contrast calculations considering the different edge definitions gave very different contrast values. Conclusion As the main conclusion, we propose a more exact edge definition of the X-ray light field, corresponding well to the average human observer’s edge determination. The new edge definition method with automated systems would reduce human variability in edge determination. Such errors could potentially affect the approval of X-ray equipment, and also increase the radiation dose. The automated measurement based on human observers’ edge definition and the corresponding contrast calculation may lead to a more precise light field calibration, which enables reduced irradiation doses on radiology patients.

Automated and observer based light field indicator edge evaluation in diagnostic X-ray equipment

Energy Technology Data Exchange (ETDEWEB)

Bottaro, Marcio; Nagy, Balazs Vince; Soares, Fernanda Cristina Salvador; Rosendo, Danilo Cabral, E-mail: marcio@iee.usp.br [Universidade de Sao Paulo (USP), SP (Brazil); Optics and Engineering Informatics, Budapest University of Technology and Economics, Budapest (Hungary)

2017-04-15

Introduction: To analyze edge detection and optical contrast calculation of light field-indicators used in X-ray via automated- and observer-based methods, and comparison with current standard approaches, which do not give exact definition for light field edge determination. Methods: Automated light sensor array was used to measure the penumbra zone of the edge in the standard X-ray equipment, while trained and naive human observers were asked to mark the light field edge according to their own determination. Different interpretations of the contrast were then calculated and compared. Results: In contrast to automated measurements of edge definition and detection, measurements by human observers showed large inter-observer variation independent of their training with X-ray equipment. Different contrast calculations considering the different edge definitions gave very different contrast values. Conclusion: As the main conclusion, we propose a more exact edge definition of the X-ray light field, corresponding well to the average human observer's edge determination. The new edge definition method with automated systems would reduce human variability in edge determination. Such errors could potentially affect the approval of X-ray equipment, and also increase the radiation dose. The automated measurement based on human observers’ edge definition and the corresponding contrast calculation may lead to a more precise light field calibration, which enables reduced irradiation doses on radiology patients. (author)

Real-time network traffic classification technique for wireless local area networks based on compressed sensing

Science.gov (United States)

Balouchestani, Mohammadreza

2017-05-01

Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

Improved Optical Flow Algorithm for a Intelligent Traffic Tracking System

Directory of Open Access Journals (Sweden)

Xia Yupeng

2013-05-01

Full Text Available It is known that to get the contours and segmentations of moving cars is the essential step of image processing in intelligent traffic tracking systems. As an effective way, the optical flow algorithm is widely used for this kind of applications. But in traditional gradient-based approaches, in order to make the data responding to the edges of moving objects expand to the area, which gray level is flat, it needs to keep the iteration times large enough. It takes a large amount of calculation time, and the accuracy of the result is not as good as expected. In order to improve the numerical reliability of image gradient data, Hessian matrix distinguishing, Gaussian filtering standard deviation amending, mean model amending and multi-image comparing, the four algorithms were investigated by applying them to track moving objects. From the experimental results, it is shown that both the calculation convergence speed and accuracy of our methods have greatly improved comparing with traditional algorithms, the feasibility and validity of those methods were confirmed.

Capacity improvement of the carbon-based electrochemical capacitor by zigzag-edge introduced graphene

Science.gov (United States)

Tamura, Naoki; Tomai, Takaaki; Oka, Nobuto; Honma, Itaru

2018-01-01

The electrochemical properties of graphene edge has been attracted much attention. Especially, zigzag edge has high electrochemical activity because neutral radical exits on edge. However, due to a lack of efficient production method for zigzag graphene, the electrochemical properties of zigzag edge have not been experimentally demonstrated and the capacitance enhancement of carbonaceous materials in energy storage devices by the control in their edge states is still challenge. In this study, we fabricated zigzag-edge-rich graphene by a one-step method combining graphene exfoliation in supercritical fluid and anisotropic etching by catalytic nanoparticles. This efficient production of zigzag-edge-rich graphene allows us to investigate the electrochemical activity of zigzag edge. By cyclic voltammetry, we revealed the zigzag edge-introduced graphene exhibited unique redox reaction in aqueous acid solution. Moreover, by the calculation on the density function theory (DFT), this unique redox potential for zigzag edge-introduced graphene can be attributed to the proton-insertion/-extraction reactions at the zigzag edge. This finding indicates that the graphene edge modification can contribute to the further increase in the capacitance of the carbon-based electrochemical capacitor.

A sensemaking perspective on framing the mental picture of air traffic controllers.

Science.gov (United States)

Malakis, Stathis; Kontogiannis, Tom

2013-03-01

It has long been recognized that controller strategies are based on a 'mental picture' or representation of traffic situations. Earlier studies indicated that controllers tend to maintain a selective representation of traffic flows based on a few salient traffic features that point out to interesting events (e.g., potential conflicts). A field study is presented in this paper that examines salient features or 'knowledge variables' that constitute the building blocks of controller mental pictures. Verbal reports from participants, a field experiment and observations of real-life scenarios provided insights into the cognitive processes that shape and reframe the mental pictures of controllers. Several cognitive processes (i.e., problem detection, elaboration, reframing and replanning) have been explored within a particular framework of sensemaking stemming from the data/frame theory (Klein et al., 2007). Cognitive maps, representing standard and non-standard air traffic flows, emerged as an explanatory framework for making sense of traffic patterns and for reframing mental pictures. The data/frame theory proved to be a useful theoretical tool for investigating complex cognitive phenomena. The findings of the study have implications for the design of training curricula and decision support systems in air traffic control systems. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Influence of near-edge processes in the elemental analysis using X

Indian Academy of Sciences (India)

The near-edge processes, such as X-ray absorption fine structure (XAFS) andresonant ... away from the shell/subshell ionization thresholds of the attenuator element. ... The influence of XAFS to the attenuation coefficient depends upon the ...

Edge printability: techniques used to evaluate and improve extreme wafer edge printability

Science.gov (United States)

Roberts, Bill; Demmert, Cort; Jekauc, Igor; Tiffany, Jason P.

2004-05-01

The economics of semiconductor manufacturing have forced process engineers to develop techniques to increase wafer yield. Improvements in process controls and uniformities in all areas of the fab have reduced film thickness variations at the very edge of the wafer surface. This improved uniformity has provided the opportunity to consider decreasing edge exclusions, and now the outermost extents of the wafer must be considered in the yield model and expectations. These changes have increased the requirements on lithography to improve wafer edge printability in areas that previously were not even coated. This has taxed all software and hardware components used in defining the optical focal plane at the wafer edge. We have explored techniques to determine the capabilities of extreme wafer edge printability and the components of the systems that influence this printability. We will present current capabilities and new detection techniques and the influence that the individual hardware and software components have on edge printability. We will show effects of focus sensor designs, wafer layout, utilization of dummy edge fields, the use of non-zero overlay targets and chemical/optical edge bead optimization.

Two-Dimensional Edge Detection by Guided Mode Resonant Metasurface

Science.gov (United States)

Saba, Amirhossein; Tavakol, Mohammad Reza; Karimi-Khoozani, Parisa; Khavasi, Amin

2018-05-01

In this letter, a new approach to perform edge detection is presented using an all-dielectric CMOS-compatible metasurface. The design is based on guided-mode resonance which provides a high quality factor resonance to make the edge detection experimentally realizable. The proposed structure that is easy to fabricate, can be exploited for detection of edges in two dimensions due to its symmetry. Also, the trade-off between gain and resolution of edge detection is discussed which can be adjusted by appropriate design parameters. The proposed edge detector has also the potential to be used in ultrafast analog computing and image processing.

Dementia and Traffic Accidents: A Danish Register-Based Cohort Study.

Science.gov (United States)

Petersen, Jindong Ding; Siersma, Volkert; Nielsen, Connie Thurøe; Vass, Mikkel; Waldorff, Frans Boch

2016-09-27

As a consequence of a rapid growth of an ageing population, more people with dementia are expected on the roads. Little is known about whether these people are at increased risk of road traffic-related accidents. Our study aims to investigate the risk of road traffic-related accidents for people aged 65 years or older with a diagnosis of dementia in Denmark. We will conduct a nationwide population-based cohort study consisting of Danish people aged 65 or older living in Denmark as of January 1, 2008. The cohort is followed for 7 years (2008-2014). Individual's personal data are available in Danish registers and can be linked using a unique personal identification number. A person is identified with dementia if the person meets at least one of the following criteria: (1) a diagnosis of the disease in the Danish National Patient Register or in the Danish Psychiatric Central Research Register, and/or (2) at least one dementia diagnosis-related drug prescription registration in the Danish National Prescription Registry. Police-, hospital-, and emergency room-reported road traffic-related accidents occurred within the study follow-up are defined as the study outcome. Cox proportional hazard regression models are used for the main analysis. Our study protocol has 3 phases including data collection, data analysis, and reporting. The first phase of register-based data collection of 853,228 individual's personal information was completed in August, 2016. The next phase is data analysis, which is expected to be finished before December 2016, and thereafter writing publications based on the findings. The study started in January 2016 and will end in December 2018. This study covers the entire elderly population of Denmark, and thereby will avoid selection bias due to nonparticipation and loss to follow-up. Furthermore, this ensures that the study results are reliable and generalizable. However, underreporting of traffic-related accidents may occur, which will limit estimation

Stereo-based Collision Avoidance System for Urban Traffic

Science.gov (United States)

Moriya, Takashi; Ishikawa, Naoto; Sasaki, Kazuyuki; Nakajima, Masato

2002-11-01

Numerous car accidents occur on urban road. However, researches done so far on driving assistance are subjecting highways whose environment is relatively simple and easy to handle, and new approach for urban settings is required. Our purpose is to extend its support to the following conditions in city traffic: the presence of obstacles such as pedestrians and telephone poles; the lane mark is not always drawn on a road; drivers may lack the sense of awareness of the lane mark. We propose a collision avoidance system, which can be applied to both highways and urban traffic environment. In our system, stereo cameras are set in front of a vehicle and the captured images are processed through a computer. We create a Projected Disparity Map (PDM) from stereo image pair, which is a disparity histogram taken along ordinate direction of obtained disparity image. When there is an obstacle in front, we can detect it by finding a peak appeared in the PDM. With a speed meter and a steering sensor, the stop distance and the radius of curvature of the self-vehicle are calculated, in order to set the observation-required area, which does not depend on lane marks, within a PDM. A danger level will be computed from the distance and the relative speed to the closest approaching object detected within the observation-required area. The method has been tested in urban traffic scenes and has shown to be effective for judging dangerous situation, and gives proper alarm to a driver.

A population-based, incidence cohort study of mid-back pain after traffic collisions

DEFF Research Database (Denmark)

Johansson, M S; Boyle, E; Hartvigsen, Jan

2015-01-01

BACKGROUND: Traffic collisions often result in a wide range of symptoms included in the umbrella term whiplash-associated disorders. Mid-back pain (MBP) is one of these symptoms. The incidence and prognosis of different traffic injuries and their related conditions (e.g. neck pain, low back pain...... data from a population-based inception cohort of all traffic injuries occurring in Saskatchewan, Canada, during a 2-year period were used. Annual overall and age-sex-specific incidence rates were calculated, the course of recovery was described using the Kaplan-Meier technique, and associations between...... recovery was 101 days (95% CI: 99-104) and about 23% were still not recovered after 1 year. Participant's expectation for recovery, general health, extent of severely affecting comorbidities and having experienced a previous traffic injury were some of the prognostic factors identified. CONCLUSIONS...

Traffic Command Gesture Recognition for Virtual Urban Scenes Based on a Spatiotemporal Convolution Neural Network

Directory of Open Access Journals (Sweden)

Chunyong Ma

2018-01-01

Full Text Available Intelligent recognition of traffic police command gestures increases authenticity and interactivity in virtual urban scenes. To actualize real-time traffic gesture recognition, a novel spatiotemporal convolution neural network (ST-CNN model is presented. We utilized Kinect 2.0 to construct a traffic police command gesture skeleton (TPCGS dataset collected from 10 volunteers. Subsequently, convolution operations on the locational change of each skeletal point were performed to extract temporal features, analyze the relative positions of skeletal points, and extract spatial features. After temporal and spatial features based on the three-dimensional positional information of traffic police skeleton points were extracted, the ST-CNN model classified positional information into eight types of Chinese traffic police gestures. The test accuracy of the ST-CNN model was 96.67%. In addition, a virtual urban traffic scene in which real-time command tests were carried out was set up, and a real-time test accuracy rate of 93.0% was achieved. The proposed ST-CNN model ensured a high level of accuracy and robustness. The ST-CNN model recognized traffic command gestures, and such recognition was found to control vehicles in virtual traffic environments, which enriches the interactive mode of the virtual city scene. Traffic command gesture recognition contributes to smart city construction.

Epidemic spreading in weighted networks: an edge-based mean-field solution.

