DocumentCode :
754646
Title :
IMMPDAF Approach for Road-Boundary Tracking
Author :
Kodagoda, K.R.S. ; Ge, Shuzhi Sam ; Wijesoma, Wijerupage Sardha ; Balasuriya, Arjuna P.
Author_Institution :
Nat. Univ. of Singapore
Volume :
56
Issue :
2
fYear :
2007
fDate :
3/1/2007 12:00:00 AM
Firstpage :
478
Lastpage :
486
Abstract :
Robust road-boundary extraction/tracking is one of the main problems in autonomous roadway navigation. Although the road boundary can be defined by various means including lane markings, curbs, and borders of vegetation, this paper focuses on road-boundary tracking using curbs. A vehicle-mounted (downward tilted) 2-D laser-measurement system is utilized to detect the curbs. The tracking problem is difficult because both the vehicle is moving and the target is disappearing, reappearing, and maneuvering in clutter. The interacting-multiple-model probabilistic-data-association filter (IMMPDAF) is proposed to solve the problems after detailed analysis. Track initiation, confirmation, and deletion are performed using the sequential-probability-ratio test. Extensive simulations followed by experiments in a campus environment show that the road-boundary tracking utilizing curbs is possible and robust through IMMPDAF
Keywords :
laser ranging; road traffic; road vehicles; IMMPDAF approach; autonomous roadway navigation; interacting-multiple-model probabilistic-data-association filter; lane markings; road-boundary tracking; robust road-boundary extraction; sequential-probability-ratio test; vehicle-mounted 2D laser-measurement system; Filters; Navigation; Performance evaluation; Remotely operated vehicles; Roads; Robustness; Sequential analysis; Target tracking; Vegetation; Vehicle detection; Autonomous vehicles; laser radar; road transportation; robot-sensing systems;
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2007.891426
Filename :
4138030
Link To Document :
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