Influence of cyber-attacks on longitudinal safety of connected and automated vehicles

Connected and automated vehicle (CAV) has been a remarkable focal point in recent years, since it is recognized as a potential method to reduce traffic congestion, emission and accident. However, the connectivity function makes CAVs vulnerable to cyber-attacks. An intuitive method to defend cyber-attacks on CAVs is that if the error between expected and measured behaviors exceeds a predetermined threshold, a security scheme should be activated. This study investigates another type of cyber-attack, denoted as slight attacks, in which the communicated data of CAVs are randomly deviated from the actual ones and deviations do not exceed the threshold. The primary objective is to evaluate the influence of slight cyber-attacks on longitudinal safety of CAVs. An empirical CAV model is first utilized to describe vehicle dynamics and generate trajectory data. A rear-end collision risk index (RCRI) derived from safe stopping distance is used to establish relation between longitudinal safety and trajectory data. Two attacked factors, communicated positions and speeds from preceding vehicles are tested. Extensive simulations are conducted and parameters are also tested via sensitivity analysis. Results indicate that (1) when one CAV is under slight cyber-attacks, it is more dangerous if communicated positions are attacked than speeds; (2) when multi CAVs are under attacked, it is possible that a situation with more vehicles under attack at a low severity may be more dangerous than that with fewer vehicles but under attack at a high severity; (3) the impact of slight cyber-attacks on deceleration period is more serious compared to acceleration period. The findings of this study provide useful suggestion for defending cyber-attacks on CAVs and improving longitudinal safety in the future.