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
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