A Reconfigurable Framework for Vehicle Localization in Urban Areas
dc.contributor.author | Viana Guerediaga, Kerman | |
dc.contributor.author | Zubizarreta Pico, Asier | |
dc.contributor.author | Díez Sánchez, Mikel | |
dc.date.accessioned | 2022-04-21T11:00:26Z | |
dc.date.available | 2022-04-21T11:00:26Z | |
dc.date.issued | 2022-03-28 | |
dc.identifier.citation | Sensors 22(7) : (2022) // Article ID 2595 | es_ES |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10810/56380 | |
dc.description.abstract | Accurate localization for autonomous vehicle operations is essential in dense urban areas. In order to ensure safety, positioning algorithms should implement fault detection and fallback strategies. While many strategies stop the vehicle once a failure is detected, in this work a new framework is proposed that includes an improved reconfiguration module to evaluate the failure scenario and offer alternative positioning strategies, allowing continued driving in degraded mode until a critical failure is detected. Furthermore, as many failures in sensors can be temporary, such as GPS signal interruption, the proposed approach allows the return to a non-fault state while resetting the alternative algorithms used in the temporary failure scenario. The proposed localization framework is validated in a series of experiments carried out in a simulation environment. Results demonstrate proper localization for the driving task even in the presence of sensor failure, only stopping the vehicle when a fully degraded state is achieved. Moreover, reconfiguration strategies have proven to consistently reset the accumulated drift of the alternative positioning algorithms, improving the overall performance and bounding the mean error. | es_ES |
dc.description.sponsorship | This research was funded by the University of the Basque Country UPV/EHU, grants GIU19/045 and PIF19/181, and the Government of the Basque Country by grants IT914-16, KK-2021/00123 and IT949-16. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject | autonomous vehicle | es_ES |
dc.subject | robust localization | es_ES |
dc.subject | reconfiguration | es_ES |
dc.subject | sensor fusion | es_ES |
dc.title | A Reconfigurable Framework for Vehicle Localization in Urban Areas | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2022-04-11T13:59:34Z | |
dc.rights.holder | 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/22/7/2595/htm | es_ES |
dc.identifier.doi | 10.3390/s22072595 | |
dc.departamentoes | Ingeniería de sistemas y automática | |
dc.departamentoes | Ingeniería mecánica | |
dc.departamentoeu | Sistemen ingeniaritza eta automatika | |
dc.departamentoeu | Ingeniaritza mekanikoa |
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Except where otherwise noted, this item's license is described as 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).