吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (10): 3200-3207.doi: 10.13229/j.cnki.jdxbgxb.20240383

• 交通运输工程·土木工程 • 上一篇    

考虑临界密度的道路网络混合交通流级联失效

路庆昌(),任永全,李静,孟旭,徐鹏程   

  1. 长安大学 电子与控制工程学院,西安 710064
  • 收稿日期:2024-04-11 出版日期:2025-10-01 发布日期:2026-02-03
  • 作者简介:路庆昌(1984-),男,教授,博士. 研究方向:交通网络建模与分析,交通行为学,交通与环境,气候变化与交通系统,交通大数据挖掘. E-mail: qclu@chd.edu.cn
  • 基金资助:
    国家自然科学基金重点项目(52232012);国家自然科学基金项目(71971029)

Cascading failures of mixed traffic flows in road networks considering critical density

Qing-chang LU(),Yong-quan REN,Jing LI,Xu MENG,Peng-cheng XU   

  1. School of Electronics and Control Engineering,Chang'an University,Xi'an 710064,China
  • Received:2024-04-11 Online:2025-10-01 Published:2026-02-03

摘要:

为探究网联自动驾驶车辆(Connected automated vehicle,CAV)引入后道路网络级联失效机理,建立了考虑新型混合交通流道路临界密度的路网级联失效模型。该方法考虑失效后流量重分配的方式,并捕捉混合交通流对道路抵抗拥堵能力的影响。本文以西安市城市道路网络为例,研究了混合交通流级联失效的规律特征。结果表明:CAV渗透率达到0.6(临界值)时,最外层节点开始抵御失效,级联失效的传播速度会显著放缓;渗透率超过0.6后,最外层节点成功抵御失效,失效总规模下降91%左右;攻击流量最大节点时的失效传播速度最快且规模最大,管控流量最大节点是级联失效管控的重点。

关键词: 交通信息工程及控制, 混合交通流, 自动驾驶, 渗透率, 道路临界密度, 级联失效

Abstract:

In order to investigate the road network cascading failures mechanism after the introduction of connected automated vehicles (CAV), a road network cascade failure model considering the critical density of a new type of road with mixed traffic flow is developed. The method considers the way of traffic redistribution after failures and captures the effect of mixed traffic flow on the road's ability to resist congestion. In this paper, the urban road network of Xi'an City is taken as an example to study the regular characteristics of the cascading failures of mixed traffic flow. The results show that when the CAV penetration rate reaches 0.6(critical value), the outermost nodes start to resist failures, and the propagation of cascading failures slows down significantly; after the penetration rate exceeds 0.6, the outermost nodes successfully resist failures, and the total size of failures decreases by about 91%. Failure propagation is fastest and largest when attacking the largest node of the traffic flow, and controlling the largest node of the traffic flow is the focus of cascade failure.

Key words: traffic information engineering and control, mixed traffic flow, automated driving, penetration, road critical density, cascading failures

中图分类号: 

  • U491.2

图1

西安市中心城区道路交通网络拓扑结构"

图2

CML与M-CML在3种攻击场景下施加不同外部扰动后的最终失效节点比例"

图3

CML与M-CML在3种攻击场景下的级联失效过程"

图4

攻击流量最大节点时不同r值的失效节点比例"

图5

攻击流量最大节点时不同r值的瞬时失效节点比例"

图6

攻击流量最大节点时临界渗透率前后部分时间步失效传播对比"

图7

不同攻击场景下不同r值的累计失效节点比例"

图8

不同攻击场景下不同r值的最终失效节点比例"

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