信号交叉口人机混驾交通流速度控制策略建模

doi:10.16182/j.issn1004731x.joss.22-0307

摘要/Abstract

摘要：

为分析人机混驾交通流下网联自动驾驶车辆（connected and autonomous vehicles，CAV）速度控制策略对交通流运行特征的影响，构建了考虑驾驶员对行车信息获取不确定性的人工驾驶车辆交叉口通行决策模型。提出考虑前车速度影响的自动驾驶速度控制策略，构建信号交叉口连续型元胞自动机更新规则，通过引入不同CAV渗透率、道路饱和度、控制区长度参数，研究CAV速度控制策略对信号交叉口交通流运行特征的影响。结果表明：CAV能显著提高交叉口通行能力，且车流通过交叉口区域的延误显著降低；同时速度控制策略的实施效果还受控制区长度的影响，呈现出随着控制区长度的增加，车均延误逐渐降低并趋于稳定。

关键词: 智能交通, 速度控制, 元胞自动机, 混合交通流, 车联网, 信号交叉口

Abstract:

In order to analyze the influence of speed control strategy of autonomous vehicle on the operation characteristics of traffic flow, a deterministic decision-making model for intersections with artificially driven vehicles considering the driver's influence on the acquisition of driving information is constructed. An automatic driving speed control strategy considering the influence of the speed of preceding vehicle is proposed, and the continuous Cellular Automata update rules for signalized intersections are constructed respectively. By introducing the different penetration rates of automatic driving, road saturation and control area length parameters, the influence of CAV speed control strategy on the traffic flow characteristics of signalized intersections is studied. The results show that the autonomous vehicle can significantly improve the traffic capacity of intersection, and the delay of traffic flow through the intersection area is significantly reduced. The implementation effect of the speed control strategy is also affected by the length of control area, which shows that following the increase of length of control area, the average vehicle delay gradually decreases and stabilizes.

Key words: intelligent transportation, speed control, Cellular Automata, mixed traffic flow, Internet of Vehicles, signalized intersections

中图分类号:

TP391

张建旭, 胡帅, 金宏意. 信号交叉口人机混驾交通流速度控制策略建模[J]. 系统仿真学报, 2022, 34(8): 1697-1709.

Jianxu Zhang, Shuai Hu, Hongyi Jin. Modeling of Traffic Flow Velocity Control Strategy for Human-machine Mixed Driving at Signalized Intersections[J]. Journal of System Simulation, 2022, 34(8): 1697-1709.

图/表 12

图1

图2

图3

图4

图5

表1

不同道路饱和度下延误降低百分比 (%)

饱和度	$p c a v = 0.2$	$p c a v = 0.4$	$p c a v = 0.6$	$p c a v = 0.8$	$p c a v = 1.0$
20	-14.1	-18.9	-23.1	-35.7	-40.0
40	-10.0	-17.6	-21.0	-31.2	-38.7
60	-6.7	-17.5	-30.0	-33.5	-46.0
80	-10.2	-27.5	-39.0	-45.5	-53.7
100	-45.4	-61.3	-67.2	-72.6	-77.9

表1

图6

表2

pcav=1时不同道路饱和度下平均延误下降百分比

道路饱和度/%	$l k O$ /m	稳定后平均延误/s	无控制平均延误/s	延误下降比例/%
40	220	8.6	10.5	18.1
60	320	9.1	10.9	16.5
80	340	9.3	11.2	17.0
100	320	9.8	12	18.3

表2

表3

pcav=0.8时不同道路饱和度下平均延误下降百分比

道路饱和度/%	$l k O$ /m	稳定后平均延误/s	无控制平均延误/s	延误下降比例/%
40	240	9.3	11.2	17.0
60	280	10.2	11.4	10.5
80	320	10.8	12.9	16.3
100	340	11.7	13.7	14.6

表3

表4

pcav=0.6时不同道路饱和度下平均延误下降百分比

道路饱和度/%	$l k O$ /m	稳定后平均延误/s	无控制平均延误/s	延误下降比例/%
40	220	10.1	10.9	7.3
60	280	11.1	12.8	13.3
80	300	12.3	13.8	10.9
100	320	13.9	16.2	14.2

表4

表5

pcav=0.4时不同道路饱和度下平均延误下降百分比

道路饱和度/%	$l k O$ /m	稳定后平均延误/s	无控制平均延误/s	延误下降比例/%
40	240	10.8	12.1	10.7
60	260	12.1	13.9	12.9
80	320	14.0	15.6	10.3
100	360	17.0	19.4	12.4

表5

表6

pcav=0.2时不同道路饱和度下平均延误下降百分比

道路饱和度/%	$l k O$ /m	稳定后平均延误/s	无控制平均延误/s	延误下降比例/%
40	220	11.5	12.3	6.5
60	200	13.4	14.5	7.6
80	380	15.6	16.7	6.6
100	380	27	28.6	5.6

