Gradient-driven parking navigation using a continuous information potential field based on wireless sensor network

Wei, W; Song, H; Li, W; Shen, P; Vasilakos, A

Gradient-driven parking navigation using a continuous information potential field based on wireless sensor network

Wei, W Song, H Li, W Shen, P Vasilakos, A

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Information Sciences, 2017, 408, pp. 100-114
Issue Date:: 2017-10-01

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Field	Value	Language
dc.contributor.author	Wei, W
dc.contributor.author	Song, H
dc.contributor.author	Li, W
dc.contributor.author	Shen, P
dc.contributor.author	Vasilakos, A https://orcid.org/0000-0003-1902-9877
dc.date.accessioned	2022-08-22T06:46:15Z
dc.date.available	2022-08-22T06:46:15Z
dc.date.issued	2017-10-01
dc.identifier.citation	Information Sciences, 2017, 408, pp. 100-114
dc.identifier.issn	0020-0255
dc.identifier.issn	1872-6291
dc.identifier.uri	http://hdl.handle.net/10453/160694
dc.description.abstract	Wireless sensor networks can support building and transportation system automation in numerous ways. An emerging application is to guide drivers to promptly locate vacant parking spaces in large parking structures during peak hours. This paper proposes efficient parking navigation via a continuous information potential field and gradient ascent method. Our theoretical analysis proves the convergence of a proposed algorithm and efficient convergence during the first and second steps of the algorithm to effectively prevent parking navigation from a gridlock situation. The empirical study demonstrates that the proposed algorithm performs more efficiently than existing algorithms.
dc.language	English
dc.publisher	Elsevier
dc.relation.ispartof	Information Sciences
dc.relation.isbasedon	10.1016/j.ins.2017.04.042
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	01 Mathematical Sciences, 08 Information and Computing Sciences, 09 Engineering
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Gradient-driven parking navigation using a continuous information potential field based on wireless sensor network
dc.type	Journal Article
utslib.citation.volume	408
utslib.for	01 Mathematical Sciences
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
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 Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-08-22T06:46:13Z
pubs.publication-status	Published
pubs.volume	408

Abstract:

Wireless sensor networks can support building and transportation system automation in numerous ways. An emerging application is to guide drivers to promptly locate vacant parking spaces in large parking structures during peak hours. This paper proposes efficient parking navigation via a continuous information potential field and gradient ascent method. Our theoretical analysis proves the convergence of a proposed algorithm and efficient convergence during the first and second steps of the algorithm to effectively prevent parking navigation from a gridlock situation. The empirical study demonstrates that the proposed algorithm performs more efficiently than existing algorithms.

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http://hdl.handle.net/10453/160694