Real Time Trajectory Re-planning for Autonomous Vehicle Lane Changing in Uncertain Traffic

Abstract

Lane changing is a common working scenario for autonomous vehicles. This paper proposes a safe and comfortoriented planning algorithm for an autonomous vehicle to perform lane changes on a straight and level road. Gray Prediction Model is used to estimate the driving status of surrounding vehicles, and time-variant safety margins are used during quadratic trajectory planning and executing. The algorithm is able to adapt its lane changing strategy based on traffic situation and passenger demands, and features condition-triggered re-planning to handle unexpected traffic situations.