kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
Using Reachable Sets for Trajectory Planning of Automated Vehicles
Tech Univ Munich, Dept Informat, D-85748 Garching, Germany..
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0001-7461-920x
Tech Univ Munich, Dept Informat, D-85748 Garching, Germany..
2021 (English)In: IEEE Transactions on Intelligent Vehicles, ISSN 2379-8858, E-ISSN 2379-8904, Vol. 6, no 2, p. 232-248Article in journal (Refereed) Published
Abstract [en]

The computational effort of trajectory planning for automated vehicles often increases with the complexity of the traffic situation. This is particularly problematic in safety-critical situations, in which the vehicle must react in a timely manner. We present a novel motion planning approach for automated vehicles, which combines set-based reachability analysis with convex optimization to address this issue. This combination makes it possible to find driving maneuvers even in small and convoluted solution spaces. In contrast to existing work, the computation time of our approach typically decreases, the more complex situations become. We demonstrate the benefits of our motion planner in scenarios from the CommonRoad benchmark suite and validate the approach on a real test vehicle.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. Vol. 6, no 2, p. 232-248
Keywords [en]
Planning, Trajectory, Reachability analysis, Trajectory planning, Complexity theory, Space vehicles, Collision avoidance, Automated vehicles, optimization
National Category
Robotics and automation
Identifiers
URN: urn:nbn:se:kth:diva-304840DOI: 10.1109/TIV.2020.3017342ISI: 000710540200009Scopus ID: 2-s2.0-85090949859OAI: oai:DiVA.org:kth-304840DiVA, id: diva2:1612836
Note

QC 20211119

Available from: 2021-11-19 Created: 2021-11-19 Last updated: 2025-02-09Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Pek, Christian

Search in DiVA

By author/editor
Pek, Christian
By organisation
Robotics, Perception and Learning, RPL
In the same journal
IEEE Transactions on Intelligent Vehicles
Robotics and automation

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 167 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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