Analyzing the impact of false-accident cyber attacks on traffic flow stability in connected vehicle environment

With the rapid development of connected vehicle (CV) technologies, cyber security issues in the vehicular network has emerged as serious concerns for successful deployment of CV systems. In the existing literature, the analysis of the cyber security impacts has been primarily focused from the computer science perspectives investigating potential attacking scenarios and counter-measures through network security strategies. In this paper, we investigate traffic impacts of cyber attacks considering real-world driver behavior, especially the “built-in” safety redundancy of the visual verification by drivers or autonomous driving system. More specifically, we study the impact of “false-accident” attacks on the stability of traffic flow. In the false-accident attack, a vehicle sends out a false accident alert to its surrounding vehicle through CV-enabled network and has considered an attacking scenario that has catastrophic effects. Traffic flow stability is based on widely-used numerical linear stability analysis methods, the ring road test. In such a test, vehicles are restricted within a ring road so that traffic congestion and perturbations appear in cyclic patterns indicating the stability of traffic flow. The study indicates that false-accident attacks do not necessarily yield significant impact on the stability of traffic flow. Sensitivity analysis is conducted by varying the attacking duration, the attacking vehicle position in a platoon, and the CV safety application reaction range.