北京航空航天大学学报 ›› 2018, Vol. 44 ›› Issue (11): 2257-2266.doi: 10.13700/j.bh.1001-5965.2018.0110

• 论文 • 上一篇    下一篇

连续信号交叉口网联自动驾驶车速控制

鹿应荣1, 许晓彤1, 丁川1,2, 鲁光泉1   

  1. 1. 北京航空航天大学 交通科学与工程学院 车路协同与安全控制北京市重点实验室, 北京 100083;
    2. 清华大学 汽车安全与节能国家重点实验室, 北京 100084
  • 收稿日期:2018-03-05 修回日期:2018-04-20 出版日期:2018-11-20 发布日期:2018-11-27
  • 通讯作者: 丁川,E-mail:cding@buaa.edu.cn E-mail:cding@buaa.edu.cn
  • 作者简介:鹿应荣,女,博士,教授,硕士生导师。主要研究方向:智能交通;许晓彤,女,硕士研究生。主要研究方向:车联网交通系统;丁川,男,博士,副教授,硕士生导师。主要研究方向:交通行为建模与仿真;鲁光泉,男,博士,教授,硕士生导师。主要研究方向:车路协同与驾驶行为。
  • 基金资助:
    汽车安全与节能国家重点实验室开放基金(KF1805);国家自然科学基金(U1764265)

Connected autonomous vehicle speed control at successive signalized intersections

LU Yingrong1, XU Xiaotong1, DING Chuan1,2, LU Guangquan1   

  1. 1. Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, School of Transportation Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
    2. State Key Lab of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
  • Received:2018-03-05 Revised:2018-04-20 Online:2018-11-20 Published:2018-11-27
  • Supported by:
    Science Fund of State Key Laboratory of Automotive Safety and Energy (KF1805); National Natural Science Foundation of China (U1764265)

摘要: 为了提高车辆在城市道路上行驶时的燃油经济性,同时减少污染物的排放,针对车联网环境下自动驾驶车辆可以与路侧设施及区域中心控制系统实时信息交互的特征,提出了连续信号交叉口车速控制方法。当车辆距下游各信号交叉口的距离和下游交叉口信号相位及时长可以提前获取时,通过提出的自动驾驶车速控制模型计算出一个使车辆能够连续通过下游多个信号交叉口的恒定速度,同时为了保证驾驶舒适性,采用平滑的三角函数曲线表征加/减速过程中的速度变化,避免了车辆在交叉口处急刹车或急加速的情况。为验证车速控制方法的有效性,基于多智能体技术建立了车联网环境下连续信号交叉口车速控制仿真系统,模拟对比分析了有速度控制和无速度控制下车辆连续通过3个信号交叉口的燃油消耗量、CO2排放量以及行程时间。结果表明:在低密度车流下,运用该车速控制方法,车辆连续通过3个信号交叉口的平均燃油消耗量与CO2排放量均减少了30%以上,行程时间减少了约5%;在中、高密度车流下,车辆的平均燃油消耗量与CO2排放量减少了约20%,并能够节省约15%的行程时间。另外,通过与目前已有的针对单点信号交叉口的车速控制模型的比较,本文提出的连续信号交叉口车速控制模型在节能减排方面更具优势。

关键词: 智能交通, 车速控制, 多智能体仿真, 连续信号交叉口, 车联网

Abstract: In order to improve fuel economy and reduce emissions on the urban road, a speed control method in successive signalized intersections was proposed for autonomous vehicles to interact with the roadside facilities and the regional center control system under the connected vehicles environment. The proposed automatic driving speed control model computes a constant speed that a vehicle can pass multiple downstream signalized intersections based on the information obtained in advance such as the distance between the vehicle and downstream signal intersections and the signal phasing and timing information. Meanwhile, in order to guarantee driving comfort and avoid sharp acceleration/deceleration at the intersection, we use the smooth curve of trigonometric function to represent the change of speed during the acceleration or deceleration process. To verify the efficiency of the speed control algorithm, the speed control simulation system embodying the cha-racteristics of the connected vehicles environment in successive signalized intersections is developed using the multi-agent technology, in which the fuel consumption, CO2 emissions and travel time under the speed control algorithm are compared with those without speed control algorithm when vehicles pass three signalized intersections. The results show that when vehicles go through the three successive intersections under low traffic density, the average fuel consumption and CO2 emissions are reduced by more than 30% by the aid of the speed control algorithm, and the travel time is reduced by about 5%; the fuel consumption and CO2 emissions can be reduced by approximately 20%, and the travel time is reduced by about 15% under the medium and high traffic density. In addition, compared with the current speed control model for the isolated signalized intersection, the proposed speed control model in successive signalized intersections has some advantages in energy saving and emission reduction.

Key words: intelligent transportation, speed control, multi-agent simulation, successive signalized intersections, connected vehicle

中图分类号: 


版权所有 © 《北京航空航天大学学报》编辑部
通讯地址:北京市海淀区学院路37号 北京航空航天大学学报编辑部 邮编:100191 E-mail:jbuaa@buaa.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发