基于虚假数据注入的网联车队弹性控制策略

doi:10.3901/JME.2025.12.266

机械工程学报 ›› 2025, Vol. 61 ›› Issue (12): 266-280.doi: 10.3901/JME.2025.12.266

• 运载工程 • 上一篇

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基于虚假数据注入的网联车队弹性控制策略

高凯^1,2, 刘林鸿², 胡林^1,2, 樊绍胜³, 程翔宇², 邹铁方^1,2

1. 长沙理工大学智能道路与车路协同湖南省重点实验室长沙 410114;
2. 长沙理工大学机械与运载工程学院长沙 410114;
3. 长沙理工大学人工智能学院长沙 410114

收稿日期:2024-08-10 修回日期:2025-02-20 发布日期:2025-08-07
作者简介:高凯，男，1985年出生，博士，副教授，博士研究生导师。主要研究方向为自动驾驶汽车感知与控制，智能交通与车联网应用、电池管理系统及相关算法。E-mail：kai_g@csust.edu.cn;刘林鸿，男，2000年出生。主要研究方向为自动驾驶强化学习安全决策。E-mail：llh_llh@stu.csust.edu.cn;胡林(通信作者)，男，1978年出生，博士，教授，博士研究生导师。主要研究方向为车辆智能化、车辆安全。E-mail：hulin@csust.edu.cn
基金资助:
国家自然科学基金(52325211)、湖南省自然科学基金(2024J15023)和长沙理工大学智能道路与车路协同湖南省重点实验室开放基金(kfj190701)资助项目。

Elastic Control Strategy for Connected Vehicle Platoon Based on False Data Injection

GAO Kai^1,2, LIU Linhong², HU Lin^1,2, Fan Shaosheng³, CHENG Xiangyu², ZOU Tiefang^1,2

1. Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems, Changsha University of Science & Technology, Changsha 410114;
2. College of Mechanical and Vehicle Engineering, Changsha University of Science & Technology, Changsha 410114;
3. School of Artificial Intelligence, Changsha University of Science & Technology, Changsha 410114

Received:2024-08-10 Revised:2025-02-20 Published:2025-08-07

摘要/Abstract

摘要： 智能网联车编队(intelligent connected vehicles,ICVS)行驶对减少车辆能耗、提高交通运输效率和安全性具有显著作用。然而来自黑客入侵、恶意软件或信号伪造的虚假数据注入攻击严重影响了车辆编队的安全运行，是当前该领域面临的严峻挑战。提出一种针对虚假数据注入攻击的网联车队弹性控制策略，结合滚动优化与攻击检测，有效降低了虚假数据注入攻击对网联车队的影响。该算法利用车队多智能体之间的级联特性，通过在相同的时空环境中获取不同车辆的期望车队状态量来快速定位受攻击的车辆，然后采用切换控制策略对受到攻击的车辆进行补偿。在仿真平台VENTOS上搭建车队动力学和通信状态网联车队模型，通过多种工况试验验证了提出的方法在检测不同类型虚假数据注入攻击的性能，经过攻击补偿实验表明受影响车辆能够恢复到稳定状态，所提出的方案为虚假数据注入攻击下的网联车队安全控制提供了一种有效的解决方案。

关键词: 智能交通, 网联车队, 虚假数据, 弹性控制, 网络攻击

Abstract: The platooning of intelligent connected vehicles(ICVs) plays a significant role in reducing vehicle energy consumption, enhancing transportation efficiency, and improving safety. However, false data injection(FDI) attacks from hackers, malware, or signal spoofing severely impact the safe operation of vehicle platoons, posing a serious challenge in this field. This study proposes a resilient control strategy for ICV platoons against false data injection attacks, combining rolling optimization and attack detection to effectively mitigate the impact of such attacks on the platoon. The algorithm leverages the cascading characteristics among multiple agents within the platoon, quickly identifying the attacked vehicle by obtaining the expected platoon state variables of different vehicles in the same spatial-temporal environment. Subsequently, a switching control strategy is employed to compensate for the attacked vehicle. The platoon dynamics and communication state models were constructed on the simulation platform VENTOS. Various scenario tests validated the proposed method’s performance in detecting different types of false data injection attacks, Compensation experiments demonstrated that affected vehicles could return to a stable state. The proposed scheme provides an effective solution for secure control of ICV platoons under false data injection attacks.

Key words: intelligent transportation, connected vehicle platoon, false data, elastic control, network attacks

中图分类号:

TP309
TP391

高凯, 刘林鸿, 胡林, 樊绍胜, 程翔宇, 邹铁方. 基于虚假数据注入的网联车队弹性控制策略[J]. 机械工程学报, 2025, 61(12): 266-280.

GAO Kai, LIU Linhong, HU Lin, Fan Shaosheng, CHENG Xiangyu, ZOU Tiefang. Elastic Control Strategy for Connected Vehicle Platoon Based on False Data Injection[J]. Journal of Mechanical Engineering, 2025, 61(12): 266-280.

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基于虚假数据注入的网联车队弹性控制策略

Elastic Control Strategy for Connected Vehicle Platoon Based on False Data Injection

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