Adaptive Estimation-Based Safety-Critical Cruise Control of Vehicular Platoons

Optimal cruise control design can increase highway throughput and vehicle safety in traffic flow. In most heterogeneous platoons, the absence of vehicle-to-vehicle (V2V) communication poses challenges in maintaining system stability and ensuring a safe inter-vehicle distance. This paper presents an adaptive estimation-based control design for adaptive cruise control (ACC) that reliably estimates the states of the preceding vehicle while ensuring the autonomous vehicle operates within a safe region. Lyapunov functions and Control Barrier Functions (CBFs) are employed to design a safety-critical controller that guarantees safety despite potential estimation errors. The proposed unified control formulation addresses limitations in the existing cruise control solutions by simultaneously ensuring safety, stability, and optimal performance. The estimator-controller framework is implemented in scenarios with and without vehicle-to-vehicle communication, demonstrating successful performance in maintaining platoon safety and stability. Additionally, physics engine-based simulations reinforce both the practical viability of the proposed control framework in real-world situations and the controller's adeptness at maintaining safety amidst realistic operating conditions.