1. Backpressure based traffic signal control considering capacity of downstream links
- Author
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Shenxue Hao, Licai Yang, Yunfeng Shi, and Yajuan Guo
- Subjects
Injury control ,Accident prevention ,Computer science ,Control (management) ,queuing network ,Poison control ,penalty function ,02 engineering and technology ,Traffic signal ,backpressure algorithm ,Downstream (manufacturing) ,0502 economics and business ,Injury prevention ,0202 electrical engineering, electronic engineering, information engineering ,Operations management ,050210 logistics & transportation ,traffic signal control ,TA1001-1280 ,Mechanical Engineering ,05 social sciences ,ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS ,stability ,Transportation engineering ,traffic control ,Automotive Engineering ,020201 artificial intelligence & image processing - Abstract
Congestion is a kind of expression of instability of traffic network. Traffic signal control keeping traffic network stable can reduce the congestion of urban traffic. In order to improve the efficiency of urban traffic network, this study proposes a decentralized traffic signal control strategy based on backpressure algorithm used in Wi-Fi mesh networks for packets routing. Backpressure based traffic signal control algorithm can stabilize urban traffic network and achieve maximum throughput. Based on original backpressure algorithm, the variant parameter and penalty function are considered to balance the queue differential and capacity of downstream links in urban traffic network. For each traffic phase of intersections, phase weight is computed using queue differential and capacity of downstream links, which fixed the deficiency of infinite queue capacity in original backpressure algorithm. It is proved that the extended backpressure traffic signal control algorithm can maintain stability of urban traffic network, and also can prevent queue spillback, so as to improve performance of whole traffic network. Simulations are carried out in Vissim using Vissim COM programming interface and Visual Studio development tools. Evaluation results illuminate that it can get better performance than the backpressure algorithm just based on queue length differential in average queue length and delay of traffic network.
- Published
- 2020