A note on hotspot identification for urban expressways

Qu, X; Meng, Q

A note on hotspot identification for urban expressways

Qu, X

Meng, Q

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Publication Type:: Journal Article
Citation:: Safety Science, 2014, 66 pp. 87 - 91
Issue Date:: 2014-07-01

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Field	Value	Language
dc.contributor.author	Qu, X https://orcid.org/0000-0003-0973-3756	en_US
dc.contributor.author	Meng, Q	en_US
dc.date.issued	2014-07-01	en_US
dc.identifier.citation	Safety Science, 2014, 66 pp. 87 - 91	en_US
dc.identifier.issn	0925-7535	en_US
dc.identifier.uri	http://hdl.handle.net/10453/118691
dc.description.abstract	Hotspot identification (HSID) is of great importance to land transport authorities (e.g. the Land Transport Authority (LTA) of Singapore) in their efforts to improve the safety of highways. According to a survey of experienced engineers at the LTA of Singapore, we draw the conclusion that the severity of crashes should not be neglected in the HSID process. Accordingly, in this technical note, societal risk-based simple ranking and empirical Bayesian methods are proposed to identify the hotspots in a Singapore expressway on the basis of the detailed three-year casualty data in the Historical Crash Damage (HCD) database. We further conduct a consistency analysis to compare the societal risk-based method and the conventional frequency-based method. The consistency analysis reports that (1) the frequency-based method is more consistent than the societal risk-based method, and (2) the empirical Bayesian method is more consistent than the simple ranking method. © 2014 Elsevier Ltd.	en_US
dc.relation.ispartof	Safety Science	en_US
dc.relation.isbasedon	10.1016/j.ssci.2014.02.006	en_US
dc.subject.classification	Human Factors	en_US
dc.title	A note on hotspot identification for urban expressways	en_US
dc.type	Journal Article
utslib.citation.volume	66	en_US
utslib.for	090507 Transport Engineering	en_US
utslib.for	09 Engineering	en_US
utslib.for	11 Medical and Health Sciences	en_US
utslib.for	17 Psychology and Cognitive Sciences	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 Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	66	en_US

Abstract:

Hotspot identification (HSID) is of great importance to land transport authorities (e.g. the Land Transport Authority (LTA) of Singapore) in their efforts to improve the safety of highways. According to a survey of experienced engineers at the LTA of Singapore, we draw the conclusion that the severity of crashes should not be neglected in the HSID process. Accordingly, in this technical note, societal risk-based simple ranking and empirical Bayesian methods are proposed to identify the hotspots in a Singapore expressway on the basis of the detailed three-year casualty data in the Historical Crash Damage (HCD) database. We further conduct a consistency analysis to compare the societal risk-based method and the conventional frequency-based method. The consistency analysis reports that (1) the frequency-based method is more consistent than the societal risk-based method, and (2) the empirical Bayesian method is more consistent than the simple ranking method. © 2014 Elsevier Ltd.

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http://hdl.handle.net/10453/118691