A Robust CACC Scheme Against Cyberattacks via Multiple Vehicle-to-Vehicle Networks

Cooperative Adaptive Cruise Control (CACC) is a vehicular technology that allows groups of vehicles on the highway to form in closely-coupled automated platoons to increase highway capacity and safety. The underlying mechanism behind CACC is the use of Vehicle-to-Vehicle (V2V) wireless communication networks to transmit acceleration commands to adjacent vehicles in the platoon. However, the use of V2V networks leads to increased vulnerabilities against faults and cyberattacks. Here, we address the problem of increasing the robustness of CACC schemes against cyberattacks by using multiple V2V networks and a data fusion algorithm. The idea is to transmit acceleration commands multiple times through different communication channels to create redundancy at the receiver side. We propose a data fusion algorithm to estimate of the true acceleration command, and isolate compromised channels. Finally, we propose a robust
$H_{\infty }$
controller that reduces the joint effect of fusion errors and sensor/channel noise in the platooning performance (tracking performance and string stability). Simulation results are presented to illustrate the performance of our approach.