Abstract
This paper presents a path planning method for the lane change maneuver of a full-sized autonomous driving bus in urban environment. A sampling method is incorporated for lane change path planning. Path candidates for lane changes are generated using the pattern of a quintic polynomial function. For optimal path selection among the candidates, a cost function and constraints are designed and applied, considering ride quality, lane change efficiency, and safety. Safety conditions account for lane departure and collision with obstacles. Considering large vehicles such as buses, the region swept by the vehicle body is derived by exploiting the geometrical relationship of the control point and corners, assuming that the control point follows the investigated path candidate. The sweeping region is utilized for accurate and efficient evaluation of the safety condition of the path candidate. Subsequently, longitudinal motion is planned based on Model Predictive Control (MPC) to maintain adequate clearance with surrounding vehicles and follow the desired speed. The proposed algorithm has been evaluated based on closed-loop simulations and vehicle-in-the-loop tests. The test results show that the proposed algorithm plans a safe lane change path, ensuring the vehicle body remains within the safe region. Additionally, the proposed algorithm is shown to enhance real-time performance.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call