Predictive Collision Avoidance Control with Optimized Ride Comfort in Vehicle Lateral Motion Control

This study aims to propose how autonomous vehicle overtakes an obstacle with model predictive control and makes a lateral ride comfortability by optimizing a jerk in a lateral direction. In this paper, we conducted a case study on collision avoidance in a waypoint tracking situation. To avoid the obstacle, we proposed a desired lateral offset from the global route and used the offset as a reference for avoidance. Then, we defined a quadratic cost function considering the jerk to minimize a motion sickness during the avoidance maneuver. To verify the method, we executed a computational simulation using actual waypoint data. As a result, we observed that the proposed scheme has more comfortability for obstacle avoidance than the method without optimizing the jerk.