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A Geometric Approach to On-road Motion Planning for Long and Multi-Body Heavy-Duty Vehicles
KTH Royal Inst Technol, Sweden; Scania CV AB, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-1795-5992
Scania CV AB, Sweden.
KTH Royal Inst Technol, Sweden.
2020 (English)In: 2020 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), IEEE , 2020, p. 999-1006Conference paper, Published paper (Refereed)
Abstract [en]

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 produces planned paths that considerably improve the behavior of heavy-duty vehicles by keeping the whole vehicle body in the center of the lane.

Place, publisher, year, edition, pages
IEEE , 2020. p. 999-1006
Series
IEEE Intelligent Vehicles Symposium, ISSN 1931-0587
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:liu:diva-177409DOI: 10.1109/IV47402.2020.9304767ISI: 000653124200150ISBN: 9781728166735 (print)OAI: oai:DiVA.org:liu-177409DiVA, id: diva2:1574011
Conference
31st IEEE Intelligent Vehicles Symposium (IV), ELECTR NETWORK, jun 23-26, 2020
Note

Funding Agencies|Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

Available from: 2021-06-28 Created: 2021-06-28 Last updated: 2021-12-28

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf