Spatio-Temporal Corridor-Based Motion Planning of Lane Change Maneuver for Autonomous Driving in Multi-Vehicle Traffic

This paper presents a methodology of lane change motion planning based on spatio-temporal corridor for autonomous driving in multi-vehicle traffic environments. The spatio-temporal corridor is constructed based on the prediction results of surrounding vehicles. For lane change decision making, the target lane change space is determined by investigating the feasibility and space sufficiency using the spatio-temporal corridor. The set of lane crossing time which enables the safe lane change is calculated in the feasibility investigation process. The feasibility investigation secures the consistency of the decision making and motion planning. The lane change motion planning algorithm incorporates decoupled lateral and longitudinal dynamics. The lateral motion is planned based on a sampling method which refers to the lane crossing time set. Subsequently, the longitudinal motion is planned using Model Predictive Control (MPC), taking into account the results of the lateral motion planning. Simulation studies have been conducted to investigate the performance of the proposed lane change algorithm. The proposed algorithm has been implemented in our test vehicle and validated via autonomous driving tests. The vehicle test results show that the proposed algorithm plans the lane change motion safely with proper ride quality.