File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A two-stage bivariate logistic-Tobit model for the safety analysis of signalized intersections

TitleA two-stage bivariate logistic-Tobit model for the safety analysis of signalized intersections
Authors
Issue Date2014
PublisherElsevier BV. The Journal's web site is located at http://www.journals.elsevier.com/analytic-methods-in-accident-research/
Citation
Analytic Methods in Accident Research, 2014, v. 3-4, p. 1-10 How to Cite?
AbstractCrash frequency and crash severity models have explored the factors that influence intersection safety. However, most of these models address the frequency and severity independently, and miss the correlations between crash frequency models at different crash severity levels. We develop a two-stage bivariate logistic-Tobit model of the crash severity and crash risk at different severity levels. The first stage uses a binary logistic model to determine the overall crash severity level. The second stage develops a bivariate Tobit model to simultaneously evaluate the risk of a crash resulting in a slight injury and the risk of a crash resulting in a kill or serious injury (KSI). The model uses 420 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during 2002 and 2003. The results obtained from the first-stage binary logistic model indicate that the overall crash severity level is significantly influenced by the annual average daily traffic and number of pedestrian crossings. The results obtained from the second-stage bivariate Tobit model indicate that the factor that significantly influences the numbers of both slight injury and KSI crashes is the proportion of commercial vehicles. The existence of four or more approaches, the reciprocal of the average turning radius and the presence of a turning pocket increase the likelihood of slight injury crashes. The average lane width and cycle time affect the likelihood of KSI crashes. A comparison with existing approaches suggests that the bivariate logistic-Tobit model provides a good statistical fit and offers an effective alternative method for evaluating the safety performance at signalized intersections.
Persistent Identifierhttp://hdl.handle.net/10722/206789
ISSN
2015 SCImago Journal Rankings: 2.577

 

DC FieldValueLanguage
dc.contributor.authorXu, Xen_US
dc.contributor.authorWong, SCen_US
dc.contributor.authorChoi, Ken_US
dc.date.accessioned2014-12-02T09:20:12Z-
dc.date.available2014-12-02T09:20:12Z-
dc.date.issued2014en_US
dc.identifier.citationAnalytic Methods in Accident Research, 2014, v. 3-4, p. 1-10en_US
dc.identifier.issn2213-6657-
dc.identifier.urihttp://hdl.handle.net/10722/206789-
dc.description.abstractCrash frequency and crash severity models have explored the factors that influence intersection safety. However, most of these models address the frequency and severity independently, and miss the correlations between crash frequency models at