工业工程 ›› 2018, Vol. 21 ›› Issue (4): 8-14,33.doi: 10.3969/j.issn.1007-7375.2018.04.002

• 实践与应用 • 上一篇    下一篇

车路协同环境下自适应信号配时优化模型

姚志洪1,2, 蒋阳升1,2, 王逸1,2   

  1. 1. 西南交通大学 交通运输与物流学院, 四川 成都 610031;
    2. 西南交通大学 综合交通运输智能化国家地方联合工程实验室, 四川 成都 610031
  • 收稿日期:2017-12-30 出版日期:2018-08-30 发布日期:2018-08-27
  • 作者简介:姚志洪(1991-),男,安徽省人,博士研究生,主要研究方向为车联网与城市交通信号控制.
  • 基金资助:
    国家自然科学基金资助项目(51578465,71771190);重庆市应用开发计划重点资助项目(cstc2014yykfB30003);西南交通大学优秀博士学位论文培育资助项目(D-YB201708)

Adaptive Signal Control Optimization Model in Vehicle Infrastructure Integration Environment

YAO Zhihong1,2, JIANG Yangsheng1,2, WANG Yi1,2   

  1. 1. School of Transportation and Logistics Southwest Jiaotong University, Chengdu 610031, China;
    2. National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2017-12-30 Online:2018-08-30 Published:2018-08-27

摘要: 在车路协同环境下,车辆位置和速度等信息容易获得,为交通信号控制系统提供了新的数据源。针对现有信号控制系统鲁棒性差,不能适应交通流实时变化特征等问题,本文提出了一种车路协同环境下交叉口自适应实时控制优化模型。该模型以交叉口车均延误最小为优化目标,相位绿灯时长为约束条件,采用遗传算法对模型进行求解,实现了对交叉口信号配时方案的实时优化。最后,通过调查数据并设计仿真实验,证明了文中模型比感应控制效果更好,车辆平均延误减少了30%,同时能够保证交叉口各个转向的车均延误均衡。

关键词: 交通工程, 自适应信号控制, 遗传算法, 车路协同, 交叉口

Abstract: Information such as position and speed of vehicles is easily obtained in vehicle infrastructure integration (VⅡ) environment. This provides a new data resource for traffic signal control systems. As the traditional signal control system is in poor robustness and cannot be adapted to the real-time variable characteristics of traffic flow, an adaptive real-time signal control optimization model in VⅡ environment is proposed. To minimize the average delay and the constraint of green time length of each phases, a genetic algorithm is used to solve the model, real-time signal timing optimization is realized at the intersection of this model. Finally, through the survey data and simulation experiment, the result shows that the proposed model performance is better than actuated control, the average delay reduced by 30%. Also, the proposed model can balance the vehicle's delay of each direction.

Key words: traffic engineering, adaptive traffic signal control, genetic algorithm, vehicle infrastructure integration, intersection

中图分类号: