2020/10/14 by Rui Oliveira, Oskar Ljungqvist, Oliveira, Rui +7 · 1 citation
Computer Science · Engineering · #Autonomous Vehicle Technology and Safety #FOS: Computer and information sciences #FOS: Electrical engineering #Robotic Path Planning Algorithms #Robotics (cs.RO) #Systems and Control (eess.SY) #Vehicle Dynamics and Control Systems #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2010.07133
openalex publication_date 2020/10/14 · openalex created_date 2020/10/22 · openalex updated_date 2026/07/28
Driving heavy-duty vehicles, such as buses and tractor-trailer vehicles, is a difficult task in comparison to passenger cars. Most research on motion planning for autonomous vehicles has focused on passenger vehicles, and many unique challenges associated with heavy-duty vehicles remain open. However, recent works have started to tackle the particular difficulties related to on-road motion planning for buses and tractor-trailer vehicles using numerical optimization approaches. In this work, we propose a framework to design an optimization objective to be used in motion planners. Based on geometric derivations, the method finds the optimal trade-off between the conflicting objectives of centering different axles of the vehicle in the lane. For the buses, we consider the front and rear axles trade-off, whereas for articulated vehicles, we consider the tractor and trailer rear axles trade-off. Our results show that the proposed design strategy results in planned paths that considerably improve the behavior of heavy-duty vehicles by keeping the whole vehicle body in the center of the lane.