交通运输系统工程与信息

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (3): 226-234.DOI: 10.16097/j.cnki.1009-6744.2026.03.021

• 智能交通系统与信息技术 • 上一篇    下一篇

智能网联汽车复用公交车道协同控制研究

张建华* ，公佳豪，张文会   

  1. 东北林业大学，土木与交通学院，哈尔滨150040
  • 收稿日期:2025-12-16 修回日期:2026-03-01 接受日期:2026-03-06 出版日期:2026-06-25 发布日期:2026-06-23
  • 作者简介:张建华（1973—），男，黑龙江牡丹江人，副教授，博士。
  • 基金资助:
    国家自然科学基金(52572369)。

Cooperative Control for Reuse of Bus Lanes by Connected and Automated Vehicles

ZHANG Jianhua*, GONG Jiahao, ZHANG Wenhui   

  1. School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China
  • Received:2025-12-16 Revised:2026-03-01 Accepted:2026-03-06 Online:2026-06-25 Published:2026-06-23
  • Supported by:
    National Natural Science Foundation of China(52572369)。

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摘要： 为最大化利用整个路网的车道资源，本文提出在保证公交优先前提下CAV（Connectedand Automated Vehicles）借用公交专用道控制策略。首先，通过分析港湾式公交站点的特点，构建公交车动态清空距离模型，并分别制定普通路段与港湾路段情况下CAV借用公交车道的控制规则。其次，由于CAV强制还道时易受邻道交通状态影响，本文提出一种CAV还道协同管控策略，即引入邻道临界密度对CAV强制换道行为进行管控，并根据邻道前后车间距的大小划分为不同场景，通过制定CAV协同换道规则来保证公交车的优先权。通过SUMO仿真平台分别对多种策略搭建仿真场景并进行验证。结果表明：与禁止CAV使用公交车道的策略相比，社会车辆车均出行时间降低5.4%，联合专用道速度提高21.21%，且在高流量下CAV与HDV（Human-driven Vehicles）的平均速度分别提高13.14%和9.63%，而公交车的平均速度仅降低0.99%；与允许CAV借用公交车道但不考虑公交优先的策略相比，本策略中虽然社会车辆车均出行时间增加1.9%，但公交车平均速度最高提高5.91%。以上证明，本策略可在不影响公交车优先权的情况下提升路网的通行效率。

关键词: 智能交通, 公交专用道复用, 公交优先, CAV控制方法, 车联网

Abstract: To maximize the utilization of lane resources across the entire road network, a control strategy for Connected and Automated Vehicles (CAV) is proposed through borrowing dedicated bus lanes, under the premise of guaranteeing bus priority. First, by analyzing the characteristics of bay-style bus stops, a dynamic clearance distance model for buses is constructed, and the control rules for CAVs borrowing bus lanes are formulated for normal road sections and bus bay sections, respectively. Second, considering that the mandatory lane-returning of CAVs is susceptible to the traffic status of adjacent lanes, a cooperative control strategy for CAV lane-returning is proposed. Specifically, the critical density of adjacent lanes is introduced to regulate the mandatory lane-changing behavior of CAVs. The scenarios are classified based on the gap between the leading and following vehicles in an adjacent lane, and cooperative lane-changing rules for CAVs are formulated to ensure the priority buses. The simulation scenarios for various strategies are constructed and verified by using the SUMO simulation platform. The results indicate that: (1) Compared with the strategy prohibiting CAVs from using bus lanes, the average travel time of social vehicles is reduced by 5.4%, and the speed of joint dedicated lanes is increased by 21.21%. Moreover, under high traffic flow, the average speeds of CAVs and Human-driven Vehicles are increased by 13.14% and 9.63%, respectively, while the average speed of buses is reduced by only 0.99%. (2) Compared with the strategy that allows CAVs to borrow bus lanes without considering the bus priority, the proposed strategy increased the average travel time of social vehicles by 1.9%, and the average speed of buses by up to 5.91% respectively. The above results demonstrate that the proposed strategy can improve the traffic efficiency of road networks without compromising bus priority.

Key words: intelligent transportation, bus lane reutilization, bus priority, CAV control method, vehicular networking

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