Traffic Congestion Evaluation and Signal Timing Optimization Based on Wireless Sensor Networks: Issues, Approaches and Simulation

• Published in: Journal of Information Science and Engineering Vol. 30; no. 4; pp. 1245 - 1260
• Main Authors: 張偉(Wei Zhang), 譚國真(Guo-Zhen Tan), 丁男(Nan Ding), 王光遠(Guang-Yuan Wang)
• Format: Journal Article
• Language: English
• Published: Taipei 社團法人中華民國計算語言學學會 01.07.2014; Institute of Information Science, Academia sinica
• Subjects: Applied sciences; Computer simulation; Congestion; Exact sciences and technology; Ground, air and sea transportation, marine construction; Logistics; Mathematical models; Monitoring; Operational research and scientific management; Operational research. Management science; Optimization; Queuing theory. Traffic theory; Radiocommunications; Road transportation and traffic; Telecommunications; Telecommunications and information theory; Time measurements; Traffic engineering; Traffic flow; traffic congestion evaluation; traffic surveillance; wireless sensor networks; congestion factor; traffic flow theory; cost function; multi-objective optimization; intelligent transportation system; scattered data fitting; timing phase optimization; Traffic lights; Line segment; Multiobjective programming; Temporal databases; Modeling; Adaptive method; Optimization; Delay; Traffic flow; Traffic control; Cost function; Monitoring; Script; Computer simulation; Measurement sensor; Traffic controller; Real time; Road signalling; Real time system; Sampling frequency; Computational geometry; Traffic management; Cross roads; Wireless network; Road traffic; Timing; Sensor array; Curve fitting; Subcriticality; Traffic congestion
• ISSN: 1016-2364
• DOI: 10.6688/JISE.2014.30.4.18

This paper proposed the model and algorithms for traffic data monitoring and signal timing optimization based on continuum traffic model and wireless sensor networks. Given the scenario that sensor nodes are sparsely installed along the segment between signalized intersections, an analytical model is built based on continuum traffic equations, and an adaptive interpolation method is proposed to estimate traffic parameters with scattered sensor data. Based on the principle of traffic congestion formation, a congestion factor is introduced which can be used to evaluate the real-time status of traffic congestion along the segment, and to predict the subcritical state of traffic jams. The result is expected to support the signal timing optimization of traffic light control for the purpose to avoid traffic jams before its formation. We simulated the traffic monitoring based on Mobile Century dataset, and analyzed the performance of signal control on VISSIM platform when congestion factor is introduced into the phase optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring, and it's helpful to alleviate urban traffic congestion that remarkably decreases the average delays and maximum queue length.