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Trajectory Planning in Traffic Scenarios Using Support Vector Machines
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.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
2019 (English)In: IFAC PAPERSONLINE, ELSEVIER , 2019, Vol. 52, no 5, p. 91-96Conference paper, Published paper (Refereed)
Abstract [en]

Finding safe and collision free trajectories in an environment with moving obstacles is central for autonomous vehicles but at the same time a complex task. A reason is that the search space in space-time domain is very complex. This paper proposes a two-step approach where in first step, the search space for trajectory planning is simplified by solving a convex optimization problem formulated as a Support Vector Machine resulting in an obstacle free corridor that is suitable for a trajectory planner. Then, in a second step, a basic A* search strategy is used in the obstacle free search space. Due to the physical model used, the comfort and safety criteria are applied while searching the trajectory. The vehicle rollover prevention is used as a safety criterion and the acceleration, jerk and steering angle limits are used as comfort criteria. For simulations, urban environments with intersections and vehicles as moving obstacles are constructed. The properties of the approach are examined by the simulation results. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER , 2019. Vol. 52, no 5, p. 91-96
Keywords [en]
Autonomous Vehicles; Trajectory planning; Learning in autonomous vehicles; Support vector machines
National Category
Robotics
Identifiers
URN: urn:nbn:se:liu:diva-161216DOI: 10.1016/j.ifacol.2019.09.015ISI: 000486629500016OAI: oai:DiVA.org:liu-161216DiVA, id: diva2:1365650
Conference
9th IFAC International Symposium on Advances in Automotive Control (AAC)
Available from: 2019-10-25 Created: 2019-10-25 Last updated: 2019-10-25

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Morsali, MahdiÅslund, JanFrisk, Erik
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • 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