Science.gov (United States)

Yang, Zimo; Zhou, Tao

2012-05-01

Weight distribution greatly impacts the epidemic spreading taking place on top of networks. This paper presents a study of a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could be applied to characterize the nonequilibrium steady states of dynamical processes on weighted networks.

Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

KAUST Repository

Canepa, Edward S.

2013-01-01

Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham- Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some decision variable. We use this fact to pose the problem of detecting spoofing cyber-attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offline. A numerical implementation is performed on a cyber-attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © 2013 IEEE.

Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

KAUST Repository

Canepa, Edward S.

2013-09-01

Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill- Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data generated by multiple sensors of different types, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for a specific decision variable. We use this fact to pose the problem of detecting spoofing cyber attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offliine. A numerical implementation is performed on a cyber attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © American Institute of Mathematical Sciences.

GIS based analysis of Intercity Fatal Road Traffic Accidents in Iran.

Science.gov (United States)

Alizadeh, A; Zare, M; Darparesh, M; Mohseni, S; Soleimani-Ahmadi, M

2015-01-01

Road traffic accidents including intercity car traffic accidents (ICTAs) are among the most important causes of morbidity and mortality due to the growing number of vehicles, risky behaviors, and changes in lifestyle of the general population. A sound knowledge of the geographical distribution of car traffic accidents can be considered as an approach towards the accident causation and it can be used as an administrative tool in allocating the sources for traffic accidents prevention. This study was conducted to investigate the geographical distribution and the time trend of fatal intercity car traffic accidents in Iran. To conduct this descriptive study, all Iranian intercity road traffic mortality data were obtained from the Police reports in the Statistical Yearbook of the Governor's Budget and Planning. The obtained data were for 17 complete Iranian calendar years from March 1997 to March 2012. The incidence rate (IR) of fatal ICTAs for each year was calculated as the total number of fatal ICTAs in every 100000 population in specified time intervals. Figures and maps indicating the trends and geographical distribution of fatal ICTAs were prepared while using Microsoft Excel and ArcGis9.2 software. The number of fatal car accidents showed a general increasing trend from 3000 in 1996 to 13500 in 2012. The incidence of fatal intercity car accidents has changed from six in 100000 population in 1996 to 18 in 100000 population in 2012. GIS based data showed that the incidence rate of ICTAs in different provinces of Iran was very divergent. The highest incidence of fatal ICTAs was in Semnan province (IR= 35.2), followed by North Khorasan (IR=22.7), and South Khorasan (IR=22). The least incidence of fatal ICTAs was in Tehran province (IR=2.4) followed by Khozestan (IR=6.5), and Eastern Azarbayejan (IR=6.6). The compensation cost of fatal ICTAs also showed an increasing trend during the studied period. Since an increasing amount of money was being paid yearly for the car

GIS based analysis of Intercity Fatal Road Traffic Accidents in Iran

Science.gov (United States)

Alizadeh, A; Zare, M; Darparesh, M; Mohseni, S; Soleimani-Ahmadi, M

2015-01-01

Road traffic accidents including intercity car traffic accidents (ICTAs) are among the most important causes of morbidity and mortality due to the growing number of vehicles, risky behaviors, and changes in lifestyle of the general population. A sound knowledge of the geographical distribution of car traffic accidents can be considered as an approach towards the accident causation and it can be used as an administrative tool in allocating the sources for traffic accidents prevention. This study was conducted to investigate the geographical distribution and the time trend of fatal intercity car traffic accidents in Iran. To conduct this descriptive study, all Iranian intercity road traffic mortality data were obtained from the Police reports in the Statistical Yearbook of the Governor’s Budget and Planning. The obtained data were for 17 complete Iranian calendar years from March 1997 to March 2012. The incidence rate (IR) of fatal ICTAs for each year was calculated as the total number of fatal ICTAs in every 100000 population in specified time intervals. Figures and maps indicating the trends and geographical distribution of fatal ICTAs were prepared while using Microsoft Excel and ArcGis9.2 software. The number of fatal car accidents showed a general increasing trend from 3000 in 1996 to 13500 in 2012. The incidence of fatal intercity car accidents has changed from six in 100000 population in 1996 to 18 in 100000 population in 2012. GIS based data showed that the incidence rate of ICTAs in different provinces of Iran was very divergent. The highest incidence of fatal ICTAs was in Semnan province (IR= 35.2), followed by North Khorasan (IR=22.7), and South Khorasan (IR=22). The least incidence of fatal ICTAs was in Tehran province (IR=2.4) followed by Khozestan (IR=6.5), and Eastern Azarbayejan (IR=6.6). The compensation cost of fatal ICTAs also showed an increasing trend during the studied period. Since an increasing amount of money was being paid yearly for the

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.

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

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.

Traffic Light Detection at Night

DEFF Research Database (Denmark)

Jensen, Morten Bornø; Philipsen, Mark Philip; Bahnsen, Chris

2015-01-01

Traffic light recognition (TLR) is an integral part of any in- telligent vehicle, it must function both at day and at night. However, the majority of TLR research is focused on day-time scenarios. In this paper we will focus on detection of traffic lights at night and evalu- ate the performance...... of three detectors based on heuristic models and one learning-based detector. Evaluation is done on night-time data from the public LISA Traffic Light Dataset. The learning-based detector out- performs the model-based detectors in both precision and recall. The learning-based detector achieves an average...

Implementation of supply chain management in supplier performance assessment using Analytical Hierarchy Process (AHP Objective Matrix (OMAX and Traffic Light System

Directory of Open Access Journals (Sweden)

Sukendar Irwan

2018-01-01

Full Text Available This study focuses on researching the implementation of supply chain management in supplier performance measurement using Analytical Hierarchy Process (AHP Objective Matrix (OMAX and Traffic Light System. The method used consisted of several stages: Identification stage of criteria variable and subcriteria variable, designing hierarchy AHP structure, calculating the weight of each criterion and subcriteria, supplier performance appraisal using OMAX method, calculating the total value of each supplier perfomance and identifying the performance of each supplier Using color indicator from Traffic Light System. Based on the results of the research, it can be seen that 9 out of 10 suppliers that are considered have a good performance while 1 supplier has a performance under the target.

Enhancing Community Detection By Affinity-based Edge Weighting Scheme

Energy Technology Data Exchange (ETDEWEB)

Yoo, Andy [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanders, Geoffrey [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Henson, Van [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vassilevski, Panayot [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-10-05

Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is ideal for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.

Traffic

International Nuclear Information System (INIS)

Lichtblau, G.

2001-01-01

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

Reliable Path Selection Problem in Uncertain Traffic Network after Natural Disaster

Directory of Open Access Journals (Sweden)

Jing Wang

2013-01-01

Full Text Available After natural disaster, especially for large-scale disasters and affected areas, vast relief materials are often needed. In the meantime, the traffic networks are always of uncertainty because of the disaster. In this paper, we assume that the edges in the network are either connected or blocked, and the connection probability of each edge is known. In order to ensure the arrival of these supplies at the affected areas, it is important to select a reliable path. A reliable path selection model is formulated, and two algorithms for solving this model are presented. Then, adjustable reliable path selection model is proposed when the edge of the selected reliable path is broken. And the corresponding algorithms are shown to be efficient both theoretically and numerically.

Learning to Grasp Unknown Objects Based on 3D Edge Information

DEFF Research Database (Denmark)

Bodenhagen, Leon; Kraft, Dirk; Popovic, Mila

2010-01-01

In this work we refine an initial grasping behavior based on 3D edge information by learning. Based on a set of autonomously generated evaluated grasps and relations between the semi-global 3D edges, a prediction function is learned that computes a likelihood for the success of a grasp using either...... an offline or an online learning scheme. Both methods are implemented using a hybrid artificial neural network containing standard nodes with a sigmoid activation function and nodes with a radial basis function. We show that a significant performance improvement can be achieved....

Multi-agent fare optimization model of two modes problem and its analysis based on edge of chaos

Science.gov (United States)

Li, Xue-yan; Li, Xue-mei; Li, Xue-wei; Qiu, He-ting

2017-03-01

This paper proposes a new framework of fare optimization & game model for studying the competition between two travel modes (high speed railway and civil aviation) in which passengers' group behavior is taken into consideration. The small-world network is introduced to construct the multi-agent model of passengers' travel mode choice. The cumulative prospect theory is adopted to depict passengers' bounded rationality, the heterogeneity of passengers' reference point is depicted using the idea of group emotion computing. The conceptions of "Langton parameter" and "evolution entropy" in the theory of "edge of chaos" are introduced to create passengers' "decision coefficient" and "evolution entropy of travel mode choice" which are used to quantify passengers' group behavior. The numerical simulation and the analysis of passengers' behavior show that (1) the new model inherits the features of traditional model well and the idea of self-organizing traffic flow evolution fully embodies passengers' bounded rationality, (2) compared with the traditional model (logit model), when passengers are in the "edge of chaos" state, the total profit of the transportation system is higher.

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.

Science.gov (United States)

Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-04-03

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.

Traffic Flow Management Wrap-Up

Science.gov (United States)

Grabbe, Shon

2011-01-01

Traffic Flow Management involves the scheduling and routing of air traffic subject to airport and airspace capacity constraints, and the efficient use of available airspace. Significant challenges in this area include: (1) weather integration and forecasting, (2) accounting for user preferences in the Traffic Flow Management decision making process, and (3) understanding and mitigating the environmental impacts of air traffic on the environment. To address these challenges, researchers in the Traffic Flow Management area are developing modeling, simulation and optimization techniques to route and schedule air traffic flights and flows while accommodating user preferences, accounting for system uncertainties and considering the environmental impacts of aviation. This presentation will highlight some of the major challenges facing researchers in this domain, while also showcasing recent innovations designed to address these challenges.

Improved GIS-based Methods for Traffic Noise Impact Assessment

DEFF Research Database (Denmark)

Nielsen, Otto Anker; Bloch, Karsten Sand

1996-01-01

When vector-based GIS-packages are used for traffic noise impact assessments, the buffer-technique is usually employed for the study: 1. For each road segment buffer-zones representing different noise-intervals are generated, 2. The buffers from all road segments are smoothed together, and 3....... The number of buildings within the buffers are enumerated. This technique provides an inaccurate assessment of the noise diffusion since it does not correct for buildings barrier and reflection to noise. The paper presents the results from a research project where the traditional noise buffer technique...... was compared with a new method which includes these corrections. Both methods follow the Common Nordic Noise Calculation Model, although the traditional buffer technique ignores parts of the model. The basis for the work was a digital map of roads and building polygons, combined with a traffic- and road...

Optimization of Process Parameters of Edge Robotic Deburring with Force Control

Science.gov (United States)

Burghardt, A.; Szybicki, D.; Kurc, K.; Muszyńska, M.

2016-12-01

The issues addressed in the paper present a part of the scientific research conducted within the framework of the automation of the aircraft engine part manufacturing processes. The results of the research presented in the article provided information in which tolerances while using a robotic control station with the option of force control we can make edge deburring.

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

Directory of Open Access Journals (Sweden)

Susel Fernandez

2016-08-01

Full Text Available Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors.

On the impact of trees on dispersion processes of traffic emissions in street canyons

NARCIS (Netherlands)

Gromke, C.B.; Ruck, B.

2009-01-01

Wind-tunnel studies of dispersion processes of traffic exhaust in urban street canyons with tree planting were performed and tracer gas concentrations using electron capture detection (ECD) and flow fields using laser Doppler velocimetry (LDV) were measured. It was found that tree planting reduces

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).

Texas traffic thermostat software tool.

Science.gov (United States)

2013-04-01

The traffic thermostat decision tool is built to help guide the user through a logical, step-wise, process of examining potential changes to their Manage Lane/toll facility. : **NOTE: Project Title: Application of the Traffic Thermostat Framework. Ap...

Texas traffic thermostat marketing package.

Science.gov (United States)

2013-04-01

The traffic thermostat decision tool is built to help guide the user through a logical, step-wise, process of examining potential changes to their Manage Lane/toll facility. : **NOTE: Project Title: Application of the Traffic Thermostat Framework. Ap...

