交通运输系统工程与信息 ›› 2024, Vol. 24 ›› Issue (3): 12-20.DOI: 10.16097/j.cnki.1009-6744.2024.03.002

• 交通运输新技术 • 上一篇    下一篇

车联网下公交专用道复用的动态清空控制方法

董红召*,杨嘉炜,全程   

  1. 浙江工业大学,智能交通系统联合研究所,杭州 310014
  • 收稿日期:2024-03-30 修回日期:2024-04-25 接受日期:2024-05-11 出版日期:2024-06-25 发布日期:2024-06-23
  • 作者简介:董红召(1969- ),男,河南滑县人,教授,博士
  • 基金资助:
    浙江省“尖兵”“领雁”研发攻关计划项目 (2024C01180)

Dynamic Clearance Control Method for Reusing Bus Lanes Under Vehicular Networking

DONG Hongzhao*, YANG Jiawei, QUAN Cheng   

  1. Joint Institute of Intelligent Transportation System, Zhejiang University of Technology, Hangzhou 310014, China
  • Received:2024-03-30 Revised:2024-04-25 Accepted:2024-05-11 Online:2024-06-25 Published:2024-06-23
  • Supported by:
    'Pioneer' and 'Leading Goose' R&D Program of Zhejiang Province (2024C01180)

摘要:

传统公交专用道动态控制方法无法同时保证公交优先和车道利用率的提升,为解决该问题,本文提出车联网支持下公交专用道复用的动态清空控制方法(Dynamic Clearance Bus Lane,DCBL),建立随网联公交行驶车速和网联社会车辆换道时间动态变化的清空框模型,同时定义换道迫切系数,结合模糊控制理论,设计考虑驾驶员换道心理的换道概率输出算法,以模拟驾驶员实际换道过程,最后通过数值仿真以验证DCBL控制方法的有效性。仿真实验结果表明:DCBL控制方法将适用的交通密度范围扩大至 0~71 pcu · km- 1,比传统的BLIP(Bus Lane with Intermittent priority)、IBL(Intermittent Bus Lane)控制方法适用范围增加了9~21pcu·km-1;在40~70 pcu·km-1的中高交通密度区间,DCBL控制方法将社会车辆平均车速保持在45.86 km·h-1 ,比传统控制方法提高了17.9%~24.7%,将公交平均车速保持在33.68 km·h-1,对比公交期望车速仅降低了6.4%;DCBL控制方法在路段中高密度区间对公交车的行驶延误小于25 s,比传统控制方法提高路段通行能力8.0%~18.3%。

关键词: 智能交通, 公交专用道复用, 动态清空框, 换道概率, 车联网

Abstract: Traditional dynamic control methods for dedicated bus lanes can be improved to ensure both the bus priority and the lane utilization rates. To address this issue, this paper proposes a dynamic clearance control method for the reutilization of dedicated bus lanes with the support from vehicular networking, which is also referred to as Dynamic Clearance Bus Lane (DCBL). This method establishes a clearance framework model that dynamically adjusts the speed of connected buses and the lane-changing time of connected private vehicles. Additionally, it defines a lane change urgency coefficient and uses the fuzzy control theory to design a lane change probability output algorithm in consideration of drivers' lane-changing psychology to simulate the actual lane-changing process. The simulation analysis was conducted to verify the effectiveness of the DCBL control method. The results indicate that the DCBL control method expands the applicable range of traffic density to 0~71 pcu · km- 1 , an increase of 9~21 pcu · km- 1 compared to traditional BLIP(Bus Lane with Intermittent priority) and IBL(Intermittent Bus Lane) control methods. In the mid-to-high-density range of 40~70 pcu · km-1 , the DCBL control method maintains the average speed of private vehicles at 45.86 km·h-1 , an improvement of 17.9%~24.7% compared to traditional control methods. The average speed of buses is maintained at 33.68 km· h-1 , only decreasing by 6.4% compared to the expected speed of buses. The DCBL control method results in a bus travel delay of less than 25 seconds mid-to-high-density range, leading to an increase in roadway throughput by 8.0%~18.3% compared to traditional control methods.

Key words: intelligent transportation, bus lane reutilization, dynamic clearance framework, lane-changing probability; vehicular networking

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