In response to the escalating challenges posed by traffic bottlenecks, accidents, and intersection delays, the deployment of platooning mechanisms emerges as an imperative remedy. This investigation revolves around a pivotal scenario wherein a closely-knit platoon of cooperative vehicles approaches an intersection. Orchestrated by a lead vehicle, this convoy navigates the traffic light to expedite the journey of its followers towards their respective destinations. However, given that the size of the platoon can be increased, it will become difficult for the leader to manage it smoothly. Therefore, dividing the platoon into small groups led by co-leaders who deal directly with the leader is considered an ideal solution to speed up and facilitate the process of maintaining platoon stability. In this paper, we propose a Cooperative Adaptive Platooning Control Algorithm (CAPCA) for the hybrid communication topology in platooning. In fact, CAPCA aims to achieve stability in the platoon by distributing tasks in a parallel manner to mini-platoons. Moreover, inherent complexities arise as select members within the platoon strive to undermine its stability. Within this context, the research addresses the intricacies of Vehicle Platooning Disruption (VPD) attacks, a menacing phenomenon characterized by deliberate efforts to destabilize or seize control of a platoon. These attacks manifest through tactics such as false data injection (FDI) and replaying of control messages. In response, a robust and multifaceted countermeasure is conceptualized. The Vehicle Platooning Disruption Attacks Detection Protocol (VPD-ADP) takes center stage as a foundational component. By identifying instability within the platoon's dynamics model, VPD-ADP lays the essential groundwork for mitigating the repercussions of FDI and replay attacks. Employing advanced stochastic time series analysis, the impact of VPD attacks is scrutinized via anomalies in the Cartesian coordinates of vehicles deviations from the trajectory anticipated by the platoon. Moreover, the study introduces the Reputation-based Reliable Mitigation Protocol (RRMP), a pioneering approach that leverages collaborative data gleaned from neighboring vehicles. RRMP is devised to assess the veracity of received messages and gauge their reliability in real-time. Through extensive simulations and experiments, the proposed approach's effectiveness in fortifying the resilience of vehicle platooning systems against an array of disruption attacks is convincingly demonstrated.

中文翻译：

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车辆列队干扰攻击的检测和缓解

为了应对交通瓶颈、事故和十字路口延误带来的不断升级的挑战，部署队列机制成为势在必行的补救措施。这项调查围绕一个关键场景展开，其中一队紧密合作的车辆接近十字路口。在领头车辆的指挥下，这个车队在红绿灯下行驶，以加快其追随者前往各自目的地的旅程。然而，由于排的规模可以扩大，领导者想要顺利管理就会变得困难。因此，将排分成由直接与领导打交道的副领导领导的小组被认为是加速和促进维持排稳定过程的理想解决方案。在本文中，我们提出了一种用于队列混合通信拓扑的协作自适应队列控制算法（CAPCA）。事实上，CAPCA 旨在通过将任务以并行方式分配给迷你排来实现排的稳定性。此外，当排内选定的成员努力破坏其稳定性时，就会出现固有的复杂性。在此背景下，该研究解决了车辆编队干扰（VPD）攻击的复杂性，这是一种威胁现象，其特点是故意破坏车队的稳定或夺取对车队的控制权。这些攻击通过虚假数据注入 (FDI) 和重放控制消息等策略来体现。作为回应，我们提出了强有力的、多方面的对策。车辆编队干扰攻击检测协议 (VPD-ADP) 作为基础组件占据中心位置。通过识别排动态模型中的不稳定性，VPD-ADP 为减轻 FDI 和重放攻击的影响奠定了必要的基础。采用先进的随机时间序列分析，通过车辆笛卡尔坐标与排预期轨迹的偏差来检查 VPD 攻击的影响。此外，该研究还引入了基于信誉的可靠缓解协议（RRMP），这是一种利用从邻近车辆收集的协作数据的开创性方法。 RRMP 旨在评估接收到的消息的准确性并实时衡量其可靠性。通过广泛的模拟和实验，所提出的方法在增强车辆队列系统抵御一系列破坏攻击的弹性方面的有效性得到了令人信服的证明。