Winter, Hanno ; Willert, Volker ; Adamy, Jürgen (2022)
Increasing Accuracy in Train Localization Exploiting Track-Geometry Constraints.
21st International Conference on Intelligent Transportation Systems (ITSC). Maui, HI, USA (04.-07.11.2018)
doi: 10.26083/tuprints-00020410
Konferenzveröffentlichung, Zweitveröffentlichung, Postprint
Kurzbeschreibung (Abstract)
Train-borne localization systems as a key component of future signalling systems are expected to offer huge economic and operational advances for the railway transportation sector. However, the reliable provision of a track-selective and constantly available location information is still unsolved and prevents the introduction of such systems so far. A contribution to overcome this issue is presented here. We show a recursive multistage filtering approach with an increased cross-track positioning accuracy, which is decisive to ensure track-selectivity. This is achieved by exploiting track-geometry constraints known in advance, as there are strict rules for the construction of railway tracks. Additionally, compact geometric track-maps can be extracted during the filtering process which are beneficial for existing train localization approaches. The filter was derived applying approximate Bayesian inference. The geometry constraints are directly incorporated in the filter design, utilizing an interacting multiple model (IMM) filter and extended Kalman filters (EKF). Throughout simulations the performance of the filter is analyzed and discussed thereafter.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Winter, Hanno ; Willert, Volker ; Adamy, Jürgen |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Increasing Accuracy in Train Localization Exploiting Track-Geometry Constraints |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Ort: | Darmstadt |
| Verlag: | IEEE |
| Kollation: | 8 ungezählte Seiten |
| Veranstaltungstitel: | 21st International Conference on Intelligent Transportation Systems (ITSC) |
| Veranstaltungsort: | Maui, HI, USA |
| Veranstaltungsdatum: | 04.-07.11.2018 |
| DOI: | 10.26083/tuprints-00020410 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/20410 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | Train-borne localization systems as a key component of future signalling systems are expected to offer huge economic and operational advances for the railway transportation sector. However, the reliable provision of a track-selective and constantly available location information is still unsolved and prevents the introduction of such systems so far. A contribution to overcome this issue is presented here. We show a recursive multistage filtering approach with an increased cross-track positioning accuracy, which is decisive to ensure track-selectivity. This is achieved by exploiting track-geometry constraints known in advance, as there are strict rules for the construction of railway tracks. Additionally, compact geometric track-maps can be extracted during the filtering process which are beneficial for existing train localization approaches. The filter was derived applying approximate Bayesian inference. The geometry constraints are directly incorporated in the filter design, utilizing an interacting multiple model (IMM) filter and extended Kalman filters (EKF). Throughout simulations the performance of the filter is analyzed and discussed thereafter. |
| Status: | Postprint |
| URN: | urn:nbn:de:tuda-tuprints-204102 |
| Zusätzliche Informationen: | Keywords: Geometry, Rail transportation, Hidden Markov models, Tracking, Bayes methods, Global navigation satellite system, Reliability |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Regelungsmethoden und Robotik (ab 01.08.2022 umbenannt in Regelungsmethoden und Intelligente Systeme) |
| Hinterlegungsdatum: | 01 Feb 2022 13:16 |
| Letzte Änderung: | 03 Feb 2022 13:41 |
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