A Methodology In Processing Descriptive Analytics Using MMDA Traffic Update Tweets Tokenization And Classification Tree In Discovering Knowledge

Directory of Open Access Journals (Sweden)

Tristan Jay P. Calaguas

2015-08-01

Full Text Available Traffic on National Capital Region of the Philippines is going as one of many problems facing by the local government and Filipino citizen who are residing in Metro Manila. In addition a Filipino citizen that is working in Metro Manila is experiencing a waste of Twenty Eight Thousand hours in traffic which results unproductivity. Due to traffic that causes long commutes it take away an individual from exercise activities that results fatigue in their health. In relation with this due to lack of exercise that causing by the traffic each year One Hundred Seventy Thousand Filipinos die from cardiovascular diseases up from Eighty Five Thousand more than Twenty years ago according to 2009 study by the Department of Health DOH. Population increase is one of many causes of traffic in Metro Manila. As population is growing the more car riders and commuters volume will be in the road including delivery trucks Pedi cabs jeeps and provincial buses that signify that there is a high employment rate in the country that causes traffic. However to sustain the public needs MMDA is the government agency that provides public services to Filipino citizens through providing updated public traffic information. For past years MMDA used Telephony lines and Television Broadcasting for traffic information dissemination which is very costly in maintenance that made them to adopt Twitter to post Traffic updates and advisories to the public .Since this government agency uses Twitter in disseminating information through posting tweet there is a need for a methodology on how these tweets will analyze so that citizens will have an insight in decision making to avoid specific time of traffic in metro manila. From this condition the researcher will adopt the use of MMDA tweets as the primary data source and apply the CRISP as the knowledge discovery standard processes that to be used in building methodology for descriptive analytics. In this experimental research several

Rotating-Disk-Based Hybridized Electromagnetic-Triboelectric Nanogenerator for Sustainably Powering Wireless Traffic Volume Sensors.

Science.gov (United States)

Zhang, Binbin; Chen, Jun; Jin, Long; Deng, Weili; Zhang, Lei; Zhang, Haitao; Zhu, Minhao; Yang, Weiqing; Wang, Zhong Lin

2016-06-28

Wireless traffic volume detectors play a critical role for measuring the traffic-flow in a real-time for current Intelligent Traffic System. However, as a battery-operated electronic device, regularly replacing battery remains a great challenge, especially in the remote area and wide distribution. Here, we report a self-powered active wireless traffic volume sensor by using a rotating-disk-based hybridized nanogenerator of triboelectric nanogenerator and electromagnetic generator as the sustainable power source. Operated at a rotating rate of 1000 rpm, the device delivered an output power of 17.5 mW, corresponding to a volume power density of 55.7 W/m(3) (Pd = P/V, see Supporting Information for detailed calculation) at a loading resistance of 700 Ω. The hybridized nanogenerator was demonstrated to effectively harvest energy from wind generated by a moving vehicle through the tunnel. And the delivered power is capable of triggering a counter via a wireless transmitter for real-time monitoring the traffic volume in the tunnel. This study further expands the applications of triboelectric nanogenerators for high-performance ambient mechanical energy harvesting and as sustainable power sources for driving wireless traffic volume sensors.

Haptic Edge Detection Through Shear

Science.gov (United States)

Platkiewicz, Jonathan; Lipson, Hod; Hayward, Vincent

2016-03-01

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals.

design and implementation of a density-based traffic light control

African Journals Online (AJOL)

HOD

sensors, a new traffic light control system was developed to ease the flow of traffic at a particular ... of traffic on each lane at the intersection triggered when a vehicle comes between the ... change the sequence back to the normal sequence.

Traffic safety program for school children through safe action and safe condition

Science.gov (United States)

Yulianto, Budi; Setiono, Mahmudah, Amirotul Musthofiah Hidayah; Santoso, Anjar Budi

2017-06-01

The facts indicate that the rights of pedestrians is on the wane. Many motorists are unwilling to provide a space for pedestrians, even when they want to cross the road at zebra-cross facility. The data of traffic accident in Surakarta City showed that 7.0% of accident victims in 2014 to 2015 were children aged 5-15 or the group of school-aged children. In general, the location of schools is on the edge of the road where a lot of vehicles run at high speed. Hence, it is very dangerous for the school children to cross the road. Pertaining to this issue, the Department of Transportation implements a program named School Safety Zone (ZoSS). ZoSS is a time-dependent speed control zone consisting of road markings, traffic signs, optional traffic signals, and rumble strips. The objective of this study was to evaluate the effectiveness of the ZoSS based on the perception of the users, including the students, teachers, parents, and community. This study was conducted through a series of activities including the distribution of questionnaire to obtain the road users' perceptions. The results showed that most of the respondents understood the meaning, aim, and benefit of ZoSS. However, it also found that traffic sign and method of cross the road (Four-T) was not recognized appropriately by the respondents. ZoSS program was generally ineffective since the pedestrians felt unsafe to cross the road due to the high-speed vehicles.

Delays at signalised intersections with exhaustive traffic control

NARCIS (Netherlands)

Boon, M.A.A.; Adan, I.J.B.F.; Winands, E.M.M.; Down, D.G.

2010-01-01

In this paper we study a traffic intersection with vehicle-actuated traffic signal control. Traffic lights stay green until all lanes within a group are emptied. Assuming general renewal arrival processes, we derive exact limiting distributions of the delays under Heavy Traffic (HT) conditions,

Delays at signalized intersections with exhaustive traffic control

NARCIS (Netherlands)

Boon, M.A.A.; Adan, I.J.B.F.; Winands, E.M.M.; Down, D.G.

2012-01-01

In this paper, we study a traffic intersection with vehicle-actuated traffic signal control. Traffic lights stay green until all lanes within a group are emptied. Assuming general renewal arrival processes, we derive exact limiting distributions of the delays under heavy traffic (HT) conditions.

Delays at signalised intersections with exhaustive traffic control

NARCIS (Netherlands)

Boon, M.A.A.; Adan, I.J.B.F.; Winands, E.M.M.; Down, D.G.

2012-01-01

In this paper, we study a traffic intersection with vehicle-actuated traffic signal control. Traffic lights stay green until all lanes within a group are emptied. Assuming general renewal arrival processes, we derive exact limiting distributions of the delays under heavy traffic (HT) conditions.

Edge detection methods based on generalized type-2 fuzzy logic

CERN Document Server

Gonzalez, Claudia I; Castro, Juan R; Castillo, Oscar

2017-01-01

In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the me-thodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detec-tion method where, a digital image is converted a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, inter-val type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphologi-cal gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preproc...

Utilization of the Tango beta-arrestin recruitment technology for cell-based EDG receptor assay development and interrogation.

Science.gov (United States)

Wetter, Justin A; Revankar, Chetana; Hanson, Bonnie J

2009-10-01

Cellular assay development for the endothelial differentiation gene (EDG) family of G-protein-coupled receptors (GPCRs) and related lysophospholipid (LP) receptors is complicated by endogenous receptor expression and divergent receptor signaling. Endogenously expressed LP receptors exist in most tissue culture cell lines. These LP receptors, along with other endogenously expressed GPCRs, contribute to off-target signaling that can complicate interpretation of second-messenger-based cellular assay results. These receptors also activate a diverse and divergent set of cellular signaling pathways, necessitating the use of a variety of assay formats with mismatched procedures and functional readouts. This complicates examination and comparison of these receptors across the entire family. The Tango technology uses the conserved beta-arrestin-dependent receptor deactivation process to allow interrogation of the EDG and related receptors with a single functional assay. This method also isolates the target receptor signal, allowing the use of tissue culture cell lines regardless of their endogenous receptor expression. The authors describe the use of this technique to build cell-based receptor-specific assays for all 8 members of the EDG receptor family as well as the related LPA receptors GPR23, GPR92, and GPR87. In addition, they demonstrate the value of this technology for identification and investigation of functionally selective receptor compounds as demonstrated by the immunosuppressive compound FtY720-P and its action at the EDG(1) and EDG(3) receptors.

Investigation on edge joints of Inconel 625 sheets processed with laser welding

Science.gov (United States)

Caiazzo, F.; Alfieri, V.; Cardaropoli, F.; Sergi, V.

2017-08-01

Laser welding of Inconel 625 edge joint beads in square groove configuration was investigated. The use of different weld geometries in new aerospace solutions explains research on edge joints. A structured plan was carried out in order to characterize the process defining the influence of laser power and welding speed and to study possible interactions among the governing factors. As weld pool protection is crucial in order to obtain sound joints when processing superalloys, a special glove box for gas supply was designed to upgrade the welding head. Welded joints were characterized referring to bead profile, microstructure and X-rays. It was found that heat input plays an important role as it affects welding stability, porosity content and bead shape. Results suggest operating with low values of heat input to reduce porosity and guarantee stable bead conformation. Furthermore, a decrease in the grain size has been observed as a consequence of decreasing heat input.

A novel downlink scheduling strategy for traffic communication system based on TD-LTE technology.

Science.gov (United States)

Chen, Ting; Zhao, Xiangmo; Gao, Tao; Zhang, Licheng

2016-01-01

There are many existing classical scheduling algorithms which can obtain better system throughput and user equality, however, they are not designed for traffic transportation environment, which cannot consider whether the transmission performance of various information flows could meet comprehensive requirements of traffic safety and delay tolerance. This paper proposes a novel downlink scheduling strategy for traffic communication system based on TD-LTE technology, which can perform two classification mappings for various information flows in the eNodeB: firstly, associate every information flow packet with traffic safety importance weight according to its relevance to the traffic safety; secondly, associate every traffic information flow with service type importance weight according to its quality of service (QoS) requirements. Once the connection is established, at every scheduling moment, scheduler would decide the scheduling order of all buffers' head of line packets periodically according to the instant value of scheduling importance weight function, which calculated by the proposed algorithm. From different scenario simulations, it can be verified that the proposed algorithm can provide superior differentiated transmission service and reliable QoS guarantee to information flows with different traffic safety levels and service types, which is more suitable for traffic transportation environment compared with the existing popularity PF algorithm. With the limited wireless resource, information flow closed related to traffic safety will always obtain priority scheduling right timely, which can help the passengers' journey more safe. Moreover, the proposed algorithm cannot only obtain good flow throughput and user fairness which are almost equal to those of the PF algorithm without significant differences, but also provide better realtime transmission guarantee to realtime information flow.

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.

A parallel finite element procedure for contact-impact problems using edge-based smooth triangular element and GPU

Science.gov (United States)

Cai, Yong; Cui, Xiangyang; Li, Guangyao; Liu, Wenyang

2018-04-01

The edge-smooth finite element method (ES-FEM) can improve the computational accuracy of triangular shell elements and the mesh partition efficiency of complex models. In this paper, an approach is developed to perform explicit finite element simulations of contact-impact problems with a graphical processing unit (GPU) using a special edge-smooth triangular shell element based on ES-FEM. Of critical importance for this problem is achieving finer-grained parallelism to enable efficient data loading and to minimize communication between the device and host. Four kinds of parallel strategies are then developed to efficiently solve these ES-FEM based shell element formulas, and various optimization methods are adopted to ensure aligned memory access. Special focus is dedicated to developing an approach for the parallel construction of edge systems. A parallel hierarchy-territory contact-searching algorithm (HITA) and a parallel penalty function calculation method are embedded in this parallel explicit algorithm. Finally, the program flow is well designed, and a GPU-based simulation system is developed, using Nvidia's CUDA. Several numerical examples are presented to illustrate the high quality of the results obtained with the proposed methods. In addition, the GPU-based parallel computation is shown to significantly reduce the computing time.

Calibrated Multi-Temporal Edge Images for City Infrastructure Growth Assessment and Prediction

Science.gov (United States)

Al-Ruzouq, R.; Shanableh, A.; Boharoon, Z.; Khalil, M.

2018-03-01

Urban Growth or urbanization can be defined as the gradual process of city's population growth and infrastructure development. It is typically demonstrated by the expansion of a city's infrastructure, mainly development of its roads and buildings. Uncontrolled urban Growth in cities has been responsible for several problems that include living environment, drinking water, noise and air pollution, waste management, traffic congestion and hydraulic processes. Accurate identification of urban growth is of great importance for urban planning and water/land management. Recent advances in satellite imagery, in terms of improved spatial and temporal resolutions, allows for efficient identification of change patterns and the prediction of built-up areas. In this study, two approaches were adapted to quantify and assess the pattern of urbanization, in Ajman City at UAE, during the last three decades. The first approach relies on image processing techniques and multi-temporal Landsat satellite images with ground resolution varying between 15 to 60 meters. In this approach, the derived edge images (roads and buildings) were used as the basis of change detection. The second approach relies on digitizing features from high-resolution images captured at different years. The latest approach was adopted, as a reference and ground truth, to calibrate extracted edges from Landsat images. It has been found that urbanized area almost increased by 12 folds during the period 1975-2015 where the growth of buildings and roads were almost parallel until 2005 when the roads spatial expansion witnessed a steep increase due to the vertical expansion of the City. Extracted Edges features, were successfully used for change detection and quantification in term of buildings and roads.

Navigators’ Behavior in Traffic Separation Schemes

Directory of Open Access Journals (Sweden)

Zbigniew Pietrzykowski

2015-03-01

Full Text Available One of the areas of decision support in the navigational ship conduct process is a Traffic Separation Scheme. TSSs are established in areas with high traffic density, often near the shore and in port approaches. The main purpose of these schemes is to improve maritime safety by channeling vessel traffic into streams. Traffic regulations as well as ships behavior in real conditions in chosen TSSs have been analyzed in order to develop decision support algorithms.

