Congestion transition in intelligent driver model with fault-tolerant control to counter cyber-attacks during the lane-changing process under a connected autonomous vehicles platform

In a vehicle-to-everything (V2X) environment, cyber-attacks pose grave security risks to the lane-changing (LC) behaviors of connected automated vehicles (CAVs). To probe deeper into how cyber-attacks impact the LC behaviors of CAVs adhering to the Minimizing Overall Braking Induced by Lane Changes (MOBIL) model, we constructed a novel Intelligent Driver Model (IDM). This model integrates fault-tolerant control to effectively counteract cyber-attacks, including bogus message attacks and collusion attacks. Theoretical analysis reveals that the linear stability condition is intimately linked with cyber-attack vulnerabilities. Simulation results demonstrate that various cyber-attack types inflict pervasive disruption on both LC and car-following (CF) behaviors of CAVs. Crucially, fault-tolerant control significantly mitigates cyber-attack-induced variations in trajectory and speed. Furthermore, we employ two distinct safety evaluation criteria to rigorously assess the efficacy of fault-tolerant control in resisting cyber-attacks.