IMMPDAF approach for road-boundary tracking

Kodagoda, KRS; Ge, SS; Wijesoma, WS; Balasuriya, AP

IMMPDAF approach for road-boundary tracking

Kodagoda, KRS

Ge, SS Wijesoma, WS Balasuriya, AP

Permalink

Publication Type:: Journal Article
Citation:: IEEE Transactions on Vehicular Technology, 2007, 56 (2), pp. 478 - 486
Issue Date:: 2007-03-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (843.2 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Kodagoda, KRS https://orcid.org/0000-0001-5175-9138	en_US
dc.contributor.author	Ge, SS	en_US
dc.contributor.author	Wijesoma, WS	en_US
dc.contributor.author	Balasuriya, AP	en_US
dc.date.issued	2007-03-01	en_US
dc.identifier.citation	IEEE Transactions on Vehicular Technology, 2007, 56 (2), pp. 478 - 486	en_US
dc.identifier.issn	0018-9545	en_US
dc.identifier.uri	http://hdl.handle.net/10453/5861
dc.description.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. © 2007 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Vehicular Technology	en_US
dc.relation.isbasedon	10.1109/TVT.2007.891426	en_US
dc.subject.classification	Automobile Design & Engineering	en_US
dc.title	IMMPDAF approach for road-boundary tracking	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	56	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
utslib.for	10 Technology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	56	en_US

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. © 2007 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/5861