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

OpenAIRE

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Yang Liu

2017-03-01

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

Spatial-Spectral Approaches to Edge Detection in Hyperspectral Remote Sensing

Science.gov (United States)

Cox, Cary M.

This dissertation advances geoinformation science at the intersection of hyperspectral remote sensing and edge detection methods. A relatively new phenomenology among its remote sensing peers, hyperspectral imagery (HSI) comprises only about 7% of all remote sensing research - there are five times as many radar-focused peer reviewed journal articles than hyperspectral-focused peer reviewed journal articles. Similarly, edge detection studies comprise only about 8% of image processing research, most of which is dedicated to image processing techniques most closely associated with end results, such as image classification and feature extraction. Given the centrality of edge detection to mapping, that most important of geographic functions, improving the collective understanding of hyperspectral imagery edge detection methods constitutes a research objective aligned to the heart of geoinformation sciences. Consequently, this dissertation endeavors to narrow the HSI edge detection research gap by advancing three HSI edge detection methods designed to leverage HSI's unique chemical identification capabilities in pursuit of generating accurate, high-quality edge planes. The Di Zenzo-based gradient edge detection algorithm, an innovative version of the Resmini HySPADE edge detection algorithm and a level set-based edge detection algorithm are tested against 15 traditional and non-traditional HSI datasets spanning a range of HSI data configurations, spectral resolutions, spatial resolutions, bandpasses and applications. This study empirically measures algorithm performance against Dr. John Canny's six criteria for a good edge operator: false positives, false negatives, localization, single-point response, robustness to noise and unbroken edges. The end state is a suite of spatial-spectral edge detection algorithms that produce satisfactory edge results against a range of hyperspectral data types applicable to a diverse set of earth remote sensing applications. This work

Analysis of learning curves in the on-the-job training of air traffic controllers

NARCIS (Netherlands)

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

2011-01-01

This chapter describes a competence-based assessment system, called CBAS, for air traffic control (ATC) simulator and on-the-job training (OJT), developed at Air Traffic Control The Netherlands (LVNL). In contrast with simulator training, learning processes in OJT are difficult to assess, because

Intelligent vehicle based traffic monitoring – exploring application in South Africa

CSIR Research Space (South Africa)

Labuschagne, FJJ

2010-08-01

Full Text Available The paper details the anticipated benefits of an intelligent vehicle based traffic monitoring approach holds. The approach utilises advanced technology with the potential to reduce crashes and includes the monitor of vehicle speeds and flows...

The visibility of IQHE at sharp edges: experimental proposals based on interactions and edge electrostatics

International Nuclear Information System (INIS)

Erkarslan, U; Oylumluoglu, G; Grayson, M; Siddiki, A

2012-01-01

The influence of the incompressible strips on the integer quantized Hall effect (IQHE) is investigated, considering a cleaved-edge overgrown (CEO) sample as an experimentally realizable sharp edge system. We propose a set of experiments to clarify the distinction between the large-sample limit when bulk disorder defines the IQHE plateau width and the small-sample limit smaller than the disorder correlation length, when self-consistent edge electrostatics define the IQHE plateau width. The large-sample or bulk quantized Hall (QH) regime is described by the usual localization picture, whereas the small-sample or edge regime is discussed within the compressible/incompressible strips picture, known as the screening theory of QH edges. Utilizing the unusually sharp edge profiles of the CEO samples, a Hall bar design is proposed to manipulate the edge potential profile from smooth to extremely sharp. By making use of a side-gate perpendicular to the two-dimensional electron system, it is shown that the plateau widths can be changed or even eliminated altogether. Hence, the visibility of IQHE is strongly influenced when adjusting the edge potential profile and/or changing the dc current direction under high currents in the nonlinear transport regime. As a second investigation, we consider two different types of ohmic contacts, namely highly transmitting (ideal) and highly reflecting (non-ideal) contacts. We show that if the injection contacts are non-ideal, but still ohmic, it is possible to measure directly the non-quantized transport taking place at the bulk of the CEO samples. The results of the experiments we propose will clarify the influence of the edge potential profile and the quality of the contacts, under QH conditions. (paper)

Traffic Light Detection

DEFF Research Database (Denmark)

Philipsen, Mark Philip; Jensen, Morten Bornø; Møgelmose, Andreas

2015-01-01

Traffic light recognition (TLR) is an integral part of any intelligent vehicle, which must function in the existing infrastructure. Pedestrian and sign detection have recently seen great improvements due to the introduction of learning based detectors using integral channel features. A similar push...... database is collected based on footage from US roads. The database consists of both test and training data, totaling 46,418 frames and 112,971 annotated traffic lights, captured in continuous sequences under a varying light and weather conditions. The learning based detector achieves an AUC of 0.4 and 0...

Optimization of Process Parameters of Edge Robotic Deburring with Force Control

Directory of Open Access Journals (Sweden)

Burghardt A.

2016-12-01

Full Text Available The issues addressed in the paper present a part of the scientific research conducted within the framework of the automation of the aircraft engine part manufacturing processes. The results of the research presented in the article provided information in which tolerances while using a robotic control station with the option of force control we can make edge deburring.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

Science.gov (United States)

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

Dynamic traffic assignment based trailblazing guide signing for major traffic generator.

Science.gov (United States)

2009-11-01

The placement of guide signs and the display of dynamic massage signs greatly affect drivers : understanding of the network and therefore their route choices. Most existing dynamic traffic assignment : models assume that drivers heading to a Major...

Life on the edge : hedgehog traffic victims and mitigation strategies in an anthropogenic landscape

NARCIS (Netherlands)

Huijser, M.P.

2000-01-01

This study focused on the most frequently recorded mammal species in road-kill surveys in western Europe: the hedgehog (Erinaceus europaeus). Investigations were conducted in an anthropogenic landscape and had two major aims:

1. to quantify the effects of traffic

2. Remotely Accessed Vehicle Traffic Management System

   Science.gov (United States)

   Al-Alawi, Raida

   2010-06-01

   The ever increasing number of vehicles in most metropolitan cities around the world and the limitation in altering the transportation infrastructure, led to serious traffic congestion and an increase in the travelling time. In this work we exploit the emergence of novel technologies such as the internet, to design an intelligent Traffic Management System (TMS) that can remotely monitor and control a network of traffic light controllers located at different sites. The system is based on utilizing Embedded Web Servers (EWS) technology to design a web-based TMS. The EWS located at each intersection uses IP technology for communicating remotely with a Central Traffic Management Unit (CTMU) located at the traffic department authority. Friendly GUI software installed at the CTMU will be able to monitor the sequence of operation of the traffic lights and the presence of traffic at each intersection as well as remotely controlling the operation of the signals. The system has been validated by constructing a prototype that resembles the real application.

3. System and method for traffic signal timing estimation

   KAUST Repository

   Dumazert, Julien; Claudel, Christian G.

   2015-01-01

   A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

4. System and method for traffic signal timing estimation

   KAUST Repository

   Dumazert, Julien

   2015-12-30

   A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

5. A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences

   Science.gov (United States)

   Rudd, Michael E.

   2014-01-01

   Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4. PMID:25202253

6. A Cortical Edge-integration Model of Object-Based Lightness Computation that Explains Effects of Spatial Context and Individual Differences

   Directory of Open Access Journals (Sweden)

   Michael E Rudd

   2014-08-01

   Full Text Available Previous work demonstrated that perceived surface reflectance (lightness can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatial integrates these steps along paths through the image to compute lightness (Rudd & Zemach, 2004, 2005, 2007. This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013 suggests that the human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010 further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer’s interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd & Zemach, 2005. Here, I show how the separate influences of grouping and attention on lightness can be together modeled by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013, and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences.

Science.gov (United States)

Rudd, Michael E

2014-01-01

Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

Robust and fast license plate detection based on the fusion of color and edge feature

Science.gov (United States)

Cai, De; Shi, Zhonghan; Liu, Jin; Hu, Chuanping; Mei, Lin; Qi, Li

2014-11-01

Extracting a license plate is an important stage in automatic vehicle identification. The degradation of images and the computation intense make this task difficult. In this paper, a robust and fast license plate detection based on the fusion of color and edge feature is proposed. Based on the dichromatic reflection model, two new color ratios computed from the RGB color model are introduced and proved to be two color invariants. The global color feature extracted by the new color invariants improves the method's robustness. The local Sobel edge feature guarantees the method's accuracy. In the experiment, the detection performance is good. The detection results show that this paper's method is robust to the illumination, object geometry and the disturbance around the license plates. The method can also detect license plates when the color of the car body is the same as the color of the plates. The processing time for image size of 1000x1000 by pixels is nearly 0.2s. Based on the comparison, the performance of the new ratios is comparable to the common used HSI color model.

Citizen Science for Traffic Planning: A Practical Example

Science.gov (United States)

Rieke, Matthes; Stasch, Christoph; Autermann, Christian; de Wall, Arne; Remke, Albert; Wulffius, Herwig; Jirka, Simon

2017-04-01

Measures affecting traffic flows in urban areas, e.g. changing the configuration of traffic lights, are often causing emotional debates by citizens who are affected by these measures. Up to now, citizens are usually not involved in traffic planning and the evaluation of the decisions that were taken. The enviroCar project provides an open platform for collecting and analyzing car sensor data with GPS position data. On the hardware side, enviroCar relies on using Android smartphones and OBD-II Bluetooth adapters. A Web server component collects and aggregates the readings from the cars, anonymizes them and publishes the data as open data which scientists, public administrations or other third parties can utilize for further analysis. In this work, we provide a general overview on the enviroCar project and present a project in a mid-size city in Germany. The city's administration utilized the enviroCar platform with the help of a traffic system consultancy for including citizens in the evaluation process of different traffic light configurations along major traffic axes. Therefore, a public campaign was started including local workshops to engage the citizens. More than 150 citizens were actively collecting more about 9.500 tracks including about 2.5 million measurements. Dedicated evaluation results for the different traffic axes were computed based on the collected data set. Because the data is publicly available as open data, others may prove and reproduce the evaluation results contributing to an objective discussion of traffic planning measures. In summary, the project illustrates how Citizen Science methods and technologies improve traffic planning and related discussions.

Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

Science.gov (United States)

Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

2016-01-01

This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.

[Traffic deaths and traffic injuries: also an economic problem for society].

Science.gov (United States)

Martinoli, S

1993-02-09

Based on an epidemiological observation on traffic accidents in the Swiss canton of Ticino, 1985, the following statement is possible: In Switzerland, 900 people die every year as a result of traffic casualties. Many victims of these accidents will be disabled for life. Direct and indirect costs of traffic injuries reach 3 billion Swiss francs a year. Only a small amount (6%) is devoted to medical treatment. The biggest part is due as compensation for lost income, disability allocations and loss of productivity. Among the avoidable fatalities those caused by traffic accidents have a very undesirable effect, because they involve mainly the young. More efforts should be undertaken to lower the mortality on the road, because it changes the Swiss population pyramid in a significant manner.

Analysis of elastic-plastic problems using edge-based smoothed finite element method

International Nuclear Information System (INIS)

Cui, X.Y.; Liu, G.R.; Li, G.Y.; Zhang, G.Y.; Sun, G.Y.

2009-01-01

In this paper, an edge-based smoothed finite element method (ES-FEM) is formulated for stress field determination of elastic-plastic problems using triangular meshes, in which smoothing domains associated with the edges of the triangles are used for smoothing operations to improve the accuracy and the convergence rate of the method. The smoothed Galerkin weak form is adopted to obtain the discretized system equations, and the numerical integration becomes a simple summation over the edge-based smoothing domains. The pseudo-elastic method is employed for the determination of stress field and Hencky's total deformation theory is used to define effective elastic material parameters, which are treated as field variables and considered as functions of the final state of stress fields. The effective elastic material parameters are then obtained in an iterative manner based on the strain controlled projection method from the uniaxial material curve. Some numerical examples are investigated and excellent results have been obtained demonstrating the effectivity of the present method.

Automated and observer based light field indicator edge evaluation in diagnostic X-ray equipment

OpenAIRE

Bottaro, Márcio; Nagy, Balázs Vince; Soares, Fernanda Cristina Salvador; Rosendo, Danilo Cabral

2017-01-01

Abstract Introduction To analyze edge detection and optical contrast calculation of light field-indicators used in X-ray via automated- and observer-based methods, and comparison with current standard approaches, which do not give exact definition for light field edge determination. Methods Automated light sensor array was used to measure the penumbra zone of the edge in the standard X-ray equipment, while trained and naïve human observers were asked to mark the light field edge according t...

Systemic Approach to Traffic Evaluation of Mostar Airport

Directory of Open Access Journals (Sweden)

Eldo Raguž

2005-11-01

Full Text Available The attempt of this work is to systematically find solutionsfor Mostar Airport development through technical and technologicalharmonization of traffic processes undertaken in twoseparate organizations - airport and air traffic control and coordinationbetween other traffic branches. The work uses theindicators of traffic flows and tourist trends in the region, andtogether with the mentioned simulations it attempts to evaluatethe traffic potentials in the region by affecting the change in thecurrent negative traffic flows at Mostar Airport.

