Multi-objective arterial coordination control method based on induction control and vehicle speed guidance

被引:0
|
作者
Deng, Mingjun [1 ,4 ]
Li, Pengyi [1 ]
Hu, Xinxia [2 ]
Xu, Liping [3 ]
机构
[1] East China Jiaotong Univ, Sch Transportat Engn, Nanchang, Jiangxi, Peoples R China
[2] Zhejiang Haining Rail Transit Operat Management Co, Jiaxing, Zhejiang, Peoples R China
[3] Shanghai Pudong Architectural Design & Res Inst Co, Shanghai, Peoples R China
[4] East China Jiaotong Univ, Sch Transportat Engn, 808,Shuanggang East Rd,Nanchang Econ & Technol Dev, Nanchang 330013, Jiangxi, Peoples R China
来源
关键词
Traffic engineering; speed guidance; multi-objective optimization; signal intersections; arterial signal coordination; MODEL;
D O I
10.1177/00202940241233504
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The fixed green wave speed and staged statistical flow used in arterial signal coordination are not adaptable to the fluctuations in vehicle travel speed and traffic flow on roads, resulting in a mismatch between the signal scheme and the optimal green wave speed and traffic flow demand. This discrepancy negatively impacts the efficiency of intersection traffic. In traditional signal control systems, the cycle and green light timing are typically set independently. However, such a setting method poses problems in practical operation. In this paper, we combine vehicle arrival and vehicle location information, and consider the interaction of speed guidance and dynamic signal optimization to construct a model. This study is developed along the following steps: in the vehicle-road coordination environment, based on the MAXBAND model, a global coordination scheme is obtained, incorporating the speed guidance method; then, based on the vehicle saturation of the inlet lane of the arterial intersection, a multi-objective optimization model for arterial signal coordination under vehicle speed guidance is established based on global coordination with the maximum green wave bandwidth and the minimum delay of arterial vehicles, the minimum number of arterial stops and the minimum delay in the minor direction road as the optimization objectives. Based on global coordination, adopting an integrated control mechanism of cycle and green light timing allows for dynamic adjustments according to real-time traffic conditions. The improved multi-objective particle swarm algorithm is chosen to solve the model, and the simulation environment is built based on the COM interface of VISSIM software and C# platform. Three adjacent intersections of Ganjiang Middle Road in Nanchang are selected as case studies, and the methods in this paper are compared with the current timing scheme, the MAXBAND method and the optimization scheme under speed guidance only, respectively. The results show that the model proposed in this paper achieves significant optimization effects on the indicators of arterial delay, arterial stopping times and the delay of minor roads.
引用
收藏
页数:16
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