In this paper we present a technique that takes advantage of detected building façades and OpenStreetMaps data to improve the localization of an autonomous vehicle driving in an urban scenario. The proposed approach leverages images from a stereo rig mounted on the vehicle to produce a mathematical representation of the buildings' façades within the field of view. This representation is matched against the outlines of the surrounding buildings as they are available on OpenStreetMaps. The information is then fed into our probabilistic framework, called Road Layout Estimation, in order to produce an accurate lane-level localization of the vehicle. The experiments conducted on the well-known KITTI datasets prove the effectiveness of our approach.

Ballardini, A., Cattaneo, D., Fontana, S., Sorrenti, D. (2016). Leveraging the OSM building data to enhance the localization of an urban vehicle. In 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) (pp.622-628). Institute of Electrical and Electronics Engineers Inc. [10.1109/ITSC.2016.7795618].

Leveraging the OSM building data to enhance the localization of an urban vehicle

BALLARDINI, AUGUSTO LUIS
Primo
;
CATTANEO, DANIELE
Secondo
;
FONTANA, SIMONE
Penultimo
;
SORRENTI, DOMENICO GIORGIO
Ultimo
2016

Abstract

In this paper we present a technique that takes advantage of detected building façades and OpenStreetMaps data to improve the localization of an autonomous vehicle driving in an urban scenario. The proposed approach leverages images from a stereo rig mounted on the vehicle to produce a mathematical representation of the buildings' façades within the field of view. This representation is matched against the outlines of the surrounding buildings as they are available on OpenStreetMaps. The information is then fed into our probabilistic framework, called Road Layout Estimation, in order to produce an accurate lane-level localization of the vehicle. The experiments conducted on the well-known KITTI datasets prove the effectiveness of our approach.
No
slide + paper
Scene Understanding, Autonomous Driving, Cartographic Maps, OpenStreetMap, Global Positioning System, Layout, Probabilistic logic, Roads, Sensors, Vehicles, Buildings
English
Intelligent Transportation Systems (ITSC), 2016 IEEE 19th International Conference on
9781509018895
http://ieeexplore.ieee.org/document/7795618/
Ballardini, A., Cattaneo, D., Fontana, S., Sorrenti, D. (2016). Leveraging the OSM building data to enhance the localization of an urban vehicle. In 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) (pp.622-628). Institute of Electrical and Electronics Engineers Inc. [10.1109/ITSC.2016.7795618].
Ballardini, A; Cattaneo, D; Fontana, S; Sorrenti, D
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/141527
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