自动驾驶车辆渗透环境下多车道瓶颈路段行驶策略仿真

doi:10.16097/j.cnki.1009-6744.2025.02.007

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (2): 69-81.DOI: 10.16097/j.cnki.1009-6744.2025.02.007

• 智能交通系统与信息技术 • 上一篇下一篇

自动驾驶车辆渗透环境下多车道瓶颈路段行驶策略仿真

张建旭^*，吴春箱

重庆交通大学，交通运输学院，重庆400074

收稿日期:2024-10-27 修回日期:2025-01-19 接受日期:2025-02-14 出版日期:2025-04-25 发布日期:2025-04-19
作者简介:张建旭(1979—)，男，河南人，副教授，博士。
基金资助:
国家自然科学基金 (52302431)；重庆市高校创新研究群体项目 (CXQT21022)。

Simulation of Driving Strategies for Multi-lane Bottleneck Road Sections in An Environment with Autonomous Vehicles Penetration

ZHANG Jianxu^*,WU Chunxiang

School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China

Received:2024-10-27 Revised:2025-01-19 Accepted:2025-02-14 Online:2025-04-25 Published:2025-04-19
Supported by:
National Natural Science Foundation of China (52302431)；Program for Innovation Team at Institutions of Higher Education in Chongqing (CXQT21022)。

摘要/Abstract

摘要： 为探索多车道临时瓶颈路段在智能网联自动驾驶车辆(CAV)渗透环境下的通行效率和交通特性，本文基于连续元胞自动机模型设计了适用于人工驾驶车辆(HV)和CAV的跟驰及换道规则；考虑HV慢启动建立了跟驰模型，基于HV换道动机建了自由换道、倾向换道和强制换道规则；针对CAV设计了促成车队的主动换道(ALC-FP)策略，中间车道CAV可向外侧车道协同换道，一方面为内侧车道运行车辆提供换道空间，另一方面促成外侧车道形成CAV车队。为验证该策略在临时瓶颈场景下对交通流的影响，设置无策略对照实验，分析不同CAV渗透率和流量水平下瓶颈路段的交通效率。仿真结果表明：与无策略相比，ALC-FP策略减少HV和CAV强制性换道分别可达75%和94.45%；CAV车队强度最大可提升50%，促成了CAV形成车队通过瓶颈路段；车辆通过瓶颈点的平均速度提升可达1倍，车辆平均延误降低明显，最高可达88.6%。

关键词: 智能交通, 协同换道, 元胞自动机模型, 混合交通流, CAV车队强度

Abstract: To explore the traffic efficiency and characteristics of multi-lane temporary bottleneck sections in a mixed intelligent connected autonomous vehicle (CAV) penetration environment, this paper designs car-following and lane-changing rules tailored to human-driven vehicles (HV) and CAV based on the continuous cellular automaton model. A car-following model was established based on HV slow start, and a lane-changing model was established considering lane-changing motivation, which can be divided into free lane-changing, inclined lane-changing, and mandatory lane-changing. For CAVs, an active lane-changing with facilitating platoon has been designed. The CAVs in middle lane can cooperate with those in the outer lane for lane-changing, providing lane-changing space for vehicles operating in the inner lane and facilitating the formation of CAV platoons in the outer lane. To verify the impact of this strategy on traffic flow in temporary bottleneck scenarios, a strategy without control experiment was set up to analyze the traffic efficiency of bottleneck sections under different CAV penetration rates and flow levels. The simulation results showed that, compared without strategy, ALC-FP strategy has reduces HV and CAV mandatory lane changing by 75% and 94.45%, respectively; The maximum increase in CAV platoon intensity is 50%, which facilitates the formation of CAV platoons passing through bottleneck sections; The average speed of vehicles passing through bottleneck can be doubled, the average delay of vehicles can be significantly reduced by up to 88.6%.

Key words: intelligent transportation, collaborative lane changing, cellular automata model, mixed traffic flow, CAV platoon intensity

中图分类号:

U491

张建旭, 吴春箱. 自动驾驶车辆渗透环境下多车道瓶颈路段行驶策略仿真[J]. 交通运输系统工程与信息, 2025, 25(2): 69-81.

ZHANGJianxu, WU Chunxiang. Simulation of Driving Strategies for Multi-lane Bottleneck Road Sections in An Environment with Autonomous Vehicles Penetration[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(2): 69-81.

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自动驾驶车辆渗透环境下多车道瓶颈路段行驶策略仿真

Simulation of Driving Strategies for Multi-lane Bottleneck Road Sections in An Environment with Autonomous Vehicles Penetration

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