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Journal of System Simulation

Abstract

Abstract: Arterial signal coordination is usually based on fixed belt speeds and time-of-day statistical flows. Actually, vehicle speeds and traffic flows are fluctuating, which causes to the mismatch between the signal scheme and the actual optimal belt speeds and traffic flow demands, and affects the intersection's traffic efficiency. Based on the vehicle infrastructure cooperation, by applying Maxband model and the maximum green wave bandwidth, the minimum number of arterial vehicle delays, arterial stops and the minor direction delays being the optimization objectives, a multi-objective optimization model for arterial signal coordination is established. Through using an improved multi-objective particle swarm algorithm the model is solved to obtain the parameters of the coordinated intersection global control scheme. A vehicle speed guidance model is proposed based on the intersection inlet lane vehicle location and signal state. According to the vehicle saturation of the inlet lane of the arterial intersection, an inductive control strategy is applied to adjust the green light timing of each intersection in real time on the basis of global coordination. The results show that the optimization model combines the speed guidance and signal coordination, considers the mainline intersection loading degree situation, dynamically adjusts the green time, reduces the number of delays and stops at intersections, and can effectively improve the efficiency of arterial coordination control.

First Page

1309

Last Page

1321

CLC

TP391.9; U491.2

Recommended Citation

Deng Mingjun, Hu Xinxia, Li Xiang, et al. Arterial Coordination Optimization Method Based on Vehicle Speed Guidance and Inductive Control[J]. Journal of System Simulation, 2024, 36(6): 1309-1321.

DOI

10.16182/j.issn1004731x.joss.23-0315

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