混入智能网联汽车的交通流稳定性与安全性分析*

doi:10.16265/j.cnki.issn1003-3033.2021.10.019

中国安全科学学报 ›› 2021, Vol. 31 ›› Issue (10): 136-143.doi: 10.16265/j.cnki.issn1003-3033.2021.10.019

混入智能网联汽车的交通流稳定性与安全性分析^*

姚志洪^1,2,3 讲师, 金玉婷¹, 王思琛¹, 胡路^1,2 副教授, 蒋阳升^1,2,3 教授

1 西南交通大学交通运输与物流学院,四川成都 611756;
2 西南交通大学综合交通大数据应用技术国家工程实验室,四川成都 611756;
3 综合交通运输智能化国家地方联合工程实验室,四川成都611756

收稿日期:2021-07-10 修回日期:2021-09-16 出版日期:2021-10-28
作者简介:姚志洪 (1991—),男,安徽宿松人,博士,讲师,主要从事智能网联交通系统建模与优化。E-mail: zhyao@swjtu.edu.cn。
基金资助:
国家自然科学基金资助(52002339);四川省科技计划项目(21YYJC3166,2020YFH0026);广西科技计划项目(2021AA01007AA);中央高校基本科研业务费专项资金(2682021CX058)。

Stability and safety analysis on traffic flow mixed with ICV

YAO Zhihong^1,2,3, JIN Yuting¹, WANG Sichen¹, HU Lu^1,2, JIANG Yangsheng^1,2,3

1 School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan 611756, China;
2 National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu Sichuan 611756, China;
3 National United Engineering Laboratory of Integrated and Intelligent Transportation, Chengdu Sichuan 611756, China

Received:2021-07-10 Revised:2021-09-16 Published:2021-10-28

摘要/Abstract

摘要： 为揭示智能网联汽车(ICV)对交通流的影响特征,首先,考虑ICV的退化机制,分析混合交通流中的跟驰模式及其比例关系;然后,采用不同参数的智能驾驶员模型(IDM)来描述不同的跟驰模式,在此基础上推导出混合交通流稳定性的判别条件;最后,选取车速标准差变异系数、碰撞时间(TTC)、碰撞暴露时间(TET)和碰撞积分时间(TIT)等作为混合交通流安全性评价指标,并基于元胞自动机进行数值仿真试验。结果表明:随着ICV渗透率的增加,车速的离散程度逐渐降低,且尾部碰撞风险逐渐减小。因此,ICV的应用能够显著提高交通流的稳定性和安全性。

关键词: 智能网联汽车(ICV), 人工驾驶汽车(HDV), 混合交通流, 跟驰模型, 稳定性, 安全性

Abstract: In order to reveal influence mechanism of ICV on traffic flow, firstly, considering degradation mechanism of ICV, its following mode and proportion in mixed traffic flow were analyzed. Then, different following modes were described by utilizing intelligent driver model (IDM) with different parameters, based on which criteria to determine stability of mixed traffic flow were derived. Finally, standard deviation coefficient of car speed, time-to-collision(TTC), exposed time-to-collision(TET) and integrated time-to-collision (TIT) were selected as safety evaluation indexes of the traffic flow, and numerical simulation experiments were conducted based on cellular automata. The results show that as penetration rate of ICV increases, dispersion degree of vehicle speed gradually decreases, so does the risk of rear collision. Therefore, application of ICV can significantly improve stability and safety of traffic flow.

Key words: intelligent connected vehicle (ICV), human driven vehicle (HDV), mixed traffic flow, car-following model, stability, safety

中图分类号:

X951
U492.8

姚志洪, 金玉婷, 王思琛, 胡路, 蒋阳升. 混入智能网联汽车的交通流稳定性与安全性分析^*[J]. 中国安全科学学报, 2021, 31(10): 136-143.

YAO Zhihong, JIN Yuting, WANG Sichen, HU Lu, JIANG Yangsheng. Stability and safety analysis on traffic flow mixed with ICV[J]. China Safety Science Journal, 2021, 31(10): 136-143.

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混入智能网联汽车的交通流稳定性与安全性分析^*

Stability and safety analysis on traffic flow mixed with ICV

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