汽车工程 ›› 2024, Vol. 46 ›› Issue (12): 2267-2278.doi: 10.19562/j.chinasae.qcgc.2024.12.013

• • 上一篇    下一篇

交通信号与网联汽车速度协同优化方法研究

陈欣宇,陈健,钱立军(),王其东   

  1. 合肥工业大学汽车与交通工程学院,合肥 230009
  • 收稿日期:2024-05-20 修回日期:2024-06-19 出版日期:2024-12-25 发布日期:2024-12-20
  • 通讯作者: 钱立军 E-mail:qianlijun66@163.com
  • 基金资助:
    国家自然科学基金面上项目(51875149)

Research on Cooperative Optimization Method of Traffic Signal and Speed of Connected Vehicles

Xinyu Chen,Jian Chen,Lijun Qian(),Qidong Wang   

  1. Department of Automotive and Traffic Engineering,Hefei University of Technology,Hefei 230009
  • Received:2024-05-20 Revised:2024-06-19 Online:2024-12-25 Published:2024-12-20
  • Contact: Lijun Qian E-mail:qianlijun66@163.com

摘要:

为提高信号交叉口的通行效率和车辆的燃油经济性,本文提出了一种考虑驾驶员误差的交通信号与网联汽车速度协同优化方法。在交通层,将交通信号优化问题转化为寻找车辆通过交叉口的最优序列的排序问题,构建了交通信号优化的最优控制模型,提出了一种基于动态规划的交通信号优化算法;在车辆层,考虑驾驶员误差的影响,构建了车辆速度优化的最优控制模型,提出了一种基于快速随机模型预测控制的网联汽车速度优化算法。仿真和智能网联微缩车试验结果表明,本文提出的协同优化策略能够有效缓解交叉口车辆由于驾驶员误差导致的减速停车,进一步降低了车辆的行程时间、怠速时间和燃油消耗。

关键词: 智能交通, 信号交叉口, 协同控制, 驾驶员误差

Abstract:

In order to improve the traffic efficiency at the signalized intersections and the fuel economy of vehicles, a cooperative optimization method of traffic signals and speed of connected vehicles considering the human driver error is proposed in this paper. In the traffic layer, by transforming the traffic signal optimization problem into a sequencing problem to find the optimal sequence of vehicles passing through the intersections, the optimal control model for traffic signal optimization is constructed and a traffic signal optimization algorithm based on dynamic planning is proposed. In the vehicle layer, the optimal control model for vehicle speed optimization is constructed by considering the influence of driver error, and a speed optimization algorithm based on fast stochastic model predictive control for connected vehicles is proposed. The simulation and intelligent connected micro-vehicle test results show that the co-optimization strategy proposed in this paper can effectively alleviate the deceleration and stopping of vehicles at intersections due to driver errors, and further reduce the travel time, idling time and fuel consumption of vehicles.

Key words: intelligent transportation, signalized intersections, cooperative control, human driver error