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 (4): 124-136.DOI: 10.16097/j.cnki.1009-6744.2026.04.011

• 智能交通系统与信息技术 • 上一篇    下一篇

网联车辆环境下干线信号与可变限速协同控制方法

岳睿*1，葛荣熙1，刘世杰2，杨广川3，林冬梅4，田宗忠5   

  1. 1. 北京交通大学，交通运输学院，北京 100044；2. 山东大学，齐鲁交通学院，济南 250061；3. 北卡罗来纳州立大学， 交通研究与教育研究所，罗利 27695，美国；4. 比佛顿市公共事务局，比佛顿 97005，美国； 5. 内华达大学里诺分校，土木环境系，里诺 89512，美国
  • 收稿日期:2026-04-30 修回日期:2026-06-01 接受日期:2026-07-01 出版日期:2026-08-25 发布日期:2026-08-21
  • 作者简介:岳睿（1992— ），男，河南禹州人，讲师，博士
  • 基金资助:
    国家自然科学基金 (52472311)

Cooperative Control Method for Arterial Signals and Variable Speed Limit Under Mixed Traffic Environment

YUE Rui*1, GE Rongxi1, LIU Shijie2, YANG Guangchuan3, LIN Dongmei4, TIAN Zongzhong5   

  1. 1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 2. School of Qilu Transportation, Shandong University, Jinan 250061, China; 3. Institute for Transportation Research and Education, North Carolina State University, Raleigh 27695, USA; 4. Public Works, City of Beaverton, Beaverton, OR 97005, USA; 5. Department of Civil and Environmental Engineering, University of Nevada, Reno, Reno 89512, USA
  • Received:2026-04-30 Revised:2026-06-01 Accepted:2026-07-01 Online:2026-08-25 Published:2026-08-21
  • Supported by:
    National Natural Science Foundation of China (52472311)

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摘要： 聚焦网联车辆混合交通流条件下干线多交叉口车辆呈队列到达引起的启停延误、排队溢出与通行效率下降问题，本文提出信号配时与可变限速双层协同控制方法。上层以滚动优化为核心，结合车道级排队状态和短时到达预测结果，生成动态相位、绿灯时长及车道级绿灯服务窗口，并通过绿灯早起与迟断实现实时修正；下层以车道级绿灯服务窗口为约束，根据受控CAV（Connected and Automated Vehicle）距停车线距离和目标绿灯窗口计算速度上限，引导车辆尽量在绿灯期间到达停车线，并结合速度边界、新增延误约束、限速保持与平滑处理以及跟驰风险检查，减少不必要的限速干预和速度波动。仿真结果表明，在中等交通需求条件下，协同控制相较固定配时方案可使平均延误降低约51.2%~65.8%，且延误改善随CAV渗透率提高更加明显。在高需求且CAV渗透率较高的情况下，车均停车次数降低约57%，表明所提方法能够有效抑制停走波动和进口道排队积聚。同时，中等需求下，车均燃油消耗相较固定配时方案降低约40.9%~48.6%。研究结果表明，所提协同控制方法能够在不同交通需求下改善通行效率、车辆运行平顺性和能耗水平。

关键词: 城市交通, 干线信号与可变限速协同控制, 双层分级控制, 网联车混合交通流, 滚动时域优化, 信 号配时, 可变限速

Abstract: This study addresses start-stop delay, queue spillback, and reduced traffic efficiency caused by platoon arrivals at multiple intersections along an arterial under mixed traffic flow with connected and automated vehicles (CAVs). A bi-level cooperative control method integrating signal timing and variable speed limit (VSL) control is proposed. At the upper level, a rolling optimization strategy is adopted. Lane-level queue states and short-term arrival predictions are used to generate dynamic phases, green durations, and lane-level green service windows, while real-time corrections are made through early green onset and delayed green termination. At the lower level, the lane-level green service windows are used as constraints. The speed limit for each controlled CAV is calculated according to its distance to the stop line and the target green window, so that vehicles are guided to arrive at the stop line during the green interval as much as possible. Speed boundaries, additional-delay constraints, speed-limit holding and smoothing, and car-following risk checks are further introduced to reduce unnecessary speed-limit interventions and speed fluctuations. Simulation results show that, under moderate traffic demand, the proposed cooperative control reduces average delay by approximately 51.2% to 65.8% compared with the fixed- time signal scheme, and the delay reduction becomes more significant as the CAV penetration rate increases. Under high demand with a high CAV penetration rate, the average number of stops per vehicle is reduced by about 57%, indicating that the proposed method can effectively suppress stop-and-go oscillations and approach queue accumulation. In addition, under moderate demand, average fuel consumption per vehicle is reduced by approximately 40.9% to 48.6% compared with the fixed-time scheme. The results indicate that the proposed cooperative control method can improve traffic efficiency and vehicle running smoothness while reducing energy consumption under different traffic demand levels.

Key words: urban transportation, cooperative control of arterial signals and variable speed limits, bi-level hierarchical control; mixed traffic flow with connected and automated vehicles, receding horizon optimization, signal timing, variable speed limit

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