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Article: Severity of pedestrian injuries due to traffic crashes at signalized intersections in Hong Kong: a Bayesian spatial logit model

TitleSeverity of pedestrian injuries due to traffic crashes at signalized intersections in Hong Kong: a Bayesian spatial logit model
Authors
KeywordsBayesian inference
conditional autoregressive prior
pedestrian injury severity
signalized intersection
spatial logit model
Issue Date2016
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www.advanced-transport.com
Citation
Journal of Advanced Transportation, 2016, v. 50 n. 8, p. 2015-2028 How to Cite?
AbstractThe present study intended to (1) investigate the injury risk of pedestrian casualties involved in traffic crashes at signalized intersections in Hong Kong; (2) determine the effect of pedestrian volumes on the severity levels of pedestrian injuries; and (3) explore the role of spatial correlation in econometric crash-severity models. The data from 1889 pedestrian-related crashes at 318 signalized intersections between 2008 and 2012 were elaborately collected from the Traffic Accident Database System maintained by the Hong Kong Transport Department. To account for the cross-intersection heterogeneity, a Bayesian hierarchical logit model with uncorrelated and spatially correlated random effects was developed. An intrinsic conditional autoregressive prior was specified for the spatial correlation term. Results revealed that (1) signalized intersections with greater pedestrian volumes generally exhibited a lower injury risk; (2) ignoring the spatial correlation potentially results in reduced model goodness-of-fit, an underestimation of variability and standard error of parameter estimates, as well as inconsistent, biased, and erroneous inference; (3) special attention should be paid to the following factors, which led to a significantly higher probability of pedestrians being killed or sustaining severe injury: pedestrian age greater than 65 years, casualties with head injuries, crashes that occurred on footpaths that were not obstructed/overcrowded, heedless or inattentive crossing, crashes on the two-way carriageway, and those that occurred near tram or light-rail transit stops. Copyright © 2017 John Wiley & Sons, Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/240906
ISSN
2023 Impact Factor: 2.0
2023 SCImago Journal Rankings: 0.582
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, X-
dc.contributor.authorXie, S-
dc.contributor.authorWong, SC-
dc.contributor.authorXu, P-
dc.contributor.authorHuang, H-
dc.contributor.authorPei, X-
dc.date.accessioned2017-05-22T09:19:14Z-
dc.date.available2017-05-22T09:19:14Z-
dc.date.issued2016-
dc.identifier.citationJournal of Advanced Transportation, 2016, v. 50 n. 8, p. 2015-2028-
dc.identifier.issn0197-6729-
dc.identifier.urihttp://hdl.handle.net/10722/240906-
dc.description.abstractThe present study intended to (1) investigate the injury risk of pedestrian casualties involved in traffic crashes at signalized intersections in Hong Kong; (2) determine the effect of pedestrian volumes on the severity levels of pedestrian injuries; and (3) explore the role of spatial correlation in econometric crash-severity models. The data from 1889 pedestrian-related crashes at 318 signalized intersections between 2008 and 2012 were elaborately collected from the Traffic Accident Database System maintained by the Hong Kong Transport Department. To account for the cross-intersection heterogeneity, a Bayesian hierarchical logit model with uncorrelated and spatially correlated random effects was developed. An intrinsic conditional autoregressive prior was specified for the spatial correlation term. Results revealed that (1) signalized intersections with greater pedestrian volumes generally exhibited a lower injury risk; (2) ignoring the spatial correlation potentially results in reduced model goodness-of-fit, an underestimation of variability and standard error of parameter estimates, as well as inconsistent, biased, and erroneous inference; (3) special attention should be paid to the following factors, which led to a significantly higher probability of pedestrians being killed or sustaining severe injury: pedestrian age greater than 65 years, casualties with head injuries, crashes that occurred on footpaths that were not obstructed/overcrowded, heedless or inattentive crossing, crashes on the two-way carriageway, and those that occurred near tram or light-rail transit stops. Copyright © 2017 John Wiley & Sons, Ltd.-
dc.languageeng-
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www.advanced-transport.com-
dc.relation.ispartofJournal of Advanced Transportation-
dc.rightsJournal of Advanced Transportation. Copyright © John Wiley & Sons, Inc.-
dc.rightsThis is the peer reviewed version of the following article: Journal of Advanced Transportation, 2016, v. 50 n. 8, p. 2015-2028, which has been published in final form at DOI: 10.1002/atr.1442. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.-
dc.subjectBayesian inference-
dc.subjectconditional autoregressive prior-
dc.subjectpedestrian injury severity-
dc.subjectsignalized intersection-
dc.subjectspatial logit model-
dc.titleSeverity of pedestrian injuries due to traffic crashes at signalized intersections in Hong Kong: a Bayesian spatial logit model-
dc.typeArticle-
dc.identifier.emailXie, S: seakay@connect.hku.hk-
dc.identifier.emailWong, SC: hhecwsc@hku.hk-
dc.identifier.authorityWong, SC=rp00191-
dc.description.naturepostprint-
dc.identifier.doi10.1002/atr.1442-
dc.identifier.scopuseid_2-s2.0-85012894252-
dc.identifier.hkuros272398-
dc.identifier.volume50-
dc.identifier.issue8-
dc.identifier.spage2015-
dc.identifier.epage2028-
dc.identifier.isiWOS:000401555900026-
dc.publisher.placeUnited States-
dc.identifier.issnl0197-6729-

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