A genetic timing scheduling model for urban traffic signal control

被引:15
|
作者
Wang, Huan [1 ]
Hu, Po [2 ]
Wang, Hao [3 ]
机构
[1] Huazhong Agr Univ, Coll Informat, Wuhan, Peoples R China
[2] Cent China Normal Univ, Sch Comp, Wuhan, Peoples R China
[3] Chongqing Univ Posts & Telecommun, Coll Comp Sci & Technol, Chongqing, Peoples R China
基金
中国国家自然科学基金;
关键词
Traffic signal control; Urban road network; Control; Intersection; Traffic flow; PARTICLE SWARM OPTIMIZATION; ALGORITHM; MANAGEMENT;
D O I
10.1016/j.ins.2021.06.082
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As urban traffic condition is diverse and complicated, maximizing the use of urban traffic signal control system to solve traffic issues becomes one of the hot and promising topics. Especially, how to control traffic signals at multiple intersections is a key challenge. To speed up urban traffic flow, this research presents a genetic timing scheduling model (GTSM) for urban traffic signal control. GTSM constructs cellular automata to update the timing cycles of traffic signals at multiple intersections, where state update functions are formulated to coordinate traffic signals. In addition, a proposed genetic optimization algo-rithm (GOA) in GTSM optimizes the timing cycles of traffic signals at multiple intersections in the dynamic timing optimization. The experimental results on urban road networks show that the performance of our model is excellent in various scenarios to control traffic signals to speed up urban traffic flow. (c) 2021 Published by Elsevier Inc.
引用
收藏
页码:475 / 483
页数:9
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