DocumentCode
2517502
Title
Drivable space characterization using automotive lidar and georeferenced map information
Author
Moras, Julien ; Rodriguez, F. Sergio A. ; Drevelle, Vincent ; Dherbomez, Gérald ; Cherfaoui, Véronique ; Bonnifait, Philippe
fYear
2012
fDate
3-7 June 2012
Firstpage
778
Lastpage
783
Abstract
The characterization in real-time of the drivable space in front of the vehicle is a key issue for safe autonomous navigation or driving assistance. This paper presents a method that uses a lidar (a multilayer laser scanner) integrated in the front bumper of an automotive vehicle. A grid processing is first applied to detect and localize objects in the immediate environment after having compensated the movement of the vehicle. Accurate map information is then introduced in the perception scheme to refine the characterization of the drivable space. The paper details the different processing stages necessary to implement this method and presents the design of the system that has been prototyped on board an experimental vehicle. We report real experiments carried out in challenging urban environments to illustrate the performance of this approach which has been evaluated thanks to a precise retro-projection of the estimated drivable space in a wide-angle scene camera.
Keywords
cameras; cartography; geophysical techniques; object detection; optical radar; path planning; road safety; road vehicle radar; road vehicles; sensor fusion; automotive lidar; automotive vehicle; drivable space characterization; driving assistance; front bumper; georeferenced map information; grid processing; multilayer laser scanner; multisensor fusion; object detection; object location; perception scheme; retro-projection; safe autonomous navigation; system design; urban environment; vehicle movement; wide-angle scene camera; Cameras; Global Positioning System; Laser radar; Roads; Robot sensing systems; Vehicles; Multi-sensor Fusion; Occupancy grids; Perception for Intelligent Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium (IV), 2012 IEEE
Conference_Location
Alcala de Henares
ISSN
1931-0587
Print_ISBN
978-1-4673-2119-8
Type
conf
DOI
10.1109/IVS.2012.6232252
Filename
6232252
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