交通运输系统工程与信息

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (1): 76-85.DOI: 10.16097/j.cnki.1009-6744.2025.01.008

• 智能交通系统与信息技术 • 上一篇    下一篇

混合流环境下瓶颈区域车道定制化速度调控研究

曹丹妮1，王涛*2，杨松坡3，屈云超4，吴建军5   

  1. 1. 北京邮电大学，智能工程与自动化学院，北京100876；2.合肥工业大学，汽车与交通工程学院，合肥230009；3. 北京工业大学，交通工程北京市重点实验室，北京100124；4.北京交通大学，系统科学学院，北京100044；5. 大连理工大学，经济管理学院，辽宁大连116024
  • 收稿日期:2024-10-14 修回日期:2024-11-11 接受日期:2024-11-27 出版日期:2025-02-25 发布日期:2025-02-21
  • 作者简介:曹丹妮(1993—)，女，辽宁鞍山人，讲师，博士。
  • 基金资助:
    中央高校基本科研业务费专项资金(2023RC35)；国家自然科学基金(72301037)。

Lane-based Speed Regulation of Bottlenecks Under Mixed Flow Environment

CAO Danni1, WANG Tao*2,YANG Songpo3, QU Yunchao4, WU Jianjun5   

  1. 1. School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China; 2. School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009, China; 3. Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China; 4. School of Systems Science, Beijing Jiaotong University, Beijing 100044, China; 5. School of Economics and Management, Dalian University of Technology, Dalian 116024, Liaoning, China
  • Received:2024-10-14 Revised:2024-11-11 Accepted:2024-11-27 Online:2025-02-25 Published:2025-02-21
  • Supported by:
    Fundamental Research Funds for the Central Universities (2023RC35)；National Natural Science Foundation of China (72301037)。

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摘要： 为缓解异常事件发生后智能网联自动驾驶车辆和人工驾驶车辆在高速公路上的拥堵及二次事故问题，本文以单车道为研究对象，提出一种车道定制化速度调控方法。利用智能网联自动驾驶车的可控性，控制其通行速度，间接引导人工驾驶车的驾驶行为。划分瓶颈区域附近路段为限速区和协调区：在限速区，基于瓶颈处实时交通流量确定不同车道的智能网联自动驾驶车限速值，控制流入协调区的车辆数，缓解拥堵波的形成与传播；在协调区，控制事发路段的智能网联自动驾驶车移动，保证车辆安全和高效通过瓶颈区。构建多组仿真实验，从通行效率和安全性两方面验证所提方法的有效性。仿真结果表明：对比无控制的基本场景，智能网联自动驾驶车渗透率为50%时，车辆平均通行时间可提升2.4%，TET(Time Exposed Time-to-collision)改善率达到14%；渗透率达到90%时，平均通行时间可提升18.5%，TET改善率达到51%。本文为解决混合流环境下高速公路异常事件发生后交通流的控制提供了策略建议与思路方法。

关键词: 交通工程, 自动驾驶车辆管控, 微观交通流仿真, 混合交通流, 速度调控

Abstract: To address the congestion and secondary accidents on highways involving both Connected and Automated Vehicles and Human-driven Vehicles after abnormal incidents occur, this paper focuses on a single lane and proposes a lane-based speed regulation method. This study utilizes the controllability of Connected and Automated Vehicles by controlling the passing speed to indirectly guide the driving behavior of Human-driven Vehicles. The area near the bottleneck is divided into a speed limit area and a coordination area. In the speed limit area, the Connected and Automated Vehicles speed limit values for different lanes are determined based on real-time traffic flow at the bottleneck, and the number of vehicles flowing into the coordination area is controlled to alleviate the formation and propagation of congestion waves. In the coordination area, the Connected and Automated Vehicles movement on the incident lane is controlled to ensure that vehicles could pass through the bottleneck area safely and efficiently. A set of simulation experiments are conducted, and the effectiveness of the proposed method is verified from two aspects: efficiency and safety. The simulation results show that compared to an uncontrolled baseline scenario, the average traveling time of vehicles can be increased by 2.4% and the improvement rate of TET (Time Exposed time-to-collision) can reach 14% in a 50% Connected and Automated Vehicles market penetration rates environment. And in a 90% market penetration rates environment, the average travel time can be increased by 18.5%, and the TET improvement rate rises to 51%. This paper could provide strategic recommendations and methods to control the traffic flow when an incident happens under the mixed flow environment.

Key words: traffic engineering, CAV control measures, microscopic traffic simulation, mixed flow, speed regulation

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