kth.sePublications KTH
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
Evaluating Sequential Reasoning about Hidden Objects in Traffic
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL. Scania CV AB.ORCID iD: 0000-0002-2069-6581
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0001-9982-578X
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0001-7461-920X
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-4173-2593
Show others and affiliations
2022 (English)In: ICCPS '22: Proceedings of the 13th ACM/IEEE International Conference on Cyber-Physical Systems, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Hidden traffic participants pose a great challenge for autonomous vehicles. Previous methods typically do not use previous observations, leading to over-conservative behavior. In this paper, we present a continuation of our work on reasoning about objects outside the current sensor view. We aim to demonstrate our recently proposed method on an autonomous platform and evaluate its reliability and real-time feasibility when using real sensor data. Showing a significant driving performance increase on a real platform, without compromising safety, would be a significant contribution to the field of autonomous driving.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022.
Keywords [en]
Autonomous Vehicles, Hidden Traffic Participants, Traffic Occlusions, Motion Planning, Reachability Analysis, Safe Autonomy
National Category
Robotics and automation
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-310427DOI: 10.1109/ICCPS54341.2022.00044ISI: 000851578700038Scopus ID: 2-s2.0-85134248642OAI: oai:DiVA.org:kth-310427DiVA, id: diva2:1648442
Conference
ACM/IEEE International Conference on Cyber-Physical Systems, Milan ’22, May 04–06, 2022, Milan, Italy
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Vinnova
Note

QC 20221004

Available from: 2022-03-30 Created: 2022-03-30 Last updated: 2025-02-09Bibliographically approved

Open Access in DiVA

fulltext(2332 kB)375 downloads
File information
File name FULLTEXT01.pdfFile size 2332 kBChecksum SHA-512
f2706d013f4397ec26770fb8936e08b7ba00c2e27dd3068659e3cae91d5b12c0dc3507dfb01c94131e15192f5d8bec9b0e14efe060830b3f71decb0e91cefa91
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Nyberg, TrulsGaspar Sánchez, José ManuelPek, ChristianTumova, JanaTörngren, Martin

Search in DiVA

By author/editor
Nyberg, TrulsGaspar Sánchez, José ManuelPek, ChristianTumova, JanaTörngren, Martin
By organisation
Robotics, Perception and Learning, RPLMechatronics
Robotics and automation

Search outside of DiVA

GoogleGoogle Scholar
Total: 375 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 790 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