Abstract
We introduce a multi-target, multi-sensor data fusion concept for automotive applications in urban environments. Based on a sensor system consisting of laser scanners, radar and LIDAR sensors, a system architecture has been created which is capable of tracking objects ofarbitrarycontours.Thefusionsystemisindependentfromthesensortypesusedandcanbe set up in a distributed architecture based on Ethernet communication.The classical Kalman filter algorithm has been extended to realize contour-functionality, removing the necessity to define a static object reference point. A specialized data association and pretracking stage effectively uses intentional sensor redundancy in order to suppress false alarms and increase trackquality.Thefusionsystemisimplementedinthe2007DARPAUrbanChallengevehicle of Team CarOLO, Technische Universitat Braunschweig.
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