考虑智能网联汽车通信延时的混合交通流稳定性分析

张璐; 张兆磊; 刘至真; 唐峰

doi:10.3963/j.jssn.1674-4861.2024.02.010

考虑智能网联汽车通信延时的混合交通流稳定性分析

doi: 10.3963/j.jssn.1674-4861.2024.02.010

长沙理工大学交通运输工程学院长沙 410114

基金项目:

国家自然科学基金青年项目 52302385

湖南省重点研发计划项目 2023SK2052

详细信息

作者简介:
张璐（2000—），硕士研究生. 研究方向：交通流稳定性. E-mail：21101030103@stu.csust.edu.cn

通讯作者:
刘至真（1995—），博士，讲师. 研究方向：车路协同、交通流理论等. E-mail：zhizhenliu@csust.edu.cn

中图分类号: U491.2+62
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出版历程
- 收稿日期: 2023-12-27
- 网络出版日期: 2024-09-14

A Stability Analysis of Mixed Traffic Flows Considering Communication Delay of Connected and Autonomous Vehicles

School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China

摘要

摘要: 针对交通系统中微小扰动所诱发的车流不稳定现象以及车辆频繁启停问题，充分考虑智能网联汽车（connected and autonomous vehicle，CAV）的通信延时，对适用于混合交通流环境的扰动抑制方法展开了深入探寻。通过对CAV信息传递延时、不同渗透率、CAV编队强度等多重因素进行综合分析，探索了通信对混合交通流稳定性的影响机制。考虑最大编队车辆数并基于马尔可夫链构建混合流稳定性分析模型，得到了不同车头时距类型的生成概率，在此基础上构建了混合交通流的稳定性判别公式以分析不同条件下的车流速度稳定区域。为提高CAV通信效率借助了路侧单元传递信息。根据车路通信流向不同，将通信过程分为车端-路端的上行通信和路端-车端的下行通信，构建了低交通密度下的信息传递延时估计模型，得到不同CAV渗透率及编队强度下的延时估计值，以分析其对交通流稳定性影响。为验证分析结果开展了扰动演化的仿真实验，结果表明：①CAV渗透率与编队强度有利于混合交通流稳定性，而通信延时对交通流稳定性有负影响；②通信延时随着CAV渗透率与编队强度、路侧单元与CAV通信半径的增大而减小；③当最大编队车辆数为6且混合流以25 m/s的稳态速度行驶时，只有CAV渗透率达到60%或编队强度大于0.5，延时才小于0.3 s且扰动得到有效抑制。
- 交通工程 /
- V2X /
- 通信延时 /
- 混合交通流 /
- 稳定性
Abstract: In traffic systems, minor disturbances can significantly destabilize traffic flow and cause vehicles to exhibit frequent start-stop problem. This study aims to identify disturbance suppression techniques for mixed traffic flows, taking into account the issue of communication delay of connected and autonomous vehicle (CAV). To study the influence mechanism of vehicle communication on the stability of mixed traffic flows, a comprehensive analysis of multiple factors such as the delay of communication among CAV, the market penetration of CAV and the platooning intensity is conducted. Considering the impact of maximum size of CAV platooning, a stability analysis model of mixed traffic flows is constructed based on Markov chain, which can derive the generation probability of different headway types. On such basis, the stability identification formula of mixed traffic flows is developed to analyze the stable speed range under different conditions. In order to improve the efficiency of communication among CAV, the roadside units are used to transmit information. According to the different directions of vehicle-road communication, the communication process is divided into uplink communication from vehicle-to-road and downlink communication from road-to-vehicle. Next, the communication delay estimation model under low traffic density is developed, based on which the communication delay under different CAV penetrations and its platooning intensities to analyze its impact on traffic flow stability. To validate the analytical results, simulation experiments of disturbance evolution are conducted. The results indicate that: ①The market penetration of CAV and its platooning intensity are beneficial to the stability of mixed traffic flow. ② Communication delay has a negative impact on the stability of mix traffic flow. In detail, the delay decreases with the increase of the market penetration of CAV and its platooning intensity, the coverage of roadside units and CAVs'communication radius.③ When the maximum size of CAV platoon equaling 6 and the steady speed of mixed flow travels equaling 25 m/s, only when the market penetration of CAV reaches 60% or its platooning intensity is greater than 0.5, can the delay be less than 0.3 s and the disturbance
- traffic engineering /
- V2X /
- communication delay /
- mixed traffic flow /
- stability analysis

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图 1 混合交通流中的5种车辆跟驰类型与编队强度示意

Figure 1. Illustration of the five car following types and platooning intensity in mixed traffic

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图 2 部署有路侧单元的高速公路研究场景

Figure 2. Highway study scenario with roadside units deployed

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图 3 V2X延时敏感性分析

Figure 3. Sensitivity analysis of V2X delivery delay

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图 4 混合流稳定性（N=6）

Figure 4. The stability of mixed traffic flow(N=6)

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图 5 混合车队中跟驰模型选取逻辑图

Figure 5. Logic diagram for the selection of car-following model in mixed flow

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图 6 V2X通信下混合交通流的速度波动随pA变化（N = 6，O = 0.5）

Figure 6. The velocity fluctuation of mixed traffic flow varies with p_A under V2X communication

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图 7 N =6，p_A =50%时混合流速度随O变化

Figure 7. The velocity fluctuation of mixed traffic flow varies with O under N =6, p_A =50%

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表 1 不同p_A水平下混合流不稳定速度范围（N =6，O =0.5）

Table 1. Unstable velocity range of mixed flow at different p_A levels(N =6, O =0.5)

CAV渗透率	不稳定速度范围/（m/s）
0.1	0.3~28.2
0.2	0.3~33
0.3	0.3~33
0.4	0.4~33
0.5	0.4~27.1
0.6	0.4~21.9
0.7	0.6~12.1
0.8	恒稳定
0.9	恒稳定

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