Urbanization impacts on mammals across urban-forest edges and a predictive model of edge effects.

Science.gov (United States)

Villaseñor, Nélida R; Driscoll, Don A; Escobar, Martín A H; Gibbons, Philip; Lindenmayer, David B

2014-01-01

With accelerating rates of urbanization worldwide, a better understanding of ecological processes at the wildland-urban interface is critical to conserve biodiversity. We explored the effects of high and low-density housing developments on forest-dwelling mammals. Based on habitat characteristics, we expected a gradual decline in species abundance across forest-urban edges and an increased decline rate in higher contrast edges. We surveyed arboreal mammals in sites of high and low housing density along 600 m transects that spanned urban areas and areas turn on adjacent native forest. We also surveyed forest controls to test whether edge effects extended beyond our edge transects. We fitted models describing richness, total abundance and individual species abundance. Low-density housing developments provided suitable habitat for most arboreal mammals. In contrast, high-density housing developments had lower species richness, total abundance and individual species abundance, but supported the highest abundances of an urban adapter (Trichosurus vulpecula). We did not find the predicted gradual decline in species abundance. Of four species analysed, three exhibited no response to the proximity of urban boundaries, but spilled over into adjacent urban habitat to differing extents. One species (Petaurus australis) had an extended negative response to urban boundaries, suggesting that urban development has impacts beyond 300 m into adjacent forest. Our empirical work demonstrates that high-density housing developments have negative effects on both community and species level responses, except for one urban adapter. We developed a new predictive model of edge effects based on our results and the literature. To predict animal responses across edges, our framework integrates for first time: (1) habitat quality/preference, (2) species response with the proximity to the adjacent habitat, and (3) spillover extent/sensitivity to adjacent habitat boundaries. This framework will

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.

Experimental studies of processes with vibrationally excited hydrogen molecules that are important for tokamak edge plasma

International Nuclear Information System (INIS)

Cadez, I.; Markelj, S.; Rupnik, Z.; Pelicon, P.

2006-01-01

We are currently conducting a series of different laboratory experimental studies of processes involving vibrationally excited hydrogen molecules that are relevant to fusion edge plasma. A general overview of our activities is presented together with results of studies of hydrogen recombination on surfaces. This includes vibrational spectroscopy of molecules formed by recombination on metal surfaces exposed to the partially dissociated hydrogen gas and recombination after hydrogen permeation through metal membrane. The goal of these studies is to provide numerical parameters needed for edge plasma modelling and better understanding of plasma wall interaction processes. (author)

Contour extraction of echocardiographic images based on pre-processing

Energy Technology Data Exchange (ETDEWEB)

Hussein, Zinah Rajab; Rahmat, Rahmita Wirza; Abdullah, Lili Nurliyana [Department of Multimedia, Faculty of Computer Science and Information Technology, Department of Computer and Communication Systems Engineering, Faculty of Engineering University Putra Malaysia 43400 Serdang, Selangor (Malaysia); Zamrin, D M [Department of Surgery, Faculty of Medicine, National University of Malaysia, 56000 Cheras, Kuala Lumpur (Malaysia); Saripan, M Iqbal

2011-02-15

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

Contour extraction of echocardiographic images based on pre-processing

International Nuclear Information System (INIS)

Hussein, Zinah Rajab; Rahmat, Rahmita Wirza; Abdullah, Lili Nurliyana; Zamrin, D M; Saripan, M Iqbal

2011-01-01

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

Information processing in echo state networks at the edge of chaos.

Science.gov (United States)

Boedecker, Joschka; Obst, Oliver; Lizier, Joseph T; Mayer, N Michael; Asada, Minoru

2012-09-01

We investigate information processing in randomly connected recurrent neural networks. It has been shown previously that the computational capabilities of these networks are maximized when the recurrent layer is close to the border between a stable and an unstable dynamics regime, the so called edge of chaos. The reasons, however, for this maximized performance are not completely understood. We adopt an information-theoretical framework and are for the first time able to quantify the computational capabilities between elements of these networks directly as they undergo the phase transition to chaos. Specifically, we present evidence that both information transfer and storage in the recurrent layer are maximized close to this phase transition, providing an explanation for why guiding the recurrent layer toward the edge of chaos is computationally useful. As a consequence, our study suggests self-organized ways of improving performance in recurrent neural networks, driven by input data. Moreover, the networks we study share important features with biological systems such as feedback connections and online computation on input streams. A key example is the cerebral cortex, which was shown to also operate close to the edge of chaos. Consequently, the behavior of model systems as studied here is likely to shed light on reasons why biological systems are tuned into this specific regime.

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

International Nuclear Information System (INIS)

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

2006-01-01

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

Analysis of Roadway Traffic Accidents Based on Rough Sets and Bayesian Networks

Directory of Open Access Journals (Sweden)

Xiaoxia Xiong

2018-02-01

Full Text Available The paper integrates Rough Sets (RS and Bayesian Networks (BN for roadway traffic accident analysis. RS reduction of attributes is first employed to generate the key set of attributes affecting accident outcomes, which are then fed into a BN structure as nodes for BN construction and accident outcome classification. Such RS-based BN framework combines the advantages of RS in knowledge reduction capability and BN in describing interrelationships among different attributes. The framework is demonstrated using the 100-car naturalistic driving data from Virginia Tech Transportation Institute to predict accident type. Comparative evaluation with the baseline BNs shows the RS-based BNs generally have a higher prediction accuracy and lower network complexity while with comparable prediction coverage and receiver operating characteristic curve area, proving that the proposed RS-based BN overall outperforms the BNs with/without traditional feature selection approaches. The proposed RS-based BN indicates the most significant attributes that affect accident types include pre-crash manoeuvre, driver’s attention from forward roadway to centre mirror, number of secondary tasks undertaken, traffic density, and relation to junction, most of which feature pre-crash driver states and driver behaviours that have not been extensively researched in literature, and could give further insight into the nature of traffic accidents.

A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure

Directory of Open Access Journals (Sweden)

Yingjie Xia

2013-01-01

Full Text Available Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs, which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI, by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.

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

Directory of Open Access Journals (Sweden)

Tianqi Zhang

2017-01-01

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

Towards Scalable Distributed Framework for Urban Congestion Traffic Patterns Warehousing

Directory of Open Access Journals (Sweden)

A. Boulmakoul

2015-01-01

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

Augmented reality enabling intelligence exploitation at the edge

Science.gov (United States)

Kase, Sue E.; Roy, Heather; Bowman, Elizabeth K.; Patton, Debra

2015-05-01

Today's Warfighters need to make quick decisions while interacting in densely populated environments comprised of friendly, hostile, and neutral host nation locals. However, there is a gap in the real-time processing of big data streams for edge intelligence. We introduce a big data processing pipeline called ARTEA that ingests, monitors, and performs a variety of analytics including noise reduction, pattern identification, and trend and event detection in the context of an area of operations (AOR). Results of the analytics are presented to the Soldier via an augmented reality (AR) device Google Glass (Glass). Non-intrusive AR devices such as Glass can visually communicate contextually relevant alerts to the Soldier based on the current mission objectives, time, location, and observed or sensed activities. This real-time processing and AR presentation approach to knowledge discovery flattens the intelligence hierarchy enabling the edge Soldier to act as a vital and active participant in the analysis process. We report preliminary observations testing ARTEA and Glass in a document exploitation and person of interest scenario simulating edge Soldier participation in the intelligence process in disconnected deployment conditions.

A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System

Directory of Open Access Journals (Sweden)

S. M. Odeh

2015-01-01

Full Text Available This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC and Genetic Algorithms (GAs and its application on a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing, and forecasting. They are, essentially, rule-based systems, in which the definition of these rules and fuzzy membership functions is generally based on verbally formulated rules that overlap through the parameter space. They have a great influence over the performance of the system. On the other hand, the Genetic Algorithm is a metaheuristic that provides a robust search in complex spaces. In this work, it has been used to adapt the decision rules of FLCs that define an intelligent traffic signal system, obtaining a higher performance than a classical FLC-based control. The simulation results yielded by the hybrid algorithm show an improvement of up to 34% in the performance with respect to a standard traffic signal controller, Conventional Traffic Signal Controller (CTC, and up to 31% in the comparison with a traditional logic controller, FLC.

Assembly and offset assignment scheme for self-similar traffic in optical burst switched networks

CSIR Research Space (South Africa)

Muwonge, KB

2007-10-01

Full Text Available at the Label Edge Router (LER) to buffer traffic in the electronic domain. Burst assembly and offset assignment schemes are implemented in a complementary manner to improve QoS of an OBS network. The authors show that OBS network performance is directly related...

Edge Detection from RGB-D Image Based on Structured Forests

Directory of Open Access Journals (Sweden)

Heng Zhang

2016-01-01

Full Text Available This paper looks into the fundamental problem in computer vision: edge detection. We propose a new edge detector using structured random forests as the classifier, which can make full use of RGB-D image information from Kinect. Before classification, the adaptive bilateral filter is used for the denoising processing of the depth image. As data sources, information of 13 channels from RGB-D image is computed. In order to train the random forest classifier, the approximation measurement of the information gain is used. All the structured labels at a given node are mapped to a discrete set of labels using the Principal Component Analysis (PCA method. NYUD2 dataset is used to train our structured random forests. The random forest algorithm is used to classify the RGB-D image information for extracting the edge of the image. In addition to the proposed methodology, the quantitative comparisons of different algorithms are presented. The results of the experiments demonstrate the significant improvements of our algorithm over the state of the art.

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.

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.

Adaptation Computing Parameters of Pan-Tilt-Zoom Cameras for Traffic Monitoring

Directory of Open Access Journals (Sweden)

Ya Lin WU

2014-01-01

Full Text Available The Closed- CIRCUIT television (CCTV cameras have been widely used in recent years for traffic monitoring and surveillance applications. We can use CCTV cameras to extract automatically real-time traffic parameters according to the image processing and tracking technologies. Especially, the pan-tilt-zoom (PTZ cameras can provide flexible view selection as well as a wider observation range, and this makes the traffic parameters can be accurately calculated. Therefore, that the parameters of PTZ cameras are calibrated plays an important role in vision-based traffic applications. However, in the specific traffic environment, which is that the license plate number of the illegal parking is located, the parameters of PTZ cameras have to be updated according to the position and distance of illegal parking. In proposed traffic monitoring systems, we use the ordinary webcam and PTZ camera. We get vanishing-point of traffic lane lines in the pixel-based coordinate system by fixed webcam. The parameters of PTZ camera can be initialized by distance of the traffic monitoring and specific objectives and vanishing-point. And then we can use the coordinate position of the illegally parked car to update the parameters of PTZ camera and then get the real word coordinate position of the illegally parked car and use it to compute the distance. The result shows the error of the tested distance and real distance is only 0.2064 meter.

Information theoretic analysis of edge detection in visual communication

Science.gov (United States)

Jiang, Bo; Rahman, Zia-ur

2010-08-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the artifacts introduced into the process by the image gathering process. However, experiments show that the image gathering process profoundly impacts the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. In this paper, we perform an end-to-end information theory based system analysis to assess edge detection methods. We evaluate the performance of the different algorithms as a function of the characteristics of the scene, and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge detection algorithm is regarded to have high performance only if the information rate from the scene to the edge approaches the maximum possible. This goal can be achieved only by jointly optimizing all processes. People generally use subjective judgment to compare different edge detection methods. There is not a common tool that can be used to evaluate the performance of the different algorithms, and to give people a guide for selecting the best algorithm for a given system or scene. Our information-theoretic assessment becomes this new tool to which allows us to compare the different edge detection operators in a common environment.

Anomalous Traffic Detection and Self-Similarity Analysis in the Environment of ATMSim

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Hae-Duck J. Jeong

2017-12-01

Full Text Available Internet utilisation has steadily increased, predominantly due to the rapid recent development of information and communication networks and the widespread distribution of smartphones. As a result of this increase in Internet consumption, various types of services, including web services, social networking services (SNS, Internet banking, and remote processing systems have been created. These services have significantly enhanced global quality of life. However, as a negative side-effect of this rapid development, serious information security problems have also surfaced, which has led to serious to Internet privacy invasions and network attacks. In an attempt to contribute to the process of addressing these problems, this paper proposes a process to detect anomalous traffic using self-similarity analysis in the Anomaly Teletraffic detection Measurement analysis Simulator (ATMSim environment as a research method. Simulations were performed to measure normal and anomalous traffic. First, normal traffic for each attack, including the Address Resolution Protocol (ARP and distributed denial-of-service (DDoS was measured for 48 h over 10 iterations. Hadoop was used to facilitate processing of the large amount of collected data, after which MapReduce was utilised after storing the data in the Hadoop Distributed File System (HDFS. A new platform on Hadoop, the detection system ATMSim, was used to identify anomalous traffic after which a comparative analysis of the normal and anomalous traffic was performed through a self-similarity analysis. There were four categories of collected traffic that were divided according to the attack methods used: normal local area network (LAN traffic, DDoS attack, and ARP spoofing, as well as DDoS and ARP attack. ATMSim, the anomaly traffic detection system, was used to determine if real attacks could be identified effectively. To achieve this, the ATMSim was used in simulations for each scenario to test its ability to

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

Science.gov (United States)

Arnaout, Georges M.; Bowling, Shannon R.

