DocumentCode :
3265948
Title :
De-cluttering with Integrated Probabilistic Data Association for Multisensor Multitarget ACC Vehicle Tracking
Author :
Maehlisch, Mirko ; Ritter, Werner ; Dietmayer, Klaus
Author_Institution :
Ulm Univ., Ulm
fYear :
2007
fDate :
13-15 June 2007
Firstpage :
178
Lastpage :
183
Abstract :
In the field of automotive environment perception, the state estimation problem of other road users with sensors like video, radar, lidar, or combinations of them has been solved for years now. However, driver assistance systems like ACC are only available for restricted environments like highways and rural roads today. Especially in complex environments, the uncertainty of target existence induced from missing and false detections becomes the dominating error source. Traditional approaches for track verification are rule based systems and trained classifiers. In this contribution, we present an automotive application of the integrated probabilistic data association (IPDA) filter superseding additional validation modules by modeling the probabilistic knowledge about both, state and existence, as temporal Markov chains and computing filter estimates for both issues. The temporal evolution and measurement update models for state and existence estimation are presented for the vehicle tracking problem as well as results from a sensor fusion setup with video and multibeam lidar.
Keywords :
sensor fusion; traffic engineering computing; filter estimates; multibeam lidar; multisensor multitarget ACC vehicle tracking; probabilistic data association; sensor fusion; track verification; Automotive engineering; Filters; Laser radar; Radar detection; Radar tracking; Road transportation; State estimation; Target tracking; Uncertainty; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2007 IEEE
Conference_Location :
Istanbul
ISSN :
1931-0587
Print_ISBN :
1-4244-1067-3
Electronic_ISBN :
1931-0587
Type :
conf
DOI :
10.1109/IVS.2007.4290111
Filename :
4290111
Link To Document :
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