Attack-Resilient Event-Triggered Control of Vehicle Speed Tracking System With DoS Attacks: Experimental Results

This paper presents an attack-resilient event-triggered mechanism (AETM) control for the longitudinal speed tracking of connected vehicles, addressing the issue of communication data saturation in the in-vehicle controller area network (CAN) caused by denial of service (DoS) attacks. In current studies, compensation data is transmitted after DoS attacks based on known attack statistics. Additionally, compensating data during DoS attacks may lead to significant performance loss in systems and CAN bus-off. To address this, an AETM is proposed to alleviate CAN data saturation during DoS attacks, at the cost of reductions in critical data. To accommodate infrequent critical data induced by the AETM, a new robust controller is designed aiming to minimize performance loss. The closed-loop discrete-time model is developed with attack-induced uncertainties and event-triggered instants which vary with DoS attacks. Then, the controller gain can be obtained by solving a series of linear matrix inequalities (LMIs) with Matlab LMI tool box and particle swarm optimization (PSO) algorithm. Finally, hardware-in-the-loop (HiL) experiments demonstrate the effectiveness of the proposed method in mitigating CAN data saturation and improving vehicle safety under DoS attacks.