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Vehicular Resilient Control Strategy for a Platoon of Self-Driving Vehicles under DoS Attack

Hassan Mokari, Yufei Tang

TL;DR

This work tackles the destabilization of vehicle platoons caused by denial‑of‑service attacks that compromise leader data. It introduces a distributed resilient control framework that detects DoS via two incremental counters, reconfigures the communication graph to isolate the attacked leader, and designates a new leader to restore leader–follower consensus, with a switching controller guiding retrieval of the attacked vehicle. Stability under time‑varying delays is established through Lyapunov–Krasovskii analysis and LMIs that incorporate delay bounds $\mathcal{U}$ and delay‑rate $d$. Simulations on a 4‑vehicle platoon demonstrate effective attack detection, isolation, leader switching, and restoration of consensus with prescribed inter‑vehicle spacings, underscoring practical viability for self‑driving platoons.

Abstract

In a platoon, multiple autonomous vehicles engage in data exchange to navigate toward their intended destination. Within this network, a designated leader shares its status information with followers based on a predefined communication graph. However, these vehicles are susceptible to disturbances, leading to deviations from their intended routes. Denial-of-service (DoS) attacks, a significant type of cyber threat, can impact the motion of the leader. This paper addresses the destabilizing effects of DoS attacks on platoons and introduces a novel vehicular resilient control strategy to restore stability. Upon detecting and measuring a DoS attack, modeled with a time-varying delay, the proposed method initiates a process to retrieve the attacked leader. Through a newly designed switching system, the attacked leader transitions to a follower role, and a new leader is identified within a restructured platoon configuration, enabling the platoon to maintain consensus. Specifically, in the event of losing the original leader due to a DoS attack, the remaining vehicles do experience destabilization. They adapt their motions as a cohesive network through a distributed resilient controller. The effectiveness of the proposed approach is validated through an illustrative case study, showing its applicability in real-world scenarios.

Vehicular Resilient Control Strategy for a Platoon of Self-Driving Vehicles under DoS Attack

TL;DR

This work tackles the destabilization of vehicle platoons caused by denial‑of‑service attacks that compromise leader data. It introduces a distributed resilient control framework that detects DoS via two incremental counters, reconfigures the communication graph to isolate the attacked leader, and designates a new leader to restore leader–follower consensus, with a switching controller guiding retrieval of the attacked vehicle. Stability under time‑varying delays is established through Lyapunov–Krasovskii analysis and LMIs that incorporate delay bounds and delay‑rate . Simulations on a 4‑vehicle platoon demonstrate effective attack detection, isolation, leader switching, and restoration of consensus with prescribed inter‑vehicle spacings, underscoring practical viability for self‑driving platoons.

Abstract

In a platoon, multiple autonomous vehicles engage in data exchange to navigate toward their intended destination. Within this network, a designated leader shares its status information with followers based on a predefined communication graph. However, these vehicles are susceptible to disturbances, leading to deviations from their intended routes. Denial-of-service (DoS) attacks, a significant type of cyber threat, can impact the motion of the leader. This paper addresses the destabilizing effects of DoS attacks on platoons and introduces a novel vehicular resilient control strategy to restore stability. Upon detecting and measuring a DoS attack, modeled with a time-varying delay, the proposed method initiates a process to retrieve the attacked leader. Through a newly designed switching system, the attacked leader transitions to a follower role, and a new leader is identified within a restructured platoon configuration, enabling the platoon to maintain consensus. Specifically, in the event of losing the original leader due to a DoS attack, the remaining vehicles do experience destabilization. They adapt their motions as a cohesive network through a distributed resilient controller. The effectiveness of the proposed approach is validated through an illustrative case study, showing its applicability in real-world scenarios.
Paper Structure (9 sections, 1 theorem, 44 equations, 6 figures, 2 algorithms)

This paper contains 9 sections, 1 theorem, 44 equations, 6 figures, 2 algorithms.

Table of Contents

  1. INTRODUCTION
  2. MATHEMATICAL MODELLING
  3. Platoon Model
  4. DoS Attack Model
  5. ATTACK DETECTION
  6. RESILIENT CONTROL
  7. STABILITY ANALYSIS
  8. SIMULATION RESULTS
  9. CONCLUSION

Key Result

Theorem 1

The system Z_dynamic under bounded_delay would be asymptotically stable if and only if: where

Figures (6)

  • Figure 1: Communication network diagrams with 4 vehicles: (a) Represents the normal mode (no attack); (b) Implies the leader is under DoS attack and this attached is detected; (c) Illustrates the attacked vehicle has been isolated; (d) Signifies vehicle 2 becomes the new leader and communicates with the platoon, aiming to reestablish a new leader-follower consensus.
  • Figure 2: (Top) Position of vehicles and (Bottom) Velocity of vehicles without attacks. Vehicle 4 is the leader.
  • Figure 3: Switching signals.
  • Figure 4: Position and velocity of vehicles under DoS attack. Vehicle 4 is under attack and is detected and isolated.
  • Figure 5: Position of vehicles. Vehicle 4 is under attack. Vehicle 2 is the new leader.
  • ...and 1 more figures

Theorems & Definitions (9)

  • Definition 1
  • Remark 1
  • Remark 2
  • Remark 3
  • Definition 2: 26
  • Remark 4
  • Theorem 1
  • proof 1
  • Remark 5