In this paper we present a general framework for urban road layout estimation, altogether with a specific application to the vehicle localization problem. The localization is performed by synergically exploiting data from different sensors, as well as map-matching with OpenStreetMap cartographic maps. The effectiveness is proven by achieving real-time computation with state-of-the-art results on a set of ten not trivial runs from the KITTI dataset, including both urban/residential and highway/road scenarios. Although this paper represents a first step implementation towards a more general urban scene understanding framework, here we prove its flexibility of application to different intelligent vehicles applications.
Ballardini, A., Fontana, S., Furlan, A., Limongi, D., Sorrenti, D. (2015). A Framework for Outdoor Urban Environment Estimation. In Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on (pp.2721-2727). Institute of Electrical and Electronics Engineers Inc. [10.1109/ITSC.2015.437].
A Framework for Outdoor Urban Environment Estimation
BALLARDINI, AUGUSTO LUISPrimo
;FONTANA, SIMONEPenultimo
;FURLAN, AXELSecondo
;SORRENTI, DOMENICO GIORGIOUltimo
2015
Abstract
In this paper we present a general framework for urban road layout estimation, altogether with a specific application to the vehicle localization problem. The localization is performed by synergically exploiting data from different sensors, as well as map-matching with OpenStreetMap cartographic maps. The effectiveness is proven by achieving real-time computation with state-of-the-art results on a set of ten not trivial runs from the KITTI dataset, including both urban/residential and highway/road scenarios. Although this paper represents a first step implementation towards a more general urban scene understanding framework, here we prove its flexibility of application to different intelligent vehicles applications.File | Dimensione | Formato | |
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