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
1 王殿海, 金盛, 马东方, 等. 城市交通控制理论与方法[M]. 北京: 电子工业出版社, 2019.
2 曹阳. 基于模拟退火的交叉口自适应信号控制优化研究[J]. 交通运输工程与信息学报, 2018, 16(1): 49-55, 60.
Cao Yang. Optimization of adaptive signal control using simulated annealing algorithm[J]. Journal of Transportation Engineering and Information, 2018, 16(1): 49-55, 60.
3 李祥尘, 李进龙, 何梦辰. 基于相位优化的干线双向绿波协调控制方法[J]. 交通运输工程与信息学报, 2018, 16(1): 115-121.
Li Xiang-chen, Li Jin-long, He Meng-chen. A phase optimization based two-way green wave control strategy for urban arterials[J]. Journal of Transportation Engineering and Information, 2018, 16(1): 115-121.
4 Miller A J. A computer control system for traffic network[C]∥Proc of the 2nd International Symposium on Theory of Road Traffic Flow, London, UK,1963:201-220.
5 Gartner N H. OPAC: a demand-responsive strategy for traffic signal control[J]. Transportation Research Record, 1983, 906: 75-84.
6 Vincent R A, Young C P. Self-optimizing traffic signal control using microprocessors—the TRRL' Mova' strategy for isolated intersections[J]. Traffic Engineering& Control, 1986, 27(7/8): 385-387.
7 Crabtree M R, Henderson I R. MOVA traffic control manual application guide [M]. Hongkong: TRI Limited, 2005.
8 徐洪峰, 柳爽, 张栋, 等. 单点全感应式信号控制方法的参数取值[J]. 吉林大学学报: 工学版, 2019, 49(1): 45-52.
Xu Hong-feng, Liu Shuang, Zhang Dong, et al. Configuring parameters of fully actuated control at isolated signalized intersections[J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(1): 45-52.
9 徐洪峰, 耿现彩. 面向Ｔ形交叉口的机动车相位固定最小绿灯时间计算[J]. 吉林大学学报: 工学版, 2011, 42(3): 600-605.
Xu Hong-feng, Geng Xian-cai. Absolute minimum green time calculation for vehicles at 3-leg intersection[J]. Journal of Jilin University (Engineering and Technology Edition), 2011, 42(3): 600-605.
10 Wang X B, Yin K, Liu H. Vehicle actuated signal performance under general traffic at an isolated intersection[J]. Transportation Research Part C: Emerging Technologies, 2018, 95: 582-598.
11 罗小芹, 王殿海, 金盛. 面向混合交通的感应式交通信号控制方法[J]. 吉林大学学报: 工学版, 2019, 49(3): 695-704.
Luo Xiao-qin, Wang Dian-hai, Jin Sheng. Traffic signal actuated control at isolated intersections for heterogeneous traffic[J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(3): 695-704.
12 Feng Y H, Head K L, Khoshmagham S, et al. A real-time adaptive signal control in a connected vehicle environment[J]. Transportation Research Part C: Emerging Technologies, 2015, 55: 460-473.
13 Guo Q, Li L, Ban X. Urban traffic signal control with connected and automated vehicles: a survey[J]. Transportation Research Part C: Emerging Technologies, 2019, 101: 313-334.
14 Kamal M, Hayakawa T, Imura J. Development and evaluation of an adaptive traffic signal control scheme under a mixed-automated traffic scenario[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(2): 590-602.
15 Feng Y, Zheng J, Liu H. Real-time detector-free adaptive signal control with low penetration of connected vehicles[J]. Transportation Research Record: Journal of the Transportation Research Board, 2018, 2672(18): 35-44.
16 Yao Z H, Jiang Y S, Zhao B, et al. A dynamic optimization method for adaptive signal control in a connected vehicle environment[J]. Journal of Intelligent Transportation Systems, 2019, 24(2): 184-200.
17 Li L, Lv Y, Wang F Y, Traffic signal timing via deep reinforcement learning[J]. Traffic Signal Timing Via Deep Reinforcement Learning, 2016, 3(3): 247-254.
18 孙浩, 陈春林, 刘琼, 等. 基于深度强化学习的交通信号控制方法[J]. 计算机科学, 2020, 47(2): 169-174.
Sun Hao, Chen Chun-lin, Liu Qiong, et al. Traffic signal control method based on deep reinforcement learning[J]. Computer Science, 2020, 47(2): 169-174.
19 Chu T S, Wang J, Codeca L, et al. Multi-agent deep reinforcement learning for large-scale traffic signal control[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 21(3): 1-10.
20 Tan K L, Poddar S, Sarkar S, et al. Deep reinforcement learning for adaptive traffic signal control[C]∥ ASME Dyn Syst Control Conf, Columbus,USA,2019.
21 Genders W, Razavi S. Asynchronous N-step Q-learning adaptive traffic signal control[J]. Journal of Intelligent Transportation Systems, 2019, 23(4): 319-331.
22 唐杰祯. 基于广域雷达的单点信号控制配时优化研究[D]. 南京:东南大学交通学院, 2019.
Tang Jie-zhen. Research on timing optimization of single-point signal control based on wide area radar[D]. Nanjing: College of Transportation,Southeast University, 2019.
23 安娜. 基于多目标跟踪雷达的单点全感应式信号控制方法[D]. 大连:大连理工大学交通运输学院, 2020.
An Na. Fully-actuated signal control at isolated intersections based on multi-target tracking radar[D]. Dalian: School of Transportation, Dalian University of Technology, 2020.
24 别一鸣, 姜凯, 汤茹茹, 等. 考虑方案过渡影响的单点交通控制时段划分方法[J]. 吉林大学学报:工学版, 2019, 49(6): 1844-1851.
Bie Yi-ming, Jiang Kai, Tang Ru-ru, et al. Time of interval partition for traffic control at isolated intersection considering impacts of plan transition[J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(6): 1844-1851.
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