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Conference Papers Year : 2011

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

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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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Dates and versions

inria-00635779 , version 1 (25-10-2011)

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  • HAL Id : inria-00635779 , version 1

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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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