|Table of Contents|

Traffic capacity enhancement strategy for urban expressway diversion area under vehicle-infrastructure cooperative environment(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2022年03期
Page:
126-138
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
Traffic capacity enhancement strategy for urban expressway diversion area under vehicle-infrastructure cooperative environment
Author(s):
LI Rui1 RAN Bin2 QU Xu2
(1. College of Civil and Transportation Engineering, Hohai University, Nanjing 210024, Jiangsu, China; 2. School of Transportation, Southeast University, Nanjing 211198, Jiangsu, China)
Keywords:
intelligent transportation system vehicle-infrastructure cooperative improved cellular automata model lane-changing influence analysis diversion area traffic capacity enhancement
PACS:
U491.112
DOI:
10.19818/j.cnki.1671-1637.2022.03.010
Abstract:
According to the mixed traffic flow characteristics of vehicles including different types of automatic vehicles(AVs)and human-driven vehicles(HVs)in the urban expressway diversion area under a vehicle-infrastructure cooperative environment, the dynamic acceleration and variable lane-changing probability were introduced to improve the traffic flow rules of a cellular automata model. The lane-changing simulation experiments in the diversion area were designed by considering the coupling influence of factors such as the penetration rate of AVs on the main road, proportion of large vehicles, penetration rate of off-ramp AVs, rate of off-ramp vehicles, number of off-ramp lanes, and distance before lane-changing. The influences of indicators including the free lane-changing rate and average distance before lane-changing of off-ramp vehicles were compared and analyzed under multi-factor coupling actions, and change rules of road capacity of the urban expressway diversion area were studied. On the basis of the variable distance before lane-changing, a strategy for improving the road capacity of the diversion area with mixed traffic flows was proposed. Analysis results show that the road capacity improves as the free lane-changing rate of off-ramp vehicles in the diversion area increases. The penetration rate of AVs on the main road has the most significant impact on the road capacity, and the road capacity under the environment with fully AVs is twice that under the environment with fully HVs. The impact of the number of off-ramp lanes on the road capacity is not significant, and the road capacity of two off-ramp lanes improves by about 3%, compared with that of one off-ramp lane. The distance before lane-changing greatly affects the road capacity, and the road capacity of the diversion area enhances by 9.6%-10.6% when the distance before lane-changing increases from 100 m to 150 m. Therefore, mobile traffic signs can be utilized to guide vehicles to change lanes in advance, which can significantly enhance the traffic capacity of the diversion area. 1 tab, 20 figs, 31 refs.

References:

