Event-Driven Safe and Resilient Control of Automated and Human-Driven Vehicles under EU-FDI Attacks

TL;DR

This paper introduces an event-driven control framework for connected and automated vehicles that ensures safety and resilience against false data injection attacks, especially during lane-changing maneuvers with unpredictable human-driven vehicles.

Contribution

It proposes an innovative event-driven control approach combining barrier and Lyapunov functions with adaptive attack resilience and data-driven behavior estimation.

Findings

Effective collision avoidance under EU-FDI attacks

Reduced computational load with event-driven approach

Robust lane-changing maneuvers demonstrated in simulations

Abstract

This paper studies the safe and resilient control of Connected and Automated Vehicles (CAVs) operating in mixed traffic environments where they must interact with Human-Driven Vehicles (HDVs) under uncertain dynamics and exponentially unbounded false data injection (EU-FDI) attacks. These attacks pose serious threats to safety-critical applications. While resilient control strategies can mitigate adversarial effects, they often overlook collision avoidance requirements. Conversely, safety-critical approaches tend to assume nominal operating conditions and lack resilience to adversarial inputs. To address these challenges, we propose an event-driven safe and resilient (EDSR) control framework that integrates event-driven Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) with adaptive attack-resilient control. The framework further incorporates data-driven estimation of HDV behaviors to ensure safety and resilience against EU-FDI attacks. Specifically, we focus on the lane-changing maneuver of CAVs in the presence of unpredictable HDVs and EU-FDI attacks on acceleration inputs. The event-driven approach reduces computational load while maintaining real-time safety guarantees. Simulation results, including comparisons with conventional safety-critical control methods that lack resilience, validate the effectiveness and robustness of the proposed EDSR framework in achieving collision-free maneuvers, stable velocity regulation, and resilient operation under adversarial conditions.