2011-01-01

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

Measurement of traffic parameters in image sequence using spatio-temporal information

International Nuclear Information System (INIS)

Lee, Daeho; Park, Youngtae

2008-01-01

This paper proposes a novel method for measurement of traffic parameters, such as the number of passed vehicles, velocity and occupancy rate, by video image analysis. The method is based on a region classification followed by spatio-temporal image analysis. Local detection region images in traffic lanes are classified into one of four categories: the road, the vehicle, the reflection and the shadow, by using statistical and structural features. Misclassification at a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. This capability of error correction results in the accurate estimation of traffic parameters even in high traffic congestion. Also headlight detection is employed for nighttime operation. Experimental results show that the accuracy is more than 94% in our test database of diverse operating conditions such as daytime, shadowy daytime, highway, urban way, rural way, rainy day, snowy day, dusk and nighttime. The average processing time is 30 ms per frame when four traffic lanes are processed, and real-time operation could be realized while ensuring robust detection performance even for high-speed vehicles up to 150 km h −1

Localized Edge Vibrations and Edge Reconstruction by Joule Heating in Graphene Nanostructures

DEFF Research Database (Denmark)

Engelund, Mads; Fürst, Joachim Alexander; Jauho, Antti-Pekka

2010-01-01

Control of the edge topology of graphene nanostructures is critical to graphene-based electronics. A means of producing atomically smooth zigzag edges using electronic current has recently been demonstrated in experiments [Jia et al., Science 323, 1701 (2009)]. We develop a microscopic theory...... for current-induced edge reconstruction using density functional theory. Our calculations provide evidence for localized vibrations at edge interfaces involving unpassivated armchair edges. We demonstrate that these vibrations couple to the current, estimate their excitation by Joule heating, and argue...

Reducing traffic in DHT-based discovery protocols for dynamic resources

Science.gov (United States)

Carlini, Emanuele; Coppola, Massimo; Laforenza, Domenico; Ricci, Laura

Existing peer-to-peer approaches for resource location based on distributed hash tables focus mainly on optimizing lookup query resolution. The underlying assumption is that the arrival ratio of lookup queries is higher than the ratio of resource publication operations. We propose a set of optimization strategies to reduce the network traffic generated by the data publication and update process when resources have dynamic-valued attributes. We aim at reducing the publication overhead of supporting multi-attribute range queries. We develop a model predicting the bandwidth reduction, and we assign proper values to the model variables on the basis of real data measurements. We further validate these results by a set of simulations. Our experiments are designed to reproduce the typical behaviour of the resulting scheme within large distributed resource location system, like the resource location service of the XtreemOS Grid-enabled Operating System.

Solutions to Improve Road Circulation in the Pitesti City Based on Analysis-Diagnostics of Road Traffic

Science.gov (United States)

Vîlcan, A.; Neagu, E.; Badarau Suster, H.; Boroiu, A. A.

2017-10-01

Road traffic congestion has become a daily phenomenon in the central area of Pitesti in the peak traffic periods. In order to achieve the mobility plan of Pitesti, an important stage is the diagnostic analysis of the road traffic. For this purpose, the urban road network was formalized through a graph containing the most important 40 intersections and traffic measurements were made at all these intersections and on the main roads connecting the peri-urban area. The data obtained by traffic macrosimulation confirmed the overloading of the street network during peak traffic hours and the analyzes made for various road traffic organization scenarios have shown that there are sustainable solutions for urban mobility only if the road network is fundamentally reconfigured (a belt outside the city and a median ring). Thus, the necessity of realizing the road passage in the Prundu neighbourhood and the finishing of the city belt by realizing the “detour West” of the city is argued. The importance of the work is that it brings scientific arguments for the realization of these road infrastructure projects, integrated in the urban mobility plan, which will base the development strategy of the Pitesti municipality.

An Algorithm of Traffic Perception of DDoS Attacks against SOA Based on Time United Conditional Entropy

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Yuntao Zhao

2016-01-01

Full Text Available DDoS attacks can prevent legitimate users from accessing the service by consuming resource of the target nodes, whose availability of network and service is exposed to a significant threat. Therefore, DDoS traffic perception is the premise and foundation of the whole system security. In this paper the method of DDoS traffic perception for SOA network based on time united conditional entropy was proposed. According to many-to-one relationship mapping between the source IP address and destination IP addresses of DDoS attacks, traffic characteristics of services are analyzed based on conditional entropy. The algorithm is provided with perception ability of DDoS attacks on SOA services by introducing time dimension. Simulation results show that the novel method can realize DDoS traffic perception with analyzing abrupt variation of conditional entropy in time dimension.

Visualization of Traffic Accidents

Science.gov (United States)

Wang, Jie; Shen, Yuzhong; Khattak, Asad

2010-01-01

Traffic accidents have tremendous impact on society. Annually approximately 6.4 million vehicle accidents are reported by police in the US and nearly half of them result in catastrophic injuries. Visualizations of traffic accidents using geographic information systems (GIS) greatly facilitate handling and analysis of traffic accidents in many aspects. Environmental Systems Research Institute (ESRI), Inc. is the world leader in GIS research and development. ArcGIS, a software package developed by ESRI, has the capabilities to display events associated with a road network, such as accident locations, and pavement quality. But when event locations related to a road network are processed, the existing algorithm used by ArcGIS does not utilize all the information related to the routes of the road network and produces erroneous visualization results of event locations. This software bug causes serious problems for applications in which accurate location information is critical for emergency responses, such as traffic accidents. This paper aims to address this problem and proposes an improved method that utilizes all relevant information of traffic accidents, namely, route number, direction, and mile post, and extracts correct event locations for accurate traffic accident visualization and analysis. The proposed method generates a new shape file for traffic accidents and displays them on top of the existing road network in ArcGIS. Visualization of traffic accidents along Hampton Roads Bridge Tunnel is included to demonstrate the effectiveness of the proposed method.

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

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Laisen Nie

2018-01-01

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

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

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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.

Creation Greenhouse Environment Map Using Localization of Edge of Cultivation Platforms Based on Stereo Vision

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A Nasiri

2017-10-01

Full Text Available Introduction Stereo vision means the capability of extracting the depth based on analysis of two images taken from different angles of one scene. The result of stereo vision is a collection of three-dimensional points which describes the details of scene proportional to the resolution of the obtained images. Vehicle automatic steering and crop growth monitoring are two important operations in agricultural precision. The essential aspects of an automated steering are position and orientation of the agricultural equipment in relation to crop row, detection of obstacles and design of path planning between the crop rows. The developed map can provide this information in the real time. Machine vision has the capabilities to perform these tasks in order to execute some operations such as cultivation, spraying and harvesting. In greenhouse environment, it is possible to develop a map and perform an automatic control by detecting and localizing the cultivation platforms as the main moving obstacle. The current work was performed to meet a method based on the stereo vision for detecting and localizing platforms, and then, providing a two-dimensional map for cultivation platforms in the greenhouse environment. Materials and Methods In this research, two webcams, made by Microsoft Corporation with the resolution of 960×544, are connected to the computer via USB2 in order to produce a stereo parallel camera. Due to the structure of cultivation platforms, the number of points in the point cloud will be decreased by extracting the only upper and lower edges of the platform. The proposed method in this work aims at extracting the edges based on depth discontinuous features in the region of platform edge. By getting the disparity image of the platform edges from the rectified stereo images and translating its data to 3D-space, the point cloud model of the environments is constructed. Then by projecting the points to XZ plane and putting local maps together

Silicon K-edge XANES spectra of silicate minerals

Science.gov (United States)

Li, Dien; Bancroft, G. M.; Fleet, M. E.; Feng, X. H.

1995-03-01

Silicon K-edge x-ray absorption near-edge structure (XANES) spectra of a selection of silicate and aluminosilicate minerals have been measured using synchrotron radiation (SR). The spectra are qualitatively interpreted based on MO calculation of the tetrahedral SiO{4/4-}cluster. The Si K-edge generally shifts to higher energy with increased polymerization of silicates by about 1.3 eV, but with considerable overlap for silicates of different polymerization types. The substitution of Al for Si shifts the Si K-edge to lower energy. The chemical shift of Si K-edge is also sensitive to cations in more distant atom shells; for example, the Si K-edge shifts to lower energy with the substitution of Al for Mg in octahedral sites. The shifts of the Si K-edge show weak correlation with average Si-O bond distance (dSi-O), Si-O bond valence (sSi-O) and distortion of SiO4 tetrahedra, due to the crystal structure complexity of silicate minerals and multiple factors effecting the x-ray absorption processes.

Synchronized flow in oversaturated city traffic.

Science.gov (United States)

Kerner, Boris S; Klenov, Sergey L; Hermanns, Gerhard; Hemmerle, Peter; Rehborn, Hubert; Schreckenberg, Michael

2013-11-01

Based on numerical simulations with a stochastic three-phase traffic flow model, we reveal that moving queues (moving jams) in oversaturated city traffic dissolve at some distance upstream of the traffic signal while transforming into synchronized flow. It is found that, as in highway traffic [Kerner, Phys. Rev. E 85, 036110 (2012)], such a jam-absorption effect in city traffic is explained by a strong driver's speed adaptation: Time headways (space gaps) between vehicles increase upstream of a moving queue (moving jam), resulting in moving queue dissolution. It turns out that at given traffic signal parameters, the stronger the speed adaptation effect, the shorter the mean distance between the signal location and the road location at which moving queues dissolve fully and oversaturated traffic consists of synchronized flow only. A comparison of the synchronized flow in city traffic found in this Brief Report with synchronized flow in highway traffic is made.

Mobile Traffic Alert and Tourist Route Guidance System Design Using Geospatial Data

Science.gov (United States)

Bhattacharya, D.; Painho, M.; Mishra, S.; Gupta, A.

2017-09-01

The present study describes an integrated system for traffic data collection and alert warning. Geographical information based decision making related to traffic destinations and routes is proposed through the design. The system includes a geospatial database having profile relating to a user of a mobile device. The processing and understanding of scanned maps, other digital data input leads to route guidance. The system includes a server configured to receive traffic information relating to a route and location information relating to the mobile device. Server is configured to send a traffic alert to the mobile device when the traffic information and the location information indicate that the mobile device is traveling toward traffic congestion. Proposed system has geospatial and mobile data sets pertaining to Bangalore city in India. It is envisaged to be helpful for touristic purposes as a route guidance and alert relaying information system to tourists for proximity to sites worth seeing in a city they have entered into. The system is modular in architecture and the novelty lies in integration of different modules carrying different technologies for a complete traffic information system. Generic information processing and delivery system has been tested to be functional and speedy under test geospatial domains. In a restricted prototype model with geo-referenced route data required information has been delivered correctly over sustained trials to designated cell numbers, with average time frame of 27.5 seconds, maximum 50 and minimum 5 seconds. Traffic geo-data set trials testing is underway.

Thumbnail Image with Blurry Edge Information Utilizing Half Factor Rules

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Boon Tatt Koik

2014-01-01

Full Text Available Thumbnail image with blurry edge information has attracted much attention in recent years. Thumbnail image, which is a tiny version of the original image, enables user to scan through a large proportion of image data for elimination of blurry image or picking up a sharp and a nice image in user’s perspective. The thumbnail image is being utilized commonly in camera, smart phone, and other computing devices. In this paper, a method to embed blurry edge information in thumbnail images is proposed. This method is straight forward and simple to be implemented in electronic products. The image will undergo edge width measurement process by finding the local maximum and local minimum locations based on its edge magnitude. This is obtained after the implementation of horizontal and vertical first order derivatives of the original high resolution input image. The blur edges will be emphasized by utilizing edge width information during downsampling process to enable users to identify blurry edge image distinctively. Experimental results show a satisfactory outcome in embedding blurry characteristics of the original image to thumbnail image on the proposed method.