[1] DAI Zhuang, LIU Xiao-yue, CHEN Xi, et al. Joint optimization of scheduling and capacity for mixed traffic with autonomous and human-driven buses: a dynamic programming approach[J]. Transportation Research Part C: Emerging Technologies, 2020, 114(5): 598-619.
[2] YE Lan-hang, YAMAMOTO T. Modeling connected and autonomous vehicles in heterogeneous traffic flow[J]. Physica A: Statistical Mechanics and Its Applications, 2018, 490(1): 269-277.
[3] 赵祥模,承靖钧,徐志刚,等.基于整车在环仿真的自动驾驶汽车室内快速测试平台[J].中国公路学报,2019,32(6):124-136.
ZHAO Xiang-mo, CHENG Jing-jun, XU Zhi-gang, et al. An indoor rapid-testing platform for autonomous vehicle based on vehicle-in-the-loop simulation[J]. China Journal of Highway and Transport, 2019, 32(6): 124-136.(in Chinese)
[4] 秦严严,张 健,陈凌志,等.手动-自动驾驶混合交通流元胞传输模型[J].交通运输工程学报,2020,20(2):229-238.
QIN Yan-yan, ZHANG Jian, CHEN Ling-zhi, et al. Cell transmission model of mixed traffic flow of manual-automated driving[J]. Journal of Traffic and Transportation Engineering, 2020, 20(2): 229-238.(in Chinese)
[5] MIRHELI A, HAJIBABAI L, HAJBABAIE A. Development of a signal-head-free intersection control logic in a fully connected and autonomous vehicle environment[J]. Transportation Research Part C: Emerging Technologies, 2018, 92(7): 412-425.
[6] XIAO Lin, WANG Meng, AREM B V. Traffic flow impacts of converting an HOV lane into a dedicated CACC lane on a freeway corridor[J]. IEEE Intelligent Transportation Systems Magazine, 2020, 12(1): 60-73.
[7] 姚 佼,倪屹聆,戴亚轩.车联网环境对城市快速路驾驶安全的影响评价[J].交通运输研究,2020,6(2):83-90.
YAO Jiao, NI Yi-ling, DAI Ya-xuan. Influence evaluation of internet of vehicles environment on driving safety of urban expressway[J]. Transport Research, 2020, 6(2): 83-90.(in Chinese)
[8] WU Wei, ZHANG Fang-ni, LIU Wei, et al. Modelling the traffic in a mixed network with autonomous-driving expressways andnon-autonomous local streets[J]. Transportation Research Part E: Logistics and Transportation Review, 2020, 134(2): 101855.
[9] WANG Yun-peng, WEI Lei, CHEN Peng. Trajectory reconstruction for freeway traffic mixed with human-driven vehicles and connected and automated vehicles[J]. Transportation Research Part C: Emerging Technologies, 2020, 111(2): 135-155.
[10] CHEN Jian-zhong, ZHOU Yang, LIANG Huan. Effects of ACC and CACC vehicles on traffic flow based on an improved variable time headway spacing strategy[J]. IET Intelligent Transport Systems, 2019, 13(9): 1365-1373.
[11] LI Lin-heng, GAN Jing, JI Xin-kai, et al. Dynamic driving risk potential field model under the connected and automated vehicles environment and its application in car-following modeling[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, DOI: 10.1109/TITS.2020.3008284.
[12] BEKIARIS-LIBERIS N, RONCOLI C, PAPAGEORGIOU M. Highway traffic state estimation per lane in the presence of connected vehicles[J]. Transportation Research Part B: Methodological, 2017, 106(12): 1-28.
[13] HU Xiang-wang, SUN Jian. Trajectory optimization of connected and autonomous vehicles at a multilane freeway merging area[J]. Transportation Research Part C: Emerging Technologies, 2019, 101: 111-125.
[14] ZHU Feng, UKKUSURI S V. An optimal estimation approach for the calibration of the car-following behavior of connected vehicles in a mixed traffic environment[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(2): 282-291.
[15] ZHAO Xiang-mo, WANG Zhen, XU Zhi-gang, et al. Field experiments on longitudinal characteristics of human driver behavior following an autonomous vehicle[J]. Transportation Research Part C: Emerging Technologies, 2020, 114(5): 205-224.
[16] SUN Jie, ZHENG Zu-duo, SUN Jian. Stability analysis methods and their applicability to car-following models in conventional and connected environments[J]. Transportation Research Part B: Methodological, 2018, 109(3): 212-237.
[17] ALI Y, ZHENG Zu-duo, HAQUE M M, et al. A game theory-based approach for modelling mandatory lane-changing behaviour in a connected environment[J]. Transportation Research Part C: Emerging Technologies, 2019, 106(9): 220-242.
[18] SHI Xiao-wei, LI Xiao-peng. Constructing a fundamental diagram for traffic flow with automated vehicles: methodology and demonstration[J]. Transportation Research Part B: Methodological, 2021, 150: 279-292.
[19] YANG Da, ZHENG Shi-yu, WEN Cheng, et al. A dynamic lane-changing trajectory planning model for automated vehicles[J]. Transportation Research Part C: Emerging Technologies, 2018, 95(10): 228-247.
[20] 张 毅,姚丹亚,李 力,等.智能车路协同系统关键技术与应用[J].交通运输系统工程与信息,2021,21(5):40-51.
ZHANG Yi, YAO Dan-ya, LI Li, et al.Technologies and applications for intelligent vehicle-infrastructure cooperation systems[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 40-51.(in Chinese)
[21] 徐志刚,李金龙,赵祥模,等.智能公路发展现状与关键技术[J].中国公路学报,2019,32(8):1-24.
XU Zhi-gang, LI Jin-long, ZHAO Xiang-mo, et al. A review on intelligent road and its related key technologies[J]. China Journal of Highway and Transport, 2019, 32(8): 1-24.(in Chinese)
[22] XIE Yuan-chang, ZHANG Hui-xing, GARTNER N H, et al. Collaborative merging strategy for freeway ramp operations in a connected and autonomous vehicles environment[J]. Journal of Intelligent Transportation Systems, 2017, 21(2): 136-147.
[23] LETTER C, ELEFTERIADOU L. Efficient control of fully automated connected vehicles at freeway merge segments[J]. Transportation Research Part C: Emerging Technologies, 2017, 80: 190-205.
[24] LIU Hao, KAN Xing-an, SHLADOVER S E, et al. Impact of cooperative adaptive cruise control on multilane freeway merge capacity[J]. Journal of Intelligent Transportation Systems, 2018, 22(3): 263-275.
[25] DONG Chang-yin, WANG Hao, LI Ye, et al.Route control strategies for autonomous vehicles exiting to off-ramps[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(7): 3104-3116.
[26] 杨 敏,王立超,张 健,等.面向智慧高速的合流区协作车辆冲突解脱协调方法[J].交通运输工程学报,2020,20(3):217-224.
YANG Min, WANG Li-chao, ZHANG Jian, et al. Collaborative method of vehicle conflict resolution in merging area for intelligent expressway[J]. Journal of Traffic and Transportation Engineering, 2020, 20(3): 217-224.(in Chinese)
[27] SUN Zhan-bo, HUANG Tian-yu, ZHANG Pei-tong. Cooperative decision-making for mixed traffic: a ramp merging example[J]. Transportation Research Part C: Emerging Technologies, 2020, 120: 102764.
[28] YANG Da, QIU Xiao-ping, MA Li-na, et al. Cellular automata-based modeling and simulation of a mixed traffic flow of manual and automated vehicles[J]. Transportation Research Record, 2017(2622): 105-116.
[29] LIU Mei-yu, SHI Jing. A cellular automata traffic flow model combined with a BP neural network based microscopic lane changing decision model[J]. Journal of Intelligent Transportation Systems, 2019, 23(4): 309-318.
[30] 余荣杰,田 野,孙 剑.高等级自动驾驶汽车虚拟测试:研究进展与前沿[J].中国公路学报,2020,33(11):125-138.
YU Rong-jie, TIAN Ye, SUN Jian. Highly automated vehicle virtual testing: a review of recent developments and research frontiers[J]. China Journal of Highway and Transport, 2020, 33(11): 125-138.(in Chinese)
[31] 宗 芳,王 猛,曾 梦,等.考虑多前车作用势的混行交通流车辆跟驰模型[J].交通运输工程学报,2022,22(1):250-262.
ZONG Fang, WANG Meng, ZENG Meng, et al. Vehicle-following model in mixed traffic flow considering interaction potential of multiple front vehicles[J]. Journal of Traffic and Transportation Engineering, 2022, 22(1): 250-262.(in Chinese)

Memo

Memo:
-
Last Update: 2022-07-20