Petrolwatch: a participatory image sensing system for automated street level information collection

Dong, Y

Petrolwatch: a participatory image sensing system for automated street level information collection

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Publication Type:: Thesis

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Field	Value	Language
dc.contributor.author	Dong, Y https://orcid.org/0000-0002-7995-9657
dc.date.accessioned	2023-03-16T13:22:11Z
dc.date.available	2023-03-16T13:22:11Z
dc.identifier.uri	http://hdl.handle.net/10453/167382
dc.description.abstract	City streets are full of useful information pertaining to traffic conditions, location of services and businesses, which can benefit the public. Such benefit has been confirmed by a number of studies [1–5]. Past research has shown that vehicle drivers gain much from traffic information services. The study in [1] showed that more than 60% of the drivers used traffic reports, and these drivers were more likely to change their route if they realized that their regular routes were congested. The study in [2] showed that the knowledge of travel time in advance provides a better basis for the travelers to choose a better route and thereby saving traveling time by up to 15%.
dc.language	en
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Petrolwatch: a participatory image sensing system for automated street level information collection
dc.type	Thesis
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-16T13:22:09Z

Abstract:

City streets are full of useful information pertaining to traffic conditions, location of services and businesses, which can benefit the public. Such benefit has been confirmed by a number of studies [1–5]. Past research has shown that vehicle drivers gain much from traffic information services. The study in [1] showed that more than 60% of the drivers used traffic reports, and these drivers were more likely to change their route if they realized that their regular routes were congested. The study in [2] showed that the knowledge of travel time in advance provides a better basis for the travelers to choose a better route and thereby saving traveling time by up to 15%.

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http://hdl.handle.net/10453/167382