网联自动驾驶环境下交叉口车道分配与车辆轨迹协同优化

doi:10.16097/j.cnki.1009-6744.2025.05.005

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (5): 59-71.DOI: 10.16097/j.cnki.1009-6744.2025.05.005

网联自动驾驶环境下交叉口车道分配与车辆轨迹协同优化

宋浪^1,2，胡晓伟^*1，俞山川²，安实¹

1. 哈尔滨工业大学，交通科学与工程学院，哈尔滨150090；2.招商局重庆交通科研设计院有限公司，重庆400067

收稿日期:2025-06-23 修回日期:2025-09-08 接受日期:2025-09-10 出版日期:2025-10-25 发布日期:2025-10-25
作者简介:宋浪(1996—)，男，贵州石阡人，高级工程师，博士。
基金资助:
国家自然科学基金(52272332)；重庆市建设科技计划项目(城科字2024第6-8号)。

Cooperative Optimization of Lane Allocation and Vehicle Trajectory at Intersections Under Connected-and-Automated-Vehicle Environment

SONG Lang^1,2, HU Xiaowei^*1, YU Shanchuan²,AN Shi¹

1. School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China; 2. China Merchants Chongqing Communication Research and Design Institute Co Ltd, Chongqing 400067, China

Received:2025-06-23 Revised:2025-09-08 Accepted:2025-09-10 Online:2025-10-25 Published:2025-10-25
Supported by:
National Natural Science Foundation of China (52272332)；Chongqing Construction Science and Technology Plan Project (城科字2024第6-8号)。

摘要/Abstract

摘要： 既有交叉口信号配时与网联自动驾驶车辆(Connected and Automated Vehicle,CAV)轨迹规划协同优化中，未考虑CAV环境下出口、左转、直行及右转车道数在运营期可灵活动态调整的优势。本文结合CAV技术特征，提出一套CAV环境下交叉口车道分配可动态调整的控制规则，称为灵活车道策略，与已有固定车道策略相比，实现了运营期交叉口各方向出口车道数和进口车道数（包括左转、直行和右转）的灵活调整。将车道分配和信号配时与CAV轨迹规划纳入到一个统一优化框架中，构建混合整数线性规划优化模型，同时，可根据各个方向车道分配情况自动生成可行的相位相序方案，并通过案例分析验证模型的有效性。研究结果表明：优化模型可根据各流向交通需求生成最优车道分配方案，尤其是当固定车道策略的车道分配与各流向交通组成不匹配时，灵活车道策略有助于提升交叉口通行效率；在低流量场景，灵活车道策略降低了4.08%的车均延误；在高流量场景，交叉口采用固定车道策略将处于过饱和状态，而灵活车道策略依然能满足通行需求。

关键词: 智能交通, 轨迹级交通控制, 混合整数线性规划, 信号交叉口, 车道控制, 网联自动驾驶车辆

Abstract: In the collaborative optimization of intersection signal timing and Connected and Automated Vehicle (CAV) trajectory planning, the CAV exit, left turn, through, and right turn lanes can be assigned dynamically in the operation period. Based on the characteristics of CAV technology, this paper proposes a set of dynamic control rules for lane assignment under CAV, named as "flexible lane strategy". Compared to the existing fixed lane strategy, the proposed strategy can adjust the number of exit lanes and entrance lanes (including left turn, through, right turn) for different directions of traffic flow during operation. Lane assignment, signal timing and CAV trajectory planning are incorporated into a unified optimization framework to build a mixed integer linear programming optimization model. Meanwhile, feasible phase and sequence schemes can be automatically generated according to lane assignment in each direction, and the effectiveness of the model is verified through a case study. The results show that the optimization model can generate the optimal lane assignment scheme according to the traffic demand of each flow direction, especially when the lane assignment of the fixed lane strategy does not match the traffic composition of each flow direction, the flexible lane strategy helps to improve the intersection traffic efficiency. In low flow scenario, the flexible Lane strategy reduces average vehicle delay by 4.08%. In high-traffic scenarios, the fixed lane strategy at the intersection will be in a supersaturated state, while the flexible lane strategy can still meet the demand.

Key words: intelligent transportation, trajectory-based traffic control, mixed integer linear programming, signalized intersection; lane-based control, connected and automated vehicle

中图分类号:

U491

宋浪, 胡晓伟, 俞山川, 安实. 网联自动驾驶环境下交叉口车道分配与车辆轨迹协同优化[J]. 交通运输系统工程与信息, 2025, 25(5): 59-71.

SONG Lang, HU Xiaowei, YU Shanchuan, AN Shi. Cooperative Optimization of Lane Allocation and Vehicle Trajectory at Intersections Under Connected-and-Automated-Vehicle Environment[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(5): 59-71.

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网联自动驾驶环境下交叉口车道分配与车辆轨迹协同优化

Cooperative Optimization of Lane Allocation and Vehicle Trajectory at Intersections Under Connected-and-Automated-Vehicle Environment

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