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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Communication dans un congrès
IEEE International Symposium on Intelligent Vehicles, Jun 2011, Baden-baden, Germany. 2011
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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. 2011. 〈inria-00635779〉

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