Probabilistic error model for a lane marking based vehicle localization coupled to open source maps
| Autor: | Roger Reynaud, Wenjie Lu, A F Sergio Rodriguez, Emmanuel Seignez |
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| Přispěvatelé: | Université Paris-Sud - Paris 11 (UP11), Institut d'électronique fondamentale (IEF), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Rodriguez Florez, Sergio Alberto |
| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | ITSC 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC) 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), Oct 2014, Qingdao, China |
| DOI: | 10.1109/itsc.2014.6957717 |
| Popis: | International audience; —Recent works have focused on lane marking feature based vehicle localization using enriched maps. The localization precision of existing methods depends strongly on the accuracy of the maps which are specially customized. In this article, we propose a marking feature based vehicle localization using open source map. Our method makes use of multi-criterion confidences to infer potential errors, and in advance, to en-hance the vehicle localization. At first, the vision-based lane marking models are obtained. Meanwhile, the map-based lane markings of current state are derived from map databases. Both lane marking sources are fused together to implement vehicle localization, using a multi-kernel based algorithm. In order to further improve the localization performance, a probabilistic error model is employed to identify the possible errors. The experiments have been carried out on public database. The results show that error modeling leads to a lower average lateral error in localization result. |
| Databáze: | OpenAIRE |
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