Understanding the T2 traffic in CMS during Run-1

Science.gov (United States)

T, Wildish

2015-12-01

In the run-up to Run-1 CMS was operating its facilities according to the MONARC model, where data-transfers were strictly hierarchical in nature. Direct transfers between Tier-2 nodes was excluded, being perceived as operationally intensive and risky in an era where the network was expected to be a major source of errors. By the end of Run-1 wide-area networks were more capable and stable than originally anticipated. The original data-placement model was relaxed, and traffic was allowed between Tier-2 nodes. Tier-2 to Tier-2 traffic in 2012 already exceeded the amount of Tier-2 to Tier-1 traffic, so it clearly has the potential to become important in the future. Moreover, while Tier-2 to Tier-1 traffic is mostly upload of Monte Carlo data, the Tier-2 to Tier-2 traffic represents data moved in direct response to requests from the physics analysis community. As such, problems or delays there are more likely to have a direct impact on the user community. Tier-2 to Tier-2 traffic may also traverse parts of the WAN that are at the 'edge' of our network, with limited network capacity or reliability compared to, say, the Tier-0 to Tier-1 traffic which goes the over LHCOPN network. CMS is looking to exploit technologies that allow us to interact with the network fabric so that it can manage our traffic better for us, this we hope to achieve before the end of Run-2. Tier-2 to Tier-2 traffic would be the most interesting use-case for such traffic management, precisely because it is close to the users' analysis and far from the 'core' network infrastructure. As such, a better understanding of our Tier-2 to Tier-2 traffic is important. Knowing the characteristics of our data-flows can help us place our data more intelligently. Knowing how widely the data moves can help us anticipate the requirements for network capacity, and inform the dynamic data placement algorithms we expect to have in place for Run-2. This paper presents an analysis of the CMS Tier-2 traffic during Run 1.

Image edges detection through B-Spline filters

International Nuclear Information System (INIS)

Mastropiero, D.G.

1997-01-01

B-Spline signal processing was used to detect the edges of a digital image. This technique is based upon processing the image in the Spline transform domain, instead of doing so in the space domain (classical processing). The transformation to the Spline transform domain means finding out the real coefficients that makes it possible to interpolate the grey levels of the original image, with a B-Spline polynomial. There exist basically two methods of carrying out this interpolation, which produces the existence of two different Spline transforms: an exact interpolation of the grey values (direct Spline transform), and an approximated interpolation (smoothing Spline transform). The latter results in a higher smoothness of the gray distribution function defined by the Spline transform coefficients, and is carried out with the aim of obtaining an edge detection algorithm which higher immunity to noise. Finally the transformed image was processed in order to detect the edges of the original image (the gradient method was used), and the results of the three methods (classical, direct Spline transform and smoothing Spline transform) were compared. The results were that, as expected, the smoothing Spline transform technique produced a detection algorithm more immune to external noise. On the other hand the direct Spline transform technique, emphasizes more the edges, even more than the classical method. As far as the consuming time is concerned, the classical method is clearly the fastest one, and may be applied whenever the presence of noise is not important, and whenever edges with high detail are not required in the final image. (author). 9 refs., 17 figs., 1 tab

Development of a Simple Traffic Sensor and System with Vehicle Classification Based on PVDF Film Element

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D. R. SANTOSO

2011-03-01

Full Text Available In this paper, piezoelectric sensor system for measuring traffic flow with vehicle classification is proposed and investigated. Sensing element is made of PVDF film, which on both sides plastered with sheets of metal electrodes for making electrical connections. This sensor will generate electric voltage when subjected to mechanical pressure by the wheels of the vehicle. The signal conditioning is required to make sensor output voltage in the range of 0-5 Volts. To classify the types of vehicles crossing the sensor, three-level comparator is used, with specifications of a low voltage reference for motorcycles, medium voltage reference for a family vehicle, and a high voltage reference for buses, trucks and the like. Output of the comparators are already a logic '0' or '1' is then processed by a microcontroller based data acquisition system that the output shows the number and type of vehicles that crossed the road in the form of digital code. These data then transmitted to a control centre that was built based on a PC. At the control centre, traffic data tabulated in the form of measurement database and stored for further analysis.

A Multicast Sparse-Grooming Algorithm Based on Network Coding in WDM Networks

Science.gov (United States)

Zhang, Shengfeng; Peng, Han; Sui, Meng; Liu, Huanlin

2015-03-01

To improve the limited number of wavelength utilization and decrease the traffic blocking probability in sparse-grooming wavelength-division multiplexing (WDM) networks, a multicast sparse-grooming algorithm based on network coding (MCSA-NC) is put forward to solve the routing problem for dynamic multicast requests in this paper. In the proposed algorithm, a traffic partition strategy, that the coarse-granularity multicast request with grooming capability on the source node is split into several fine-granularity multicast requests, is designed so as to increase the probability for traffic grooming successfully in MCSA-NC. Besides considering that multiple destinations should receive the data from source of the multicast request at the same time, the traditional transmission mechanism is improved by constructing edge-disjoint paths for each split multicast request. Moreover, in order to reduce the number of wavelengths required and further decrease the traffic blocking probability, a light-tree reconfiguration mechanism is presented in the MCSA-NC, which can select a minimal cost light tree from the established edge-disjoint paths for a new multicast request.

Edge and line detection of complicated and blurred objects

OpenAIRE

Haugsdal, Kari

2010-01-01

This report deals with edge and line detection in pictures with complicated and/or blurred objects. It explores the alternatives available, in edge detection, edge linking and object recognition. Choice of methods are the Canny edge detection and Local edge search processing combined with regional edge search processing in the form of polygon approximation.

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

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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.

Scale-up of ethanol production from winter barley by the EDGE (enhanced dry grind enzymatic) process in fermentors up to 300 liters

Science.gov (United States)

A fermentation process, which was designated the EDGE (enhanced dry grind enzymatic) process, has recently been developed for barley ethanol production. In the EDGE process, in addition to the enzymes normally required for starch hydrolysis, commercial Beta-glucanases were used to hydrolyze (1,3)(1,...

Modelling of H.264 MPEG2 TS Traffic Source

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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.

Development of a mobile application for manual traffic counts

Directory of Open Access Journals (Sweden)

Ghanim Mohammad

2017-01-01

Full Text Available The use of technology in performing traffic counts has become widely used by many transportation agencies and private sectors. Different technologies have been employed to perform such counts, such as inductive loops, image processing, Bluetooth technologies, and laser and infrared technologies. However, the use of these advanced technologies come with extra cost to develop, install, and maintain. While the use of advanced technologies provide reliable traffic counts and vehicle classifications data, the use of manual traffic is an inevitable task. Manual traffic counts can serve different purposes, such as performing quality control or conducting short-term traffic survey. Manual traffic counts are usually conducted with the use of the traditional paper-and-pencil approach or the use of hand-held devices that are specifically developed to assess performing manual traffic counts. In this paper, the development of a mobile app that can be used to assist those who need to perform manual traffic counts. The app can be used by many public agencies, private sectors, and college students to collect their traffic data. It also provides users with the capabilities of sharing their traffic counts instantly, where traffic counts can be extracted and processed quickly by other parties.

Silicon oxide nanoimprint stamp fabrication by edge lithography reinforced with silicon nitride

NARCIS (Netherlands)

Zhao, Yiping; Berenschot, Johan W.; de Boer, Meint J.; Jansen, Henricus V.; Tas, Niels Roelof; Huskens, Jurriaan; Elwenspoek, Michael Curt

2007-01-01

The fabrication of silicon oxide nanoimprint stamp employing edge lithography in combination with silicon nitride deposition is presented. The fabrication process is based on conventional photolithography an weg etching methods. Nanoridges with width dimension of sub-20 nm were fabricated by edge

Optimization of traffic distribution control in software-configurable infrastructure of virtual data center based on a simulation model

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I. P. Bolodurina

2017-01-01

Full Text Available Currently, the proportion of use of cloud computing technology in today's business processes of companies is growing steadily. Despite the fact that it allows you to reduce the cost of ownership and operation of IT infrastructure, there are a number of problems related to the control of data centers. One such problem is the efficiency of the use of available companies compute and network resources. One of the directions of optimization is the process of traffic control of cloud applications and services in data centers. Given the multi-tier architecture of modern data center, this problem does not quite trivial. The advantage of modern virtual infrastructure is the ability to use software-configurable networks and software-configurable data storages. However, existing solutions with algorithmic optimization does not take into account a number of features forming network traffic with multiple classes of applications. Within the framework of the exploration solved the problem of optimizing the distribution of traffic cloud applications and services for the software-controlled virtual data center infrastructure. A simulation model describing the traffic in data center and software-configurable network segments involved in the processing of user requests for applications and services located network environment that includes a heterogeneous cloud platform and software-configurable data storages. The developed model has allowed to implement cloud applications traffic management algorithm and optimize access to the storage system through the effective use of the channel for data transmission. In experimental studies found that the application of the developed algorithm can reduce the response time of cloud applications and services, and as a result improve the performance of processing user requests and to reduce the number of failures.

A NEURAL NETWORK BASED TRAFFIC-AWARE FORWARDING STRATEGY IN NAMED DATA NETWORKING

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Parisa Bazmi

2016-11-01

Full Text Available Named Data Networking (NDN is a new Internet architecture which has been proposed to eliminate TCP/IP Internet architecture restrictions. This architecture is abstracting away the notion of host and working based on naming datagrams. However, one of the major challenges of NDN is supporting QoS-aware forwarding strategy so as to forward Interest packets intelligently over multiple paths based on the current network condition. In this paper, Neural Network (NN Based Traffic-aware Forwarding strategy (NNTF is introduced in order to determine an optimal path for Interest forwarding. NN is embedded in NDN routers to select next hop dynamically based on the path overload probability achieved from the NN. This solution is characterized by load balancing and QoS-awareness via monitoring the available path and forwarding data on the traffic-aware shortest path. The performance of NNTF is evaluated using ndnSIM which shows the efficiency of this scheme in terms of network QoS improvementof17.5% and 72% reduction in network delay and packet drop respectively.

Defect detection based on extreme edge of defective region histogram

Directory of Open Access Journals (Sweden)

Zouhir Wakaf

2018-01-01

Full Text Available Automatic thresholding has been used by many applications in image processing and pattern recognition systems. Specific attention was given during inspection for quality control purposes in various industries like steel processing and textile manufacturing. Automatic thresholding problem has been addressed well by the commonly used Otsu method, which provides suitable results for thresholding images based on a histogram of bimodal distribution. However, the Otsu method fails when the histogram is unimodal or close to unimodal. Defects have different shapes and sizes, ranging from very small to large. The gray-level distributions of the image histogram can vary between unimodal and multimodal. Furthermore, Otsu-revised methods, like the valley-emphasis method and the background histogram mode extents, which overcome the drawbacks of the Otsu method, require preprocessing steps and fail to use the general threshold for multimodal defects. This study proposes a new automatic thresholding algorithm based on the acquisition of the defective region histogram and the selection of its extreme edge as the threshold value to segment all defective objects in the foreground from the image background. To evaluate the proposed defect-detection method, common standard images for experimentation were used. Experimental results of the proposed method show that the proposed method outperforms the current methods in terms of defect detection.

Spatial Analysis of Traffic and Routing Path Methods for Tsunami Evacuation

Science.gov (United States)

Fakhrurrozi, A.; Sari, A. M.

2018-02-01

Tsunami disaster occurred relatively very fast. Thus, it has a very large-scale impact on both non-material and material aspects. Community evacuation caused mass panic, crowds, and traffic congestion. A further research in spatial based modelling, traffic engineering and splitting zone evacuation simulation is very crucial as an effort to reduce higher losses. This topic covers some information from the previous research. Complex parameters include route selection, destination selection, the spontaneous timing of both the departure of the source and the arrival time to destination and other aspects of the result parameter in various methods. The simulation process and its results, traffic modelling, and routing analysis emphasized discussion which is the closest to real conditions in the tsunami evacuation process. The method that we should highlight is Clearance Time Estimate based on Location Priority in which the computation result is superior to others despite many drawbacks. The study is expected to have input to improve and invent a new method that will be a part of decision support systems for disaster risk reduction of tsunamis disaster.

A sensor network architecture for urban traffic state estimation with mixed eulerian/lagrangian sensing based on distributed computing

KAUST Repository

Canepa, Edward S.; Odat, Enas M.; Dehwah, Ahmad H.; Mousa, Mustafa; Jiang, Jiming; Claudel, Christian G.

2014-01-01

This article describes a new approach to urban traffic flow sensing using decentralized traffic state estimation. Traffic sensor data is generated both by fixed traffic flow sensor nodes and by probe vehicles equipped with a short range transceiver. The data generated by these sensors is sent to a local coordinator node, that poses the problem of estimating the local state of traffic as a mixed integer linear program (MILP). The resulting optimization program is then solved by the nodes in a distributed manner, using branch-and-bound methods. An optimal amount of noise is then added to the maps before dissemination to a central database. Unlike existing probe-based traffic monitoring systems, this system does not transmit user generated location tracks nor any user presence information to a centralized server, effectively preventing privacy attacks. A simulation of the system performance on computer-generated traffic data shows that the system can be implemented with currently available technology. © 2014 Springer International Publishing Switzerland.

