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.
Highlights
Congestion is one of major problems of urban traffic system
In 1960s, fixed-time traffic control methods are proposed based on off-line historical data, such as TRANSYT (Robertson 1969) and MAXBAND (Little et al 1981), different optimal timing plans are selected at different time of a day
Backpressure based traffic control method is a distributed policy for urban road networks. It can determine the switching traffic phase based on the local traffic information especially queue length of each link of intersections
Summary
Congestion is one of major problems of urban traffic system. Traffic control strategy plays an important role to improve traffic efficiency and balance traffic load. Adaptive traffic control strategies are proposed to adjust signal timing plans based on online traffic information for responding to real-time traffic demand, such as SCOOT (Hunt et al 1981) and SCATS (Lowrie 1982). Centralized signal timing schemes are computed according to current traffic conditions, but be implied in cycle, when traffic situation may have changed already (Cesme, Furth 2014) For fixing these deficiencies, there is a consensus of researchers that distributed traffic control policy is ideal alternative. The existing backpressure based traffic signal control algorithms compute phase pressure to determine active phase according to queue length and routing rates. The control parameter V and penalty function can trade off queue differential and congestion status of downstream links, avoiding spillback on downstream links
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