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
Evaluating the Impact of Map Inaccuracies on Path Discrimination Behind Railway Turnouts
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-3599-5584
2022 (English)In: 95th IEEE Vehicular Technology Conference - Spring, VTC 2022, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference paper, Published paper (Refereed)
Abstract [en]

Determination of train positions within a railway network must be fail-safe and of high accuracy. In train-bourne positioning, exploitation of geometrical map features is an important factor and uncertainties in the map information may affect the position estimate. In this paper, we present a method to estimate the position of a train in the track net and to identify the correct path behind a turnout, using absolute position estimates and geometrical map information of various accuracies. We evaluate the impact of uncertainties in the map representation on the correct identification of a path behind a turnout. We derive a formulation of a probabilistic track map and include the map information into a constrained multi-hypothesis Kalman filter. We show in numerical simulations on a crossover and a turnout that modelling existing map uncertainties significantly improves the track discrimination.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022.
Series
IEEE Vehicular Technology Conference VTC
Keywords [en]
map matching, multi-hypothesis Kalman filter, train positioning, probabilistic track map
National Category
Transport Systems and Logistics Information Systems
Identifiers
URN: urn:nbn:se:kth:diva-321003DOI: 10.1109/VTC2022-Spring54318.2022.9860460ISI: 000861825800090Scopus ID: 2-s2.0-85137817458OAI: oai:DiVA.org:kth-321003DiVA, id: diva2:1708499
Conference
IEEE 95th Vehicular Technology Conference: (VTC-Spring), JUN 19-22, 2022, Helsinki, FINLAND
Note

Part of proceedings: ISBN 978-1-6654-8243-1

QC 20221104

Available from: 2022-11-04 Created: 2022-11-04 Last updated: 2022-11-04Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Löffler, WendiBengtsson, Mats

Search in DiVA

By author/editor
Löffler, WendiBengtsson, Mats
By organisation
Information Science and Engineering
Transport Systems and LogisticsInformation Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 66 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