Optimizing Autonomous Vehicle Safety and Performance: Advanced CLF-CBF Integration for Adaptive Cruise Control

This article addresses the challenges associated with the safety and performance of autonomous vehicles. Passenger safety and comfort are enhanced through the optimization of advanced driver assistance systems (ADAS), such as adaptive cruise control (ACC). A new longitudinal controller has been developed using Control Lyapunov Functions (CLF) and high-order Control Barrier Functions (CBF). This controller imposes strict safety constraints and integrates Lyapunov functions for an efficient adaptive cruise control system. The proposed CLF-CBF methodology significantly improves the adaptability and efficiency of vehicle control systems, particularly in speed regulation and stop-and-go scenarios. The approach has been validated through numerical simulations, demonstrating its effectiveness in achieving safety and control objectives.