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Geometrical Based Trajectory Calculation for Autonomous Vehicles in Multi-Vehicle Traffic Scenarios
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-7349-1937
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
2021 (English)In: 2021 32ND IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), IEEE , 2021, p. 1235-1242Conference paper, Published paper (Refereed)
Abstract [en]

A computationally cheap method for computing collision-free trajectories with multiple moving obstacles is proposed here while meeting comfort and safety criteria. By avoiding search in the trajectory calculation and instead using a geometrical set to calculate the trajectory, the calculation time is significantly reduced. The geometrical set is calculated by solving a support vector machine problem and solving the SVM problem characterizes maximum separating surfaces between obstacles and the ego vehicle in the time-space domain. The trajectory on the separating surface might not be kinematically feasible. Therefore, a vehicle model and a Newton-Raphson based procedure is proposed to obtain a safe, kinematically feasible trajectory on the separating surface. A roundabout scenario and two take-over scenarios with different configurations are used to investigate the properties of the proposed algorithm. Robustness properties of the proposed algorithm is investigated by a large number of randomly initiated simulation scenarios.

Place, publisher, year, edition, pages
IEEE , 2021. p. 1235-1242
Series
IEEE Intelligent Vehicles Symposium, ISSN 1931-0587
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:liu:diva-184758DOI: 10.1109/IV48863.2021.9575957ISI: 000782373100177ISBN: 9781728153940 (electronic)OAI: oai:DiVA.org:liu-184758DiVA, id: diva2:1657592
Conference
32nd IEEE Intelligent Vehicles Symposium (IV), ELECTR NETWORK, jul 11-17, 2021
Available from: 2022-05-11 Created: 2022-05-11 Last updated: 2022-05-11

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Morsali, MahdiFrisk, ErikÅslund, Jan
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Total: 114 hits
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