表6

参考文献 20

1	杨晓光, 赵靖, 马万经, 等. 信号控制交叉口通行能力计算方法研究综述[J]. 中国公路学报, 2014, 27(5): 148-157.
	Yang Xiaoguang, Zhao Jing, Ma Wanjing, et al. A Review of Research on the Calculation Method of Traffic Capacity of Signal-Controlled Intersections [J]. Journal of China Highway, 2014, 27(5): 148-157.
2	Sharma N, Kumar P P, Dhyani R, et al. Idling Fuel Consumption and Emissions of Air Pollutants at Selected Signalized Intersections in Delhi[J]. Journal of Cleaner Production (S0959-6526), 2019, 212: 8-21.
3	Asadi B, Vahidi A. Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time[J]. IEEE Transactions on Control Systems Technology (S1063-6536), 2011, 19(3): 707-714.
4	Ala M V, Yang H, Rakha H. Modeling Evaluation of Eco-Cooperative Adaptive Cruise Control in Vicinity of Signalized Intersections[J]. Transportation Research Record (S0361-1981), 2016, 2559: 108-119.
5	Yang H, Rakha H, Ala M V. Eco-Cooperative Adaptive Cruise Control at Signalized Intersections Considering Queue Effects[J]. IEEE Transactions on Intelligent Transportation Systems (S1524-9050), 2017, 18(6): 1575-1585.
6	刘欢, 杨雷, 邵社刚, 等. 车路协同环境下信号交叉口速度引导策略[J]. 重庆交通大学学报(自然科学版), 2019, 38(12): 8-17.
	Liu Huan, Yang Lei, Shao Shegang, et al. Speed Guidance Strategy of Signaled Intersections in Vehicle-Road Collaboration Environment [J]. Journal of Chongqing Jiaotong University (Natural Science Edition), 2019, 38(12): 8-17.
7	孟竹, 邱志军. 节能导向的信号交叉口生态驾驶策略研究[J]. 交通信息与安全, 2018, 36(2): 76-84, 92.
	Meng Zhu, Qiu Zhijun. Research on Eco-Driving Strategy of Energy-Saving Signalized Intersections [J]. Traffic Information and Safety, 2018, 36(2):76-84, 92.
8	刘显贵, 王晖年, 洪经纬, 等. 网联环境下信号交叉口车速控制策略及优化[J]. 交通运输系统工程与信息, 2021, 21(2): 82-90.
	Liu Xiangui, Wang Huinian, Hong Jingwei, et al. Speed Control Strategy and Optimization at Signalized Intersections in the Networked Environment [J].Transportation Systems Engineering and Information, 2021, 21(2): 82-90.
9	Yao Z, Xu T, Jiang Y, et al. Linear Stability Analysis of Heterogeneous Traffic Flow Considering Degradations of Connected Automated Vehicles and Reaction Time[J]. Physica A: Statistical Mechanics and Its Applications (S0378-4371), 2021, 561: 125218.
10	庞明宝, 夏泽民, 栾燕海. 城市快速路多匝道协调控制信号施加策略仿真[J]. 系统仿真学报, 2018, 30(8): 3050-3057.
	Pang Mingbao, Xia Zemin, Luan Yanhai. Simulation of Multi-ramp Coordinated Control Signal Application Strategy for Urban Expressways [J]. Journal of System Simulation, 2018, 30(8): 3050-3057.
11	马新露, 李贝, 许陈蕾. 信号倒计时影响下的进口道交通流分析与建模[J]. 交通运输系统工程与信息, 2017, 17(5): 36-44.
	Ma Xinlu, Li Bei, Xu Chenlei. Traffic Flow Analysis and Modeling of the Entrance Under the Influence of Signal Countdown [J]. Transportation System Engineering and Information, 2017, 17(5): 36-44.
12	李素兰, 张谢东, 施俊庆, 等. 基于机动车排放的交叉口信号控制仿真与分析[J]. 交通运输系统工程与信息, 2019, 19(4): 72-78.
	Li Sulan, Zhang Xiedong, Shi Junqing, et al. Simulation and Analysis of Intersection Signal Control Based on Motor Vehicle Emissions [J]. Transportation Systems Engineering and Information, 2019, 19(4): 72-78.
13	Du M, Liu J, Chen Q. Improving Traffic Efficiency During Yellow Lights Using Connected Vehicles[J]. Physica A: Statistical Mechanics and Its Applications (S0378-4371) , 2021, 578: 126108.
14	江泽浩, 杨晓光, 汪涛. 绿灯倒计时影响下机动车微观驾驶行为分析与决策建模[J]. 交通运输系统工程与信息, 2018, 18(2): 66-72.
	Jiang Zehao, Yang Xiaoguang, Wang Tao. Analysis and Decision Modeling of Motor Vehicle Microscopic Driving Behavior Under the Influence of Green Light Countdown [J]. Transportation Systems Engineering and Information, 2018, 18(2): 66-72.
15	Gipps P G. A Behavioural Car-Following Model for Computer Simulation[J]. Transportation Research Part B: Methodological(S0191-2615), 1981, 15(2): 105-111.
16	邱小平, 于丹, 孙若晓, 等. 基于安全距离的元胞自动机交通流模型研究[J]. 交通运输系统工程与信息, 2015, 15(2): 54-60.
	Qiu Xiaoping, Yu Dan, Sun Ruoxiao, et al. Research on Cellular Automata Traffic Flow Model Based on Safety Distance [J]. Transportation Systems Engineering and Information, 2015, 15(2): 54-60.
17	Ao Z, Jiang B, Shi P. Fault-Tolerant Control For a Class of Nonlinear Sampled-Data Systems Via a Euler Approximate Observer [J]. Automatica (S0005-1098), 2010, 46(11): 1852-1859.
18	Shladover S E, Su D Y, Lu X Y. Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow[J]. Transportation Research Record (S0361-1981), 2012, 2324(1): 63-70.
19	Shladover S E, Nowakowski C, Lu X Y, et al. Cooperative Adaptive Cruise Control: Definitions and Operating Concepts[J]. Transportation Research Record (S0361-1981), 2015, 2489(1): 145-152.
20	安实, 姚焓东, 姜慧夫, 等. 信号交叉口绿色驾驶车速控制方法[J]. 交通运输系统工程与信息, 2015, 15(5): 53-59.
	An Shi, Yao Handong, Jiang Huifu, et al. Speed Control Method for Green Driving at Signalized Intersections [J]. Transportation System Engineering and Information, 2015, 15(5): 53-59.

