Infrastructure supported autonomous driving is getting in the focus of current research. In this work, we investigated the usage of a traffic monitoring infrastructure combined with the environmental model of an autonomous driving vehicle for localization. The forwarded environmental model of the infrastructure contains tracked road users, but the used tracking algorithm is unknown. The result is based on a two-stage transformation process with optimized fusion and tracking by a Kalman filter. Experiments show, that the algorithm provides a consistent localization at the first time step.
Vehicle Localization Using Infrastructure Sensing
Lect.Notes Mobility
International Forum on Advanced Microsystems for Automotive Applications ; 2020 ; Berlin, Germany May 26, 2020 - May 27, 2020
2020-12-11
11 pages
Article/Chapter (Book)
Electronic Resource
English
Localization , Infrastructure sensors , Intelligent vehicles , MEC-View project , Roadside sensors , MEC-Server , Automated driving , Information fusion , Kalman filter , Pose estimation , Optimized fusion Engineering , Automotive Engineering , Robotics and Automation , Cyber-physical systems, IoT , Transportation Technology and Traffic Engineering
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