考虑时延的网联车混合交通流基本图模型

doi:10.12141/j.issn.1000-565X.210702

华南理工大学学报(自然科学版) ›› 2023, Vol. 51 ›› Issue (1): 106-113.doi: 10.12141/j.issn.1000-565X.210702

所属专题： 2023年交通运输工程

考虑时延的网联车混合交通流基本图模型

罗瑞发¹ 郝慧君² 徐桃让²顾秋凡²

^1.同济大学道路与交通工程教育部重点实验室，上海 201804
^2.西南交通大学交通运输与物流学院，四川成都 610031

收稿日期:2021-11-04 出版日期:2023-01-25 发布日期:2023-01-02
通信作者: 郝慧君（1999-），女，硕士生，主要从事智慧交通研究。 E-mail:810399784@qq.com
作者简介:罗瑞发（1976-），男，博士，高级工程师，主要从事智慧交通研究。E-mail:luorf@genvict.com.
基金资助:
国家自然科学基金资助项目(52002339);广西科技计划项目创新驱动发展专项(桂科AA21077011)

Fundamental Diagram Model of Mixed Traffic Flow of Connected Vehicles Considering Time Delay

LUO Ruifa¹HAO Huijun²XU Taorang²GU Qiufan²

^1.Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
^2.School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

Received:2021-11-04 Online:2023-01-25 Published:2023-01-02
Contact: 郝慧君（1999-），女，硕士生，主要从事智慧交通研究。 E-mail:810399784@qq.com
About author:罗瑞发（1976-），男，博士，高级工程师，主要从事智慧交通研究。E-mail:luorf@genvict.com.
Supported by:
the National Natural Science Foundation of China(52002339)

摘要/Abstract

摘要：

由于智能网联车的不断发展，未来将出现智能网联车和人工驾驶车共同存在的混合交通流，因此，研究道路上的混合交通有助于解决交通拥堵等问题，具有一定的现实意义。为探究这类混合交通流的流量、密度和速度之间的关系，文中综合考虑智能网联车辆退化和车辆时延，建立了自动驾驶环境下混合交通流的基本图模型。首先，确定交通流中的车辆类型和不同类型车辆的比例，并考虑联网智能车辆跟随人工车辆时发生的车辆功能退化；然后，确定3种车辆的延迟时间并改进每种车辆的跟驰模型；在此基础上，同时考虑车辆时延和车辆功能退化两种因素，推导出交通流平衡时的基本图模型，并对模型中的自由流速度参数进行敏感度分析。研究结果表明，智能网联车对混合交通流的最大流量和最佳密度有积极影响，车辆时延有消极影响，自由流速度则对混合交通流的最大流量有积极影响，对最佳密度有消极影响。SUMO仿真结果表明，在不同场景下仿真得到的流量?密度分布点符合理论曲线，验证了文中理论模型的准确性。

关键词: 智能网联车, 混合交通流, 基本图模型, 车辆功能退化, 车辆时延

Abstract:

Due to the continuous development of connected and automated vehicles, there will be a mixed traffic flow in which intelligent networked vehicles and manual driving vehicles coexist in the future. Therefore, the study of mixed traffic on the road can effectively solve traffic congestion and other problems, so it has certain practical significance. In order to explore the relationship between the flow, density and speed of this type of mixed traffic flow, this paper established a fundamental diagram model of the mixed traffic flow in an autonomous driving environment based on the comprehensive consideration of the degradation of intelligent networked vehicles and the delay between vehicles. First, it determined the types of vehicles in the traffic flow and the proportion of different types of vehicle, and considered the vehicle functional degradation when connected intelligent vehicles follow artificial vehicles. Then, the delay time of each type of three vehicles was determined and the following model of each vehicle was improved. On this basis, considering both the vehicle delay and the vehicle function degradation, the fundamental diagram model of traffic flow balance was derived, and the sensitivity analysis of free flow speed parameter in the model was carried out. The research result shows that connected and automated vehicles have a positive impact on the maximum flow and optimal density of mixed traffic flows, while vehicle delays have a negative impact; the free flow speed has a positive impact on the maximum flow and a negative impact on the optimal density of mixed traffic flow. The SUMO simulation results show that the simulated flow-density distribution points in different scenarios conform to the theoretical curve, which verifies the accuracy of the theoretical model in the paper.

Key words: connected and automated vehicle, mixed traffic flow, fundamental diagram model, vehicle function degradation, vehicle time delay

中图分类号:

U463.6

罗瑞发, 郝慧君, 徐桃让, 等. 考虑时延的网联车混合交通流基本图模型[J]. 华南理工大学学报(自然科学版), 2023, 51(1): 106-113.

