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Conference papers

Fusion of Telemetric and Visual Data from Road Scenes with a Lexus Experimental Platform

Igor Paromtchik 1 Mathias Perrollaz 1 Christian Laugier 1
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Fusion of telemetric and visual data from traffic scenes helps exploit synergies between different on-board sensors, which monitor the environment around the ego-vehicle. This paper outlines our approach to sensor data fusion, detection and tracking of objects in a dynamic environment. The approach uses a Bayesian Occupancy Filter to obtain a spatio-temporal grid representation of the traffic scene. We have implemented the approach on our experimental platform on a Lexus car. The data is obtained in traffic scenes typical of urban driving, with multiple road participants. The data fusion results in a model of the dynamic environment of the ego-vehicle. The model serves for the subsequent analysis and interpretation of the traffic scene to enable collision risk estimation for improving the safety of driving.
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Submitted on : Tuesday, October 25, 2011 - 7:21:12 PM
Last modification on : Thursday, October 21, 2021 - 3:45:49 AM
Long-term archiving on: : Thursday, January 26, 2012 - 2:45:29 PM


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  • HAL Id : inria-00635779, version 1



Igor Paromtchik, Mathias Perrollaz, Christian Laugier. Fusion of Telemetric and Visual Data from Road Scenes with a Lexus Experimental Platform. IEEE International Symposium on Intelligent Vehicles, Jun 2011, Baden-baden, Germany. ⟨inria-00635779⟩



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