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浙江大学学报(工学版)  2024, Vol. 58 Issue (2): 381-387    DOI: 10.3785/j.issn.1008-973X.2024.02.016
交通工程、土木工程     
高速公路施工区车队被动换道行为建模与仿真
张俊杰(),马永锋*(),陈淑燕,邢冠仰,张子煜
东南大学 交通学院,城市智能交通江苏省重点实验室,现代城市交通技术江苏高校协同创新中心,江苏 南京 211189
Modeling and simulation of passive lane-changing behavior of platoons in freeway work zone
Junjie ZHANG(),Yongfeng MA*(),Shuyan CHEN,Guanyang XING,Ziyu ZHANG
College of Transportation, Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
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摘要:

针对高速公路施工区域车速波动大,通行效率低的问题,从网联环境车队行为协同优化角度出发,构建车队被动换道行为模型. 利用Plexe-SUMO搭建仿真平台,设计相应车队生成及换道选择算法,实现车队行为的生成与仿真. 考虑不同的流量状态,通过调整车队规模,探究不同车队规模对施工区通行效率提升的影响,寻求较理想的车队组织形式. 结果表明,在中、低流量(小于900 辆/h)状态下,车辆以较小规模(小于4辆)的车队形式行驶较合适. 随着路段流量的增多,尤其在高流量状态下,车辆组成规模较大的车队(大于6辆)更能够提升通行效率. 在实验场景下,当单车道流量小于1 100 辆/h时,理想的车队规模为2辆. 当流量较大时,理想车队规模为6~8辆. 这表明在不同流量状态下的施工区域,存在某一合理车队规模,使得路段通行能力达到最优.

关键词: 车队高速公路施工区被动换道车队规模优化Plexe-SUMO    
Abstract:

A passive lane-changing behavior model for connected vehicle platoons was developed from the perspective of cooperative optimization of platoon behavior aiming at the issue of significant speed fluctuations and low traffic efficiency in freeway work zones. The Plexe-SUMO simulation platform was employed, and algorithms for platoon generation and lane-changing choices were designed, thereby enabling the generation and simulation of platoon behavior. Different traffic flow conditions were considered, and the impact of platoon size adjustments on the enhancement of traffic efficiency in work zones was analyzed, culminating in the quest for an optimal platoon organization structure. The experimental results show that small platoons of less than 4 pcu are more suitable in medium and low-volume states (less than 900 pcu/h). Larger platoon sizes (greater than 6 pcu) improved passing efficiency as volume increases, especially in high-volume states. An ideal platoon size of 2 pcu was found when the single-lane volume was less than 1100 pcu/h in the experimental scenario, while a platoon size between 6 and 8 pcu was ideal for high volume states. There exists an optimal platoon size in work zones under different traffic flow conditions, allowing the roadway capacity to reach its maximum efficiency.

Key words: platoon    freeway    work zone    passive lane-changing    platoon size optimization    Plexe-SUMO
收稿日期: 2023-06-30 出版日期: 2024-01-23
CLC:  U 491  
基金资助: 国家重点研发计划资助项目(2022YFB4300300)
通讯作者: 马永锋     E-mail: zhangjunjie@seu.edu.cn;mayf@seu.edu.cn
作者简介: 张俊杰(1996—),男,博士生,从事智能交通和交通安全的研究. orcid.org/0000-0003-0143-038X. E-mail:zhangjunjie@seu.edu.cn
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引用本文:

张俊杰,马永锋,陈淑燕,邢冠仰,张子煜. 高速公路施工区车队被动换道行为建模与仿真[J]. 浙江大学学报(工学版), 2024, 58(2): 381-387.

Junjie ZHANG,Yongfeng MA,Shuyan CHEN,Guanyang XING,Ziyu ZHANG. Modeling and simulation of passive lane-changing behavior of platoons in freeway work zone. Journal of ZheJiang University (Engineering Science), 2024, 58(2): 381-387.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2024.02.016        https://www.zjujournals.com/eng/CN/Y2024/V58/I2/381

图 1  车队整体换道行为的示意图
图 2  施工影响区车队被动换道行为的示意图
算法1 车队行为生成及车道选择
输入:车道:L = {L1, L2, L3, ···, Lm}
   所有车道中可发车的车道:L_gen = {L_gen1, L_gen2, ···, L_geng}
   可发车车道车辆类型:C = {C1, C2, C3,···, Cg}
   可发车车道车队规模:S = {S1, S2, S3,···, Sg}
   可发车车道车流量:B = {B1, B2, B3, ···, Bg}
   时间:D
函数:产生车队:Generate_Platoon(L, C, S)
   随机函数:Random(Set())
过程:
1:A ← {}
2:Last = {Last1, Last2,···,Lastg} ← 可发车车道上次发车时间
3:T = {3600/(Bi/Si) for i in {1,2,···,g}} ← 发车间隔
4:换道函数:ChangeLane(A, L)
5:d ← 当前时间
6:while d <= D
7:   for L_geni in L_gen
8:     Blank_Time = d ? Lasti
9:     while Blank_Time == Ti
10:      p ← Generate_Platoon(L_geni, Ci, Si)
11:      AA ∪ {p}
12:      Lasti = d
13:  for Aj in A
14:    if Aj到达换道区域
15:      LcLAj可换道车道
16:      Lj = Random (Lc)
17:      ChangeLine (Aj, Lj)
18:    else if Aj驶出所有车道
19:      AA ?{Aj}
20:  d += 1
  
参数数值
现状情形车队情形
跟驰模型KraussACC
换道模型SL2015
车身长度/m55
车辆最大速度/(m·s?116.616.6
速度偏差系数0.10
车辆加速度/(m·s?234
车辆减速度/(m·s?234
紧急情况下车辆
最大减速度/(m·s?2
89
期望车头时距/s1.51
驾驶不完美系数0.50
静止时车间最小间距/m20.5
表 1  现状及车队行为仿真的主要参数设定
图 3  SUMO仿真逻辑流图
图 4  施工区域车队运行的仿真效果
图 5  不同流量状态下各指标输出结果的色阶图
图 6  不同流量及队列规模条件下的延误指标变化
$ \bar f $/(辆·h?1$ \bar p $指标相对变化比例/%
$ \bar v $$ \bar \omega $$ \bar l $
30028.71?18.25?6.02
50023.59?13.82?4.47
70026.03?39.40?3.91
900224.55?80.36?87.04
11006291.19?93.71?91.52
1300873.26?34.10?42.65
表 2  施工区不同流量状态下各队列规模指标相对现状的变化比例汇总
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