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

Abstract

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.