[1]	朱依婷, 闫云, 何兆成. 公交与社会车辆混合的中观交通建模与仿真[J]. 系统仿真学报, 2022, 34(9): 2019-2027.
[2]	程鹏, 张文柱, 谢书翰, 杨子轩. 基于移动边缘计算的车联网任务卸载研究与仿真[J]. 系统仿真学报, 2022, 34(6): 1304-1311.
[3]	蒋阳升, 王思琛, 高宽, 刘梦, 姚志洪. 混入智能网联车队的混合交通流元胞自动机模型[J]. 系统仿真学报, 2022, 34(5): 1025-1032.
[4]	潘红光, 高磊, 米文毓. 基于改进宏观交通流模型的MPC算法设计[J]. 系统仿真学报, 2021, 33(8): 1875-1881.
[5]	何兆成, 林炫华, 聂佩林, 张荣辉. 考虑展宽设计的中观交通仿真模型及其标定[J]. 系统仿真学报, 2021, 33(4): 781-791.
[6]	刘展宏, 杨秀建, 吴相稷, 黄震. 基于元胞自动机的雾天车辆跟驰建模与仿真[J]. 系统仿真学报, 2021, 33(10): 2399-2410.
[7]	刘宗杨, 周春辉, 赵俊男, 肖进丽, 甘浪雄. 基于元胞自动机的航道通过能力建模与仿真[J]. 系统仿真学报, 2021, 33(10): 2478-2487.
[8]	屈重君, 康泽禹, 程咏梅. 基于幂函数控制指令的垂直飞行仿真性能分析[J]. 系统仿真学报, 2020, 32(9): 1780-1786.
[9]	宋英华, 张宇, 霍非舟, 吕伟, 马亚萍. 考虑避让行为的人员疏散元胞自动机模型研究[J]. 系统仿真学报, 2020, 32(6): 975-981.
[10]	周国雄, 李彤, 陈爱斌, 何明芳. 森林灭火水源选址的建模与仿真[J]. 系统仿真学报, 2020, 32(4): 660-668.
[11]	邢志伟, 徐铭怡, 罗晓, 罗谦. 飞机滑行路径仿真与优化研究[J]. 系统仿真学报, 2020, 32(2): 323-331.
[12]	周晨静, 高亚聪, 荣建. 微观交通仿真模型参数标定方法改善研究[J]. 系统仿真学报, 2020, 32(11): 2112-2120.
[13]	柴琳果, 蔡伯根, 上官伟, 王剑, 陈俊杰. 基于间隙理论的智能车交叉口运行控制方法[J]. 系统仿真学报, 2019, 31(9): 1875-1882.
[14]	袁泉, 高岩, 裘晨璐. 基于人-机-环境因素的未来交通事故风险研究[J]. 系统仿真学报, 2019, 31(3): 566-574.
[15]	王玖玲, 吴韶波, 张媛利, 邱佳慧, 刘琪. 利用V2X增强GPS的协同车辆定位方法[J]. 系统仿真学报, 2019, 31(12): 2901-2906.