LUO Ruifa, HAO Huijun, XU Taorang, et al. Fundamental Diagram Model of Mixed Traffic Flow of Connected Vehicles Considering Time Delay[J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(1): 106-113.

图/表 5

参考文献 15

1	刘爽，吴韶波．V2X车联网关键技术及应用［J］．物联网技术，2018，8（10）：39-40，43．
	LIU Shuang， WU Shao-bo ．The key technologies and applications of V2X vehicles［J］．Internet of Things Technologies，2018，8（10）：39-40，43．
2	BANSAL P， KOCKELMAN K M ．Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies［J］．Transportation Research Part A； Policy and Practice，2017，95A：49-63．
3	CALVERE S C， SCHAKEL W J， LINT Van J W C ．Will automated vehicles negatively impact traffic flow？［J］．Journal of Advanced Transportation，2017，2017：1-17．
4	TALEBPOUR A， MAHMASSANI H S ．Influence of connected and autonomous vehicles on traffic flow stability and throughput［J］．Transportation Research Part C：Emerging Technologies，2016，71：143-163．
5	YE L， YAMAMOTO T ．Modeling connected and autonomous vehicles in heterogeneous traffic flow［J］．Physica A：Statistical Mechanics and its Applications，2018，490：269-277．
6	ZHOU J， ZHU F ．Modeling the fundamental diagram of mixed human-driven and connected automated vehicles-ScienceDirect［J］．Transportation Research Part C：Emerging Technologies，2020，115：102614/1-20．
7	秦严严，王昊，王炜，等．混有CACC车辆和ACC车辆的异质交通流基本图模型［J］．中国公路学报，2017，30（10）：127-136．
	QIN Yan-yan， WANG Hao， WANG Wei，et al ．Heterogeneous traffic flow model mixed with CACC and ACC vehicles［J］．China Journal of Highway and Transport，2017，30（10）：127-136．
8	常鑫，李海舰，荣建，等．混有智能网联车队的交通流基本图模型分析［J］．东南大学学报（自然科学版），2020，50（4）：782-788．
	CHANG Xin， LI Haijian， RONG Jian，et al ．Analysis of basic traffic flow diagram model with intelligent network fleet［J］．Journal of Southeast University （Natural Science Edition），2020，50（4）：782-788．
9	LEVIN M W， BOYLES S D ．A multiclass cell transmission model for shared human and autonomous vehicle roads［J］．Transportation Research Part C：Emerging Technologies，2016，62：103-116．
10	徐桃让，姚志洪，蒋阳升，等．智能网联车环境下考虑反应时间影响的基本图模型［J］．公路交通科技，2020，37（8）：108-117．
	XU Tao-rang， YAO Zhi-hong， JIANG Yang-sheng，et al ．The fundamental graph model considering the effect of reaction time in intelligent networked vehicle environment［J］．Journal of Highway and Transportation Research and Developmen，2020，37（8）：108-117．
11	MILANES V， SHLADOVER S E， SPRIING J，et al ．Cooperative adaptive cruise control in real traffic situations［J］．IEEE Transactions on Intelligent Transportation Systems，2014，15（1）：296-305．
12	SHLADOVER S， SU D， LU X Y ．Impacts of cooperative adaptive cruise control on freeway traffic flow［J］．Transportation Research Record Journal of the Transportation Research Board，2012，2324：63-70．
13	NGODUY D ．Analytical studies on the instabilities of heterogeneous intelligent traffic flow［J］．Communications in Nonlinear Science and Numerical Simulation，2013，18（10）：2699-2706．
14	ZHENG F， LIU C， LIU X，et al ．Analyzing the impact of automated vehicles on uncertainty and stability of the mixed traffic flow［J］．Transportation Research Part C：Emerging Technologies，2020，112：203-219．
15	YAO Z， HU R， WANG Y，et al ．Stability analysis and the fundamental diagram for mixed connected automated and human-driven vehicles［J］．Physica A：Statistical Mechanics and its Applications，2019，533：121931．

[1]	李潇, 汪涛, 张毅, 等. 网联车混行条件下交通流量融合方法[J]. 华南理工大学学报(自然科学版), 2022, 50(5): 49-55.
[2]	常鑫, 李海舰, 荣建, 等. 混有网联车队的高速公路通行能力分析 [J]. 华南理工大学学报（自然科学版）, 2020, 48(4): 142-148.

考虑时延的网联车混合交通流基本图模型

Fundamental Diagram Model of Mixed Traffic Flow of Connected Vehicles Considering Time Delay

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献 15

相关文章 2

编辑推荐

Metrics

本文评价