Traffic accidents: an econometric investigation

OpenAIRE

Tito Moreira; Adolfo Sachsida; Loureiro Paulo

2004-01-01

Based on a sample of drivers in Brasilia's streets, this article investigates whether distraction explains traffic accidents. A probit model is estimated to determine the predictive power of several variables on traffic accidents. The main conclusion drawn from this study is that the proxies used to measure distraction, such as the use of cell phones and cigarette smoking in a moving vehicle, are significant factors in determining traffic accidents.

Visual Analysis in Traffic & Re-identification

DEFF Research Database (Denmark)

Møgelmose, Andreas

and analysis, and person re-identification. In traffic sign detection, the work comprises a thorough survey of the state of the art, assembly of the worlds largest public dataset with U.S. traffic signs, and work in machine learning based detection algorithms. It was shown that detection of U.S. traffic signs...

SoC-Based Edge Computing Gateway in the Context of the Internet of Multimedia Things: Experimental Platform

Directory of Open Access Journals (Sweden)

Maher Jridi

2018-01-01

Full Text Available This paper presents an algorithm/architecture and Hardware/Software co-designs for implementing a digital edge computing layer on a Zynq platform in the context of the Internet of Multimedia Things (IoMT. Traditional cloud computing is no longer suitable for applications that require image processing due to cloud latency and privacy concerns. With edge computing, data are processed, analyzed, and encrypted very close to the device, which enable the ability to secure data and act rapidly on connected things. The proposed edge computing system is composed of a reconfigurable module to simultaneously compress and encrypt multiple images, along with wireless image transmission and display functionalities. A lightweight implementation of the proposed design is obtained by approximate computing of the discrete cosine transform (DCT and by using a simple chaotic generator which greatly enhances the encryption efficiency. The deployed solution includes four configurations based on HW/SW partitioning in order to handle the compromise between execution time, area, and energy consumption. It was found with the experimental setup that by moving more components to hardware execution, a timing speedup of more than nine times could be achieved with a negligible amount of energy consumption. The power efficiency was then enhanced by a ratio of 7.7 times.

Application of machine learning methods for traffic signs recognition

Science.gov (United States)

Filatov, D. V.; Ignatev, K. V.; Deviatkin, A. V.; Serykh, E. V.

2018-02-01

This paper focuses on solving a relevant and pressing safety issue on intercity roads. Two approaches were considered for solving the problem of traffic signs recognition; the approaches involved neural networks to analyze images obtained from a camera in the real-time mode. The first approach is based on a sequential image processing. At the initial stage, with the help of color filters and morphological operations (dilatation and erosion), the area containing the traffic sign is located on the image, then the selected and scaled fragment of the image is analyzed using a feedforward neural network to determine the meaning of the found traffic sign. Learning of the neural network in this approach is carried out using a backpropagation method. The second approach involves convolution neural networks at both stages, i.e. when searching and selecting the area of the image containing the traffic sign, and when determining its meaning. Learning of the neural network in the second approach is carried out using the intersection over union function and a loss function. For neural networks to learn and the proposed algorithms to be tested, a series of videos from a dash cam were used that were shot under various weather and illumination conditions. As a result, the proposed approaches for traffic signs recognition were analyzed and compared by key indicators such as recognition rate percentage and the complexity of neural networks’ learning process.

Research on Urban Road Traffic Congestion Charging Based on Sustainable Development

Science.gov (United States)

Ye, Sun

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

Intelligent Testing of Traffic Light Programs: Validation in Smart Mobility Scenarios

Directory of Open Access Journals (Sweden)

Javier Ferrer

2016-01-01

Full Text Available In smart cities, the use of intelligent automatic techniques to find efficient cycle programs of traffic lights is becoming an innovative front for traffic flow management. However, this automatic programming of traffic lights requires a validation process of the generated solutions, since they can affect the mobility (and security of millions of citizens. In this paper, we propose a validation strategy based on genetic algorithms and feature models for the automatic generation of different traffic scenarios checking the robustness of traffic light cycle programs. We have concentrated on an extensive urban area in the city of Malaga (in Spain, in which we validate a set of candidate cycle programs generated by means of four optimization algorithms: Particle Swarm Optimization for Traffic Lights, Differential Evolution for Traffic Lights, random search, and Sumo Cycle Program Generator. We can test the cycles of traffic lights considering the different states of the city, weather, congestion, driver expertise, vehicle’s features, and so forth, but prioritizing the most relevant scenarios among a large and varied set of them. The improvement achieved in solution quality is remarkable, especially for CO2 emissions, in which we have obtained a reduction of 126.99% compared with the experts’ solutions.

Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

Science.gov (United States)

Hamdan, H. G. Muhammad; Khalifah, O. O.

2017-11-01

Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded.

Urbanization impacts on mammals across urban-forest edges and a predictive model of edge effects.

Directory of Open Access Journals (Sweden)

Nélida R Villaseñor

Full Text Available With accelerating rates of urbanization worldwide, a better understanding of ecological processes at the wildland-urban interface is critical to conserve biodiversity. We explored the effects of high and low-density housing developments on forest-dwelling mammals. Based on habitat characteristics, we expected a gradual decline in species abundance across forest-urban edges and an increased decline rate in higher contrast edges. We surveyed arboreal mammals in sites of high and low housing density along 600 m transects that spanned urban areas and areas turn on adjacent native forest. We also surveyed forest controls to test whether edge effects extended beyond our edge transects. We fitted models describing richness, total abundance and individual species abundance. Low-density housing developments provided suitable habitat for most arboreal mammals. In contrast, high-density housing developments had lower species richness, total abundance and individual species abundance, but supported the highest abundances of an urban adapter (Trichosurus vulpecula. We did not find the predicted gradual decline in species abundance. Of four species analysed, three exhibited no response to the proximity of urban boundaries, but spilled over into adjacent urban habitat to differing extents. One species (Petaurus australis had an extended negative response to urban boundaries, suggesting that urban development has impacts beyond 300 m into adjacent forest. Our empirical work demonstrates that high-density housing developments have negative effects on both community and species level responses, except for one urban adapter. We developed a new predictive model of edge effects based on our results and the literature. To predict animal responses across edges, our framework integrates for first time: (1 habitat quality/preference, (2 species response with the proximity to the adjacent habitat, and (3 spillover extent/sensitivity to adjacent habitat boundaries. This

New Solutions Based On Wireless Networks For Dynamic Traffic Lights Management: A Comparison Between IEEE 802.15.4 And Bluetooth

Directory of Open Access Journals (Sweden)

Collotta Mario

2015-09-01

Full Text Available The Wireless Sensor Networks are widely used to detect and exchange information and in recent years they have been increasingly involved in Intelligent Transportation System applications, especially in dynamic management of signalized intersections. In fact, the real-time knowledge of information concerning traffic light junctions represents a valid solution to congestion problems. In this paper, a wireless network architecture, based on IEEE 802.15.4 or Bluetooth, in order to monitor vehicular traffic flows near to traffic lights, is introduced. Moreover, an innovative algorithm is proposed in order to determine dynamically green times and phase sequence of traffic lights, based on measured values of traffic flows. Several simulations compare IEEE 802.15.4 and Bluetooth protocols in order to identify the more suitable communication protocol for ITS applications. Furthermore, in order to confirm the validity of the proposed algorithm for the dynamic management of traffic lights, some case studies have been considered and several simulations have been performed.

Dementia and traffic accidents: a Danish register-based cohort study

DEFF Research Database (Denmark)

Petersen, Jindong Ding; Siersma, Volkert Dirk; Nielsen, CT

2016-01-01

BACKGROUND: As a consequence of a rapid growth of an ageing population, more people with dementia are expected on the roads. Little is known about whether these people are at increased risk of road traffic-related accidents. OBJECTIVE: Our study aims to investigate the risk of road traffic...... Central Research Register, and/or (2) at least one dementia diagnosis-related drug prescription registration in the Danish National Prescription Registry. Police-, hospital-, and emergency room-reported road traffic-related accidents occurred within the study follow-up are defined as the study outcome...... selection bias due to nonparticipation and loss to follow-up. Furthermore, this ensures that the study results are reliable and generalizable. However, underreporting of traffic-related accidents may occur, which will limit estimation of absolute risks....

The development of area wide traffic management scenarios

NARCIS (Netherlands)

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

2014-01-01

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

Performance of chip seals using local and minimally processed aggregates for preservation of low traffic volume roadways.

Science.gov (United States)

2013-07-01

This report documents the performance of two low traffic volume experimental chip seals constructed using : locally available, minimally processed sand and gravel aggregates after four winters of service. The projects : were constructed by CDOT maint...

A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting

Directory of Open Access Journals (Sweden)

Shifen Cheng

2018-06-01

Full Text Available Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and

Emergent traffic jams

International Nuclear Information System (INIS)

Nagel, K.; Paczuski, M.

1995-01-01

We study a single-lane traffic model that is based on human driving behavior. The outflow from a traffic jam self-organizes to a critical state of maximum throughput. Small perturbations of the outflow far downstream create emergent traffic jams with a power law distribution P(t)∼t -3/2 of lifetimes t. On varying the vehicle density in a closed system, this critical state separates lamellar and jammed regimes and exhibits 1/f noise in the power spectrum. Using random walk arguments, in conjunction with a cascade equation, we develop a phenomenological theory that predicts the critical exponents for this transition and explains the self-organizing behavior. These predictions are consistent with all of our numerical results

Emergent traffic jams

Science.gov (United States)

Nagel, Kai; Paczuski, Maya

1995-04-01

We study a single-lane traffic model that is based on human driving behavior. The outflow from a traffic jam self-organizes to a critical state of maximum throughput. Small perturbations of the outflow far downstream create emergent traffic jams with a power law distribution P(t)~t-3/2 of lifetimes t. On varying the vehicle density in a closed system, this critical state separates lamellar and jammed regimes and exhibits 1/f noise in the power spectrum. Using random walk arguments, in conjunction with a cascade equation, we develop a phenomenological theory that predicts the critical exponents for this transition and explains the self-organizing behavior. These predictions are consistent with all of our numerical results.

Production of ethanol from winter barley by the EDGE (enhanced dry grind enzymatic process

Directory of Open Access Journals (Sweden)

Kurantz M

2010-04-01

Full Text Available Abstract Background US legislation requires the use of advanced biofuels to be made from non-food feedstocks. However, commercialization of lignocellulosic ethanol technology is more complex than expected and is therefore running behind schedule. This is creating a demand for non-food, but more easily converted, starch-based feedstocks other than corn that can fill the gap until the second generation technologies are commercially viable. Winter barley is such a feedstock but its mash has very high viscosity due to its high content of β-glucans. This fact, along with a lower starch content than corn, makes ethanol production at the commercial scale a real challenge. Results A new fermentation process for ethanol production from Thoroughbred, a winter barley variety with a high starch content, was developed. The new process was designated the EDGE (enhanced dry grind enzymatic process. In this process, in addition to the normal starch-converting enzymes, two accessory enzymes were used to solve the β-glucan problem. First, β-glucanases were used to hydrolyze the β-glucans to oligomeric fractions, thus significantly reducing the viscosity to allow good mixing for the distribution of the yeast and nutrients. Next, β-glucosidase was used to complete the β-glucan hydrolysis and to generate glucose, which was subsequently fermented in order to produce additional ethanol. While β-glucanases have been previously used to improve barley ethanol production by lowering viscosity, this is the first full report on the benefits of adding β-glucosidases to increase the ethanol yield. Conclusions In the EDGE process, 30% of total dry solids could be used to produce 15% v/v ethanol. Under optimum conditions an ethanol yield of 402 L/MT (dry basis or 2.17 gallons/53 lb bushel of barley with 15% moisture was achieved. The distillers dried grains with solubles (DDGS co-product had extremely low β-glucan (below 0.2% making it suitable for use in both ruminant

Edges in CNC polishing: from mirror-segments towards semiconductors, paper 1: edges on processing the global surface.

Science.gov (United States)

Walker, David; Yu, Guoyu; Li, Hongyu; Messelink, Wilhelmus; Evans, Rob; Beaucamp, Anthony

2012-08-27

Segment-edges for extremely large telescopes are critical for observations requiring high contrast and SNR, e.g. detecting exo-planets. In parallel, industrial requirements for edge-control are emerging in several applications. This paper reports on a new approach, where edges are controlled throughout polishing of the entire surface of a part, which has been pre-machined to its final external dimensions. The method deploys compliant bonnets delivering influence functions of variable diameter, complemented by small pitch tools sized to accommodate aspheric mis-fit. We describe results on witness hexagons in preparation for full size prototype segments for the European Extremely Large Telescope, and comment on wider applications of the technology.

ADAPTIVE ANT COLONY OPTIMIZATION BASED GRADIENT FOR EDGE DETECTION