考虑提升队列规模的智能网联车辆编队策略

doi:10.16097/j.cnki.1009-6744.2025.02.005

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (2): 48-57.DOI: 10.16097/j.cnki.1009-6744.2025.02.005

• 智能交通系统与信息技术 • 上一篇下一篇

考虑提升队列规模的智能网联车辆编队策略

孙煦^1,2，马天行^1,2，王天实^*3，王健宇^1,2，陆化普⁴

1. 北京建筑大学，土木与交通工程学院，北京102616；2.北京建筑大学，通用航空技术北京实验室，北京100044； 3. 中国国际可持续交通创新和知识中心，北京100736；4.清华大学，交通研究所，北京100084

收稿日期:2024-10-16 修回日期:2025-01-06 接受日期:2025-01-18 出版日期:2025-04-25 发布日期:2025-04-19
作者简介:孙煦(1987—)，女，安徽宣城人，副教授，博士。
基金资助:
北京市社会科学基金青年项目(20GLC048)。

Strategic Approaches for Optimizing Queue Size in Connected and Autonomous Vehicle Platooning

SUN Xu^1,2,MA Tianxing^1,2,WANG Tianshi^*3,WANG Jianyu1,2,LU Huapu⁴

1. School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 102616, China; 2. Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China; 3. Global Sustainable Transport Innovation and Knowledge Center, Beijing 100736, China; 4. Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China

Received:2024-10-16 Revised:2025-01-06 Accepted:2025-01-18 Online:2025-04-25 Published:2025-04-19
Supported by:
The Youth Project of Beijing Social Science Fund(20GLC048)。

摘要/Abstract

摘要： 为深入研究智能网联车辆(ConnectedandAutonomousVehicles, CAVs)队列规模对混合交通流的影响，本文以队列规模为划分依据，考虑队内间隙排序与队外相对位置，提出一种基于两阶段的智能网联车辆集聚编队策略。基于元胞自动机构建一种3车道的高速公路运行场景，考虑CAVs渗透率和队列最大规模等因素，对比分析无编队自由混行和基于两阶段的CAVs编队策略下交通流通行能力、密度和CAVs队列的换道次数、行驶速度和安全性等。结果表明：相比于无编队自由混行，基于两阶段的编队策略在不同CAVs渗透率场景中提高通行能力约16.78%；在中等CAVs渗透率场景，两阶段编队策略能显著提高安全性，风险碰撞时间累计降低45.45%；此外，该编队策略存在临界规模，一阶段最大编队规模为6veh，两阶段最大编队规模为14veh。

关键词: 智能交通, 编队策略, 元胞自动机, 智能网联车辆, 交通流, 队列规模

Abstract: This study aims to comprehensively explore the effect of queue size for effective mixed traffic flow in Connected and Autonomous Vehicles (CAVs). The study is segregated based on queue size, considering intra-platoon gap organization as well as inter-platoon relative positioning. A two-stage platooning strategy for CAVs is proposed and studied. A three-lane highway operation model is built based on cellular automata with parameters like CAV penetration rate and maximum queue size. The performance of the proposed strategy is compared with free-flow mixed traffic and another two-stage CAV platooning model. Comparison is made with respect to important traffic parameters like traffic flow capacity, density, lane changing frequency, driving speed, and CAVs' safety profile. The outcome demonstrates that, as compared with free-flow mixed traffic, two-stage platooning strategy increases traffic capacity around 16.78% in various CAV penetration rate conditions. In scenarios with moderate CAV penetration levels, the strategy contributes significantly in terms of safety, reducing cumulative collision risk time by 45.45%. Moreover, the platooning strategy demonstrates a critical scale where the optimal platoon size is limited to 6 vehicles at the one-stage and 14 vehicles at the two-stage.

Key words: intelligent transportation;platooning strategy;cellular automata modeling;connected and autonomous vehicles (CAVs);traffic flow, queue size

中图分类号:

U495

孙煦, 马天行, 王天实, 王健宇, 陆化普. 考虑提升队列规模的智能网联车辆编队策略[J]. 交通运输系统工程与信息, 2025, 25(2): 48-57.

SUN Xu, MA Tianxing, WANG Tianshi, WANG Jianyu, LU Huapu. Strategic Approaches for Optimizing Queue Size in Connected and Autonomous Vehicle Platooning[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(2): 48-57.

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考虑提升队列规模的智能网联车辆编队策略

Strategic Approaches for Optimizing Queue Size in Connected and Autonomous Vehicle Platooning

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