Attack Detection and Defense System Using an Unknown Input Observer for Cooperative Adaptive Cruise Control Systems
Yudai Yamamoto, Naomi Kuze, Toshimitsu Ushio
Abstract
Cooperative adaptive cruise control (CACC) is a technology for the automated control of platoons of vehicles. CACC controls the behavior of vehicles based on information that is shared among the vehicles through vehicle-to-vehicle (V2V) communication. However, cyberattacks on V2V communication can degrade the control performance and may cause serious accidents such as vehicle collisions; therefore, it is important to improve the resilience against such attacks. In this paper, we propose a novel attack detection and defense mechanism for CACC. Our approach is based on an unknown input observer (UIO), which estimates vehicle states by treating the unreliable information obtained through V2V communication as unknown inputs. Attacks on V2V communication are detected from the estimated states. When an attack is detected, the control method is switched to a secure method. Through simulation experiments, we show that the proposed mechanism can detect attacks immediately and accurately, allowing the stability of the platoon to be maintained.