  This paper develops a new control design for guaranteeing a vehicle's safety
during lane change maneuvers in a complex traffic environment. The proposed
method uses a finite state machine (FSM), where a quadratic program based
optimization problem using control Lyapunov functions and control barrier
functions (CLF-CBF-QP) is used to calculate the system's optimal inputs via
rule-based control strategies. The FSM can make switches between different
states automatically according to the command of driver and traffic
environment, which makes the ego vehicle find a safe opportunity to do a
collision-free lane change maneuver. By using a convex quadratic program, the
controller can guarantee the system's safety at a high update frequency. A set
of pre-designed typical lane change scenarios as well as randomly generated
driving scenarios are simulated to show the performance of our controller.
