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网联通信时延下的混合队列控制特性分析

许庆 王嘉伟 王建强 李克强 高博麟

许庆, 王嘉伟, 王建强, 李克强, 高博麟. 网联通信时延下的混合队列控制特性分析[J]. 交通信息与安全, 2021, 39(1): 128-136. doi: 10.3963/j.jssn.1674-4861.2021.01.015
引用本文: 许庆, 王嘉伟, 王建强, 李克强, 高博麟. 网联通信时延下的混合队列控制特性分析[J]. 交通信息与安全, 2021, 39(1): 128-136. doi: 10.3963/j.jssn.1674-4861.2021.01.015
XU Qing, WANG Jiawei, WANG Jianqiang, LI Keqiang, GAO Bolin. A Performance Analysis of Mixed Platoon Control under Communication Delay[J]. Journal of Transport Information and Safety, 2021, 39(1): 128-136. doi: 10.3963/j.jssn.1674-4861.2021.01.015
Citation: XU Qing, WANG Jiawei, WANG Jianqiang, LI Keqiang, GAO Bolin. A Performance Analysis of Mixed Platoon Control under Communication Delay[J]. Journal of Transport Information and Safety, 2021, 39(1): 128-136. doi: 10.3963/j.jssn.1674-4861.2021.01.015

网联通信时延下的混合队列控制特性分析

doi: 10.3963/j.jssn.1674-4861.2021.01.015
基金项目: 

国家自然科学基金面上基金项目 52072212

广东省重点领域研发计划项目 2019B090912001

详细信息
    作者简介:

    许庆(1984—),博士,助理研究员.研究方向:网联车辆控制、车辆动力学. Email: qingxu@tsinghua.edu.cn

    通讯作者:

    李克强(1963—),博士,教授.研究方向:系统动态设计与控制、智能网联云控系统. Email: likq@tsinghua.edu.cn

  • 中图分类号: U491

A Performance Analysis of Mixed Platoon Control under Communication Delay

  • 摘要: 针对CACC协同自适应巡航控制技术,探究其在车联网通信时延影响下,与驾驶员驾驶汽车共存而构成的混合队列系统的性能。从微观跟车行为角度,基于频域传递函数,推导通信时延下的CACC队列稳定最小跟车时距的理论表达式,并通过数值验证指出CACC队列稳定最小跟车时距随通信时延增大而增大的特性。从交通激波特性角度,针对无时延CACC、有时延CACC和时延过大而退化后的ACC自适应巡航3种情形,给定相同的跟车时距,进行不同渗透率下的大规模交通仿真实验,实验结果表明,在无时延和1 s时延这2种情形下,CACC在20%及以上的渗透率时均能显著降低交通扰动,削弱激波,性能差别不明显; 相比而言,退化后的ACC性能明显恶化。

     

  • 图  1  协同自适应巡航控制系统(CACC)

    Figure  1.  Cooperative adaptive cruise control(CACC)

    图  2  不同通信时延下的队列稳定最小跟车时距

    Figure  2.  Minimum time headway for string stability at different communication delays

    图  3  仿真场景布置示意图

    Figure  3.  Simulation scenario

    图  4  所有车辆均为驾驶员驾驶汽车下的车辆轨迹图

    Figure  4.  Vehicle trajectories when all the vehicles are human-driven

    图  5  通信时延 θ =0 s时CACC控制下的车辆轨迹数据图(以速度区分交通波)

    Figure  5.  Vehicle trajectories under CACC when θ =0 s(traffic wave is characterized by the velocity)

    图  6  通信时延θ =1 s时CACC控制下的车辆轨迹数据图(以速度区分交通波)

    Figure  6.  Vehicle trajectories under CACC when θ =1 s(traffic wave is characterized by the velocity)

    图  7  退化为ACC控制下的车辆轨迹数据图(以速度区分交通波)

    Figure  7.  Vehicle trajectories under ACC degraded from CACC(traffic wave is characterized by the velocity)

    图  8  通信时延θ =0 s时CACC控制下的车辆轨迹数据图(以加速度区分交通波)

    Figure  8.  Vehicle trajectories under CACC when θ =0 s(traffic wave is characterized by the acceleration)

    图  9  通信时延 θ =1 s时CACC控制下的车辆轨迹数据图(以加速度区分交通波)

    Figure  9.  Vehicle trajectories under CACC when θ =1 s(traffic wave is characterized by the acceleration)

    图  10  退化为ACC控制下的车辆轨迹数据图(以加速度区分交通波)

    Figure  10.  Vehicle trajectories under ACC degraded from CACC(traffic wave is characterized by the acceleration)

    表  1  反馈控制K(s) 的参数取值

    Table  1.   Parameter setup for the feedback K(s)

    第1组 第2组
    kp 0.40 0.90
    kd 1.20 2.70
    下载: 导出CSV

    表  2  头车运动轨迹

    Table  2.   Velocity profile of the leading vehicle

    时间/s 轨迹
    0≤ t < 30 头车以25 m/s的速度匀速行驶,跟随车辆达到稳定
    30≤ t < 33 头车以-5 m/s2的加速度进行紧急制动
    33≤ t < 38 头车保持10 m/s的速度匀速行驶
    38 ≤t < 53 头车以1 m/s2加速度恢复至25 m/s的速度
    53≤ t≤ 200 头车以25 m/s匀速行驶
    下载: 导出CSV

    表  3  交通仿真中的参数取值

    Table  3.   Parameter setup in traffic simulation

    参数 符号 数值
    驾驶员反应延迟/s τ 0.5
    自由加速度指数 δ 4.0
    车辆最大加速度/(m/s2) am 2.0
    车辆最大减速度/(m/s2) bm 5.0
    驾驶员舒适加速度/(m/s2) ac 1.4
    驾驶员舒适减速度/(m/s2) bc 2.0
    驾驶员期望速度/(m/s2) vd 25.0
    静止时的车距/m s0 0.0
    车辆动力学参数 η 0.1
    期望时距/s hd 1.2
    期望速度/(m/s) vd 25.0
    控制器P参数 kp 0.9
    控制器D参数 kd 2.7
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-10-25
  • 刊出日期:  2021-02-28

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