Path planning for autonomous bus driving in highly constrained environmentsShow others and affiliations
2019 (English)In: Proceedings 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Institute of Electrical and Electronics Engineers (IEEE) , 2019, p. 2743-2749Conference paper, Published paper (Refereed)
Abstract [en]
Driving in urban environments often presents difficult situations that require expert maneuvering of a vehicle. These situations become even more challenging when considering large vehicles, such as buses. We present a path planning framework that addresses the demanding driving task of buses in highly constrained environments, such as urban areas. The approach is formulated as an optimization problem using the road-aligned vehicle model. The road-aligned frame introduces a distortion on the vehicle body and obstacles, motivating the development of novel approximations that capture this distortion. These approximations allow for the formulation of safe and accurate collision avoidance constraints. Unlike other path planning approaches, our method exploits curbs and other sweepable regions, which a bus must often sweep over in order to manage certain maneuvers. Furthermore, it takes full advantage of the particular characteristics of buses, namely the overhangs, an elevated part of the vehicle chassis, that can sweep over curbs. Simulations are presented, showing the applicability and benefits of the proposed method.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2019. p. 2743-2749
Keywords [en]
collision avoidance, mobile robots, optimisation, path planning, road vehicles, vehicle dynamics, optimization problem, road-aligned vehicle model, road-aligned frame, vehicle body, collision avoidance constraints, path planning approaches, vehicle chassis, autonomous bus driving, path planning framework, urban areas, Roads, Optimization, Path planning, Nonlinear distortion, Collision avoidance, Planning
National Category
Robotics and automation
Identifiers
URN: urn:nbn:se:kth:diva-268930DOI: 10.1109/ITSC.2019.8916773ISI: 000521238102127Scopus ID: 2-s2.0-85076813702OAI: oai:DiVA.org:kth-268930DiVA, id: diva2:1396860
Conference
IEEE Intelligent Transportation Systems Conference, ITSC 2019, Auckland, New Zealand, October 27-30, 2019
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Note
QC 20200625
Part of ISBN 978-1-5386-7024-8, 978-1-5386-7025-5
2020-02-262020-02-262025-02-09Bibliographically approved