Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (10): 2456-2465.doi: 10.13229/j.cnki.jdxbgxb20210313

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Traffic signal control method at isolated intersections based on multi-target radar data

Dong-bo LIU1,2(),Li-xiao SHEN3,Lei-lei DAI2(),Jian LU1   

  1. 1.School of Transportation，Southeast University，Nanjing 211189，China
    2.Traffic Management Research Institute of the Ministry of Public Security，Wuxi 214151，China
    3.Zhejiang Urban and Rural Planning Design Institute，Hangzhou 310027，China
  • Received:2021-03-05 Online:2022-10-01 Published:2022-11-11
  • Contact: Lei-lei DAI E-mail:dbliu@vip.sina.com;alei_9935@126.com

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Abstract:

Aiming at the characteristics that the multi-target radar detectors can obtain the regional traffic performance， a signal control method at isolated intersections was r proposed based on multi-target radar data. First， according to the queue length of the detection area at the approach， a signal control strategy at isolated intersections is designed， and the signal control method is divided into two stages. Secondly， the signal control methods of the two stages are determined respectively. The first stage mainly solves the problem of conventional vehicle release， and establishes the signal phase transfer rule. The second stage mainly solves the problem of excessively long queues of vehicles at the approach and overflow of queues at the exit. The corresponding control logic rules are established. On this basis， the value and optimization method of related control parameters are determined. Finally， the actual typical intersection is taken as an example to simulate and verify the proposed signal control method. The results show that the proposed signal control method in this paper can effectively improve the operation efficiency of the intersection， the average vehicle delay is reduced by 9%， and the vehicle queue length under high traffic demand is reduced by 15.5%.

Key words: traffic information engineering and control, multi-target radar, traffic signal control, traffic simulation

CLC Number: 

  • U491

Fig.1

Traffic signal control idea map"

Fig.2

Diagram of assessment area division"

Table 1

Weight determination method"

车道数n123≥4
权重系数ξp10.90.80.7

Fig.3

Flow chart of the first control stage"

Fig.4

Flow chart of the second control stage"

Fig.5

Diagram of test intersection"

Table 2

Signal timing parameters setting"

信号参数取值
α/（veh·km-1）70
β/（veh·km-1）40 veh/km
ξp0.7
Δt/s1
P1/P5（东西直行）最小绿/s20
最大绿/s45
P2/P6（东西左转）最小绿/s10
最大绿/s30
P3/P7（南北直行）最小绿/s20
最大绿/s40
P4/P8（南北左转）最小绿/s10
最大绿/s30

Table 3

Green interval time matrix"

P1P2P3P4P5P6P7P8
P124106
P231045
P324345
P444204
P504340
P614300
P762263
P800553

Table 4

Simulation model parameter setting"

参 数取 值
车辆组成类型95% Car，5% Bus
驾驶行为模型Wiedemann 74
驾驶期望车速50（45~55）km/h
仿真运行时段0~11400 sim.sec
数据采样时段600~11400 sim.sec
数据采样间隔300 sim.sec
仿真运行步长5 time steps/sim.sec

Fig.6

Delays under different traffic demand"

Fig.7

Comparison of average vehicle delays at intersections"

Table 5

Hypothesis test of signal control performance"

项 目均值标准差延误降低P值显著性
低需求新方法27.944.128.69%0.000显著
老方法30.604.35
中需求新方法41.276.329.73%0.002显著
老方法45.726.91
高需求新方法69.5111.818.82%0.000显著
老方法76.2312.04

Table 6

Queue length comparison"

项 目平均排队长度/m排队减少
低需求新方法31.343.33%
老方法32.42
中需求新方法53.2110.47%
老方法59.43
高需求新方法73.3215.54%
老方法86.81
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