Title: Vehicle recognition and tracking using a generic multisensor and multialgorithm fusion approach

Authors: Fawzi Nashashibi, Ayoub Khammari, Claude Laurgeau

Addresses: Robotics Centre – Ecole des Mines de Paris, 60 Boulevard Saint-Michel, Paris Cedex 06, 75 272, France. ' Robotics Centre –– Ecole des Mines de Paris, 60 Boulevard Saint-Michel, Paris Cedex 06, 75 272, France. ' Robotics Centre – Ecole des Mines de Paris, 60 Boulevard Saint-Michel, Paris Cedex 06, 75 272, France

Abstract: This paper tackles the problem of improving the robustness of vehicle detection for Adaptive Cruise Control (ACC) applications. Our approach is based on a multisensor and a multialgorithms data fusion for vehicle detection and recognition. Our architecture combines two sensors: a frontal camera and a laser scanner. The improvement of the robustness stems from two aspects. First, we addressed the vision-based detection by developing an original approach based on fine gradient analysis, enhanced with a genetic AdaBoost-based algorithm for vehicle recognition. Then, we use the theory of evidence as a fusion framework to combine confidence levels delivered by the algorithms in order to improve the classification |vehicle versus non-vehicle|. The final architecture of the system is very modular, generic and flexible in that it could be used for other detection applications or using other sensors or algorithms providing the same outputs. The system was successfully implemented on a prototype vehicle and was evaluated under real conditions and over various multisensor databases and various test scenarios, illustrating very good performances.

Keywords: intelligent transportation systems; adaptive cruise control; ACC; vehicle detection; vision; laser scanning; object recognition; AdaBoost; sensor fusion; theory of evidence; transferable belief model; TBM; vehicle recognition; data fusion; genetic algorithms.

DOI: 10.1504/IJVAS.2008.016482

International Journal of Vehicle Autonomous Systems, 2008 Vol.6 No.1/2, pp.134 - 154

Published online: 31 Dec 2007 *

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