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Assessment of Cyberattack Detection-Isolation Algorithm for CAV Platoons Using SUMO

Sanchita Ghosh, Tanushree Roy

TL;DR

The paper tackles cybersecurity in multi-modal CAV platoons by developing a unified V2V-V2I detection-isolation framework. It models a switching-mode ring-platoon and implements a two-phase scheme (V2X detection followed by V2I isolation) with per-vehicle detectors and isolators and theoretical guarantees. The approach is validated in a SUMO-TraCI-MATLAB setup using UDDS/NGSIM driving data, across FDI and DoS attack scenarios, demonstrating timely detection and isolation of V2I threats while maintaining platoon safety. The work highlights practical viability for real-time resilience and paves the way for hardware-in-the-loop test beds.

Abstract

A Connected Autonomous Vehicle (CAV) platoon in an evolving real-world driving environment relies strongly on accurate vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication for its safe and efficient operation. However, a cyberattack on this communication network can corrupt the appropriate control actions, tamper with system measurement, and drive the platoon to unsafe or undesired conditions. As a first step toward practicable resilience against such V2V-V2I attacks, in this paper, we implemented a unified V2V-V2I cyberattack detection scheme and a V2I isolation scheme for a CAV platoon under changing driving conditions in Simulation of Urban MObility (SUMO). The implemented algorithm utilizes vehicle-specific residual generators that are designed based on analytical disturbance-to-state stability, robustness, and sensitivity performance constraints. Our case studies include two driving scenarios where highway driving is simulated using the Next-Generation Simulation (NGSIM) data and urban driving follows the benchmark EPA Urban Dynamometer Driving Schedule (UDDS). The results validate the applicability of the algorithm to ensure CAV cybersecurity and demonstrate the promising potential for practical test-bed implementation in the future.

Assessment of Cyberattack Detection-Isolation Algorithm for CAV Platoons Using SUMO

TL;DR

The paper tackles cybersecurity in multi-modal CAV platoons by developing a unified V2V-V2I detection-isolation framework. It models a switching-mode ring-platoon and implements a two-phase scheme (V2X detection followed by V2I isolation) with per-vehicle detectors and isolators and theoretical guarantees. The approach is validated in a SUMO-TraCI-MATLAB setup using UDDS/NGSIM driving data, across FDI and DoS attack scenarios, demonstrating timely detection and isolation of V2I threats while maintaining platoon safety. The work highlights practical viability for real-time resilience and paves the way for hardware-in-the-loop test beds.

Abstract

A Connected Autonomous Vehicle (CAV) platoon in an evolving real-world driving environment relies strongly on accurate vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication for its safe and efficient operation. However, a cyberattack on this communication network can corrupt the appropriate control actions, tamper with system measurement, and drive the platoon to unsafe or undesired conditions. As a first step toward practicable resilience against such V2V-V2I attacks, in this paper, we implemented a unified V2V-V2I cyberattack detection scheme and a V2I isolation scheme for a CAV platoon under changing driving conditions in Simulation of Urban MObility (SUMO). The implemented algorithm utilizes vehicle-specific residual generators that are designed based on analytical disturbance-to-state stability, robustness, and sensitivity performance constraints. Our case studies include two driving scenarios where highway driving is simulated using the Next-Generation Simulation (NGSIM) data and urban driving follows the benchmark EPA Urban Dynamometer Driving Schedule (UDDS). The results validate the applicability of the algorithm to ensure CAV cybersecurity and demonstrate the promising potential for practical test-bed implementation in the future.

Paper Structure

This paper contains 10 sections, 5 equations, 5 figures.

Table of Contents

  1. INTRODUCTION
  2. PROBLEM STATEMENT
  3. Framework and CAV model
  4. Cyberattack policy
  5. DETECTION- ISOLATION ALGORITHM
  6. SUMO VALIDATION
  7. Case Study I: FDI attack through V2V network
  8. Case Study II: FDI attack through V2I network
  9. Case Study III: DoS attack through V2I network
  10. CONCLUSIONS

Figures (5)

  • Figure 1: Typical impacts of V2V and V2I attacks on CAV platoon.
  • Figure 2: Block diagram showing the communication between the SUMO-TraCI platform (representing the road topology, driving environment, CAV platoon and on-board controllers) and Matlab (representing the supervisory controller and detector-isolator system) for the simulation case studies.
  • Figure 3: Under V2V attack, the plot shows (top) the velocity, (second) the position, (third) the V2X DS residual, and (last) the V2I IS residual.
  • Figure 4: Under V2I attack, the plot shows (top) the velocity, (second) the position, (third) the V2X DS residual, and (last) the V2I IS residual.
  • Figure 5: Under V2I attack, the plot shows (top) the velocity, (second) the position, (third) the V2X DS residual, and (last) the V2I IS residual.