丁恒Ding Heng

教授

教授 博士生导师 硕士生导师

电子邮箱:

入职时间:2005-07-01

所在单位:道路与交通工程系

职务:系主任/交通工程研究所所长

学历:博士研究生毕业

办公地点:三立苑416

在职信息:在职

论文成果

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Heng Ding(*) Ruohui Wang, Liangwen Wang, Wei Ma, Xiaoyan Zheng, Wenjuan Huang. Macroscopic characteristics of road network traffic flow under cyberattacks in a connected vehicle environment

发布时间:2025-05-01 点击次数:

影响因子:2.8
DOI码:10.1016/j.physa.2025.130641
所属单位:Hefei University of Technology
教研室:School of Automotive and Transportation Engineerin
发表刊物:Physica A: Statistical Mechanics and its Applications
刊物所在地:USA
项目来源:National Natural Science Foundation of China
关键字:Connected vehicle environment; Traffic network; Delay Cyberattacks; Macroscopic fundamental diagram (MFD); Rerouting
摘要:Connected Autonomous Vehicle (CAV) technology enables real-time path information provision and smaller headway distances, and is adopted to improve the efficiency and safety of road network traffic flow. However, dynamic information interaction between CAV and the platform is mainly transferred through communication networks. The open communication environment is vulnerable to cyberattacks, leading to security threats such as delays and interruptions in traffic networks. Existing studies on the impact of cyberattacks on traffic mainly focus on individual vehicles or queues, which cannot be used to analyse the effects of the cyberattacks on the macroscopic traffic network. To acquire the impact of information delay caused by cyberattacks on traffic networks, based on the macroscopic fundamental diagram (MFD) theory, this paper carries out two works. Firstly, the effect of cyberattacks with different durations on the MFD of traffic networks in a grid-connected environment is analysed using a classical grid road network and a real road network as the analysis objects. Secondly, the variability of the impact of cyberattacks on the MFD of road networks is analysed under different CAV penetration rates as well as under different cyberattack durations. The experimental results demonstrate three findings: (i) when the road network is in a congested flow state, the MFD curve of the traffic network is more affected by cyberattacks; (ii) different cyberattack delay times will vary depending on the size and complexity of the road network; and (iii) the impact degree of cyberattacks decreases the traveling completion flow of the traffic network, and which increases with the rise of CAV penetration.
论文类型:期刊论文
学科门类:工学
文献类型:J
页面范围:130641
字数:13200
是否译文:
发表时间:2025-05-01
收录刊物:SCI、EI
发布期刊链接:https://doi.org/10.1016/j.physa.2025.130641