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This paper develops a new control design for guaranteeing a vehicle's safetyduring lane change maneuvers in a complex traffic environment. The proposedmethod uses a finite state machine (FSM), where a quadratic program basedoptimization problem using control Lyapunov functions and control barrierfunctions (CLF-CBF-QP) is used to calculate the system's optimal inputs viarule-based control strategies. The FSM can make switches between differentstates automatically according to the command of driver and trafficenvironment, which makes the ego vehicle find a safe opportunity to do acollision-free lane change maneuver. By using a convex quadratic program, thecontroller can guarantee the system's safety at a high update frequency. A setof pre-designed typical lane change scenarios as well as randomly generateddriving scenarios are simulated to show the performance of our controller.

Rule-Based Safety-Critical Control Design using Control Barrier Functions with Application to Autonomous Lane Change