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Path Planning for Autonomous Bus Driving in Highly Constrained Environments
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-6802-7520
KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0003-1673-2671
KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems. KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-3672-5316
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2019 (English)In: 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 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
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
Identifiers
URN: urn:nbn:se:kth:diva-268930DOI: 10.1109/ITSC.2019.8916773OAI: oai:DiVA.org:kth-268930DiVA, id: diva2:1396860
Conference
2019 IEEE Intelligent Transportation Systems Conference (ITSC)
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Available from: 2020-02-26 Created: 2020-02-26 Last updated: 2020-02-26

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Oliveira, Rui Filipe De SousaLima, Pedro F.Pereira, Goncalo CollaresMårtensson, JonasWahlberg, Bo

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Oliveira, Rui Filipe De SousaLima, Pedro F.Pereira, Goncalo CollaresMårtensson, JonasWahlberg, Bo
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Decision and Control Systems (Automatic Control)Integrated Transport Research Lab, ITRLSignals, Sensors and SystemsBiomedical and X-ray PhysicsOptimization and Systems Theory
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