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Article: Bayesian approach to model pedestrian crashes at signalized intersections with measurement errors in exposure

TitleBayesian approach to model pedestrian crashes at signalized intersections with measurement errors in exposure
Authors
KeywordsMeasurement errors
Pedestrian crash frequency
Pedestrian exposure
Signalized intersections
Issue Date2018
PublisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/336/description#description
Citation
Accident Analysis & Prevention, 2018, v. 121, p. 285-294 How to Cite?
AbstractThis study intended to identify the potential factors contributing to the occurrence of pedestrian crashes at signalized intersections in a densely populated city, based on a comprehensive dataset of 898 pedestrian crashes at 262 signalized intersections during 2010–2012 in Hong Kong. The detailed geometric design, traffic characteristics, signal control, built environment, along with the vehicle and pedestrian volumes were elaborately collected. A Bayesian measurement errors model was introduced as an alternative method to explicitly account for the uncertainties in volume data. To highlight the role played by exposure, models with and without pedestrian volume were estimated and compared. The results indicated that the omission of pedestrian volume in pedestrian crash frequency models would lead to reduced goodness-of-fit, biased parameter estimates, and incorrect inferences. Our empirical analysis demonstrated the existence of moderate uncertainties in pedestrian and vehicle volumes. Six variables were found to have a significant association with the number of pedestrian crashes at signalized intersections. The number of crossing pedestrians, the number of passing vehicles, the presence of curb parking, and the presence of ground-floor shops were positively related with pedestrian crash frequency, whereas the presence of playgrounds near intersections had a negative effect on pedestrian crash occurrences. Specifically, the presence of exclusive pedestrian signals for all crosswalks was found to significantly reduce the risk of pedestrian crashes by 43%. The present study is expected to shed more light on a deeper understanding of the environmental determinants of pedestrian crashes.
Persistent Identifierhttp://hdl.handle.net/10722/264007
ISSN
2023 Impact Factor: 5.7
2023 SCImago Journal Rankings: 1.897
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXie, S-
dc.contributor.authorDong, N-
dc.contributor.authorWong, SC-
dc.contributor.authorHuang, H-
dc.contributor.authorXU, P-
dc.date.accessioned2018-10-22T07:48:01Z-
dc.date.available2018-10-22T07:48:01Z-
dc.date.issued2018-
dc.identifier.citationAccident Analysis & Prevention, 2018, v. 121, p. 285-294-
dc.identifier.issn0001-4575-
dc.identifier.urihttp://hdl.handle.net/10722/264007-
dc.description.abstractThis study intended to identify the potential factors contributing to the occurrence of pedestrian crashes at signalized intersections in a densely populated city, based on a comprehensive dataset of 898 pedestrian crashes at 262 signalized intersections during 2010–2012 in Hong Kong. The detailed geometric design, traffic characteristics, signal control, built environment, along with the vehicle and pedestrian volumes were elaborately collected. A Bayesian measurement errors model was introduced as an alternative method to explicitly account for the uncertainties in volume data. To highlight the role played by exposure, models with and without pedestrian volume were estimated and compared. The results indicated that the omission of pedestrian volume in pedestrian crash frequency models would lead to reduced goodness-of-fit, biased parameter estimates, and incorrect inferences. Our empirical analysis demonstrated the existence of moderate uncertainties in pedestrian and vehicle volumes. Six variables were found to have a significant association with the number of pedestrian crashes at signalized intersections. The number of crossing pedestrians, the number of passing vehicles, the presence of curb parking, and the presence of ground-floor shops were positively related with pedestrian crash frequency, whereas the presence of playgrounds near intersections had a negative effect on pedestrian crash occurrences. Specifically, the presence of exclusive pedestrian signals for all crosswalks was found to significantly reduce the risk of pedestrian crashes by 43%. The present study is expected to shed more light on a deeper understanding of the environmental determinants of pedestrian crashes.-
dc.languageeng-
dc.publisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/336/description#description-
dc.relation.ispartofAccident Analysis & Prevention-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectMeasurement errors-
dc.subjectPedestrian crash frequency-
dc.subjectPedestrian exposure-
dc.subjectSignalized intersections-
dc.titleBayesian approach to model pedestrian crashes at signalized intersections with measurement errors in exposure-
dc.typeArticle-
dc.identifier.emailXie, S: seakay@connect.hku.hk-
dc.identifier.emailWong, SC: hhecwsc@hku.hk-
dc.identifier.emailXU, P: pengpengxu@yeah.net-
dc.identifier.authorityWong, SC=rp00191-
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.aap.2018.09.030-
dc.identifier.scopuseid_2-s2.0-85054309337-
dc.identifier.hkuros294771-
dc.identifier.volume121-
dc.identifier.spage285-
dc.identifier.epage294-
dc.identifier.isiWOS:000449241600031-
dc.publisher.placeUnited Kingdom-

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