DocumentCode :
3467411
Title :
Dynamic cluster tracking technique for traffic monitoring using on-vehicle radar
Author :
Zorka, Nicholas ; Cheok, Ka C.
Author_Institution :
Ford Sci. Res. Lab., Ford Motor Co., Dearborn, MI, USA
fYear :
2004
fDate :
14-17 June 2004
Firstpage :
728
Lastpage :
731
Abstract :
Predictive sensing applications are starting to find wide applications in automotive safety applications. In collision situations the need to alert the driver and to take effective countermeasures to meet the needs of the vehicle occupant safety is becoming increasingly more dependent on sensors. Electronic systems to provide warning and to implement active adaptation of occupant restraints to provide for enhanced safety protection are becoming more dependent on active safety sensors. This paper deals with a system that uses radar sensors that provides the ability to cluster the number of vehicles based on radar return signals and to actively track their movement with a Kalman filter.
Keywords :
Kalman filters; driver information systems; filtering theory; image sensors; pattern clustering; radar tracking; road safety; road vehicle radar; Kalman filter; active safety sensors; automotive safety; collision situations; countermeasures; dynamic cluster tracking; electronic systems; occupant restraints; on-vehicle radar; predictive sensing; radar return signals; radar sensors; safety protection; traffic monitoring; vehicle occupant safety; Automotive engineering; Driver circuits; Electronic countermeasures; Monitoring; Radar countermeasures; Radar tracking; Road accidents; Sensor systems; Vehicle dynamics; Vehicle safety;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2004 IEEE
Print_ISBN :
0-7803-8310-9
Type :
conf
DOI :
10.1109/IVS.2004.1336474
Filename :
1336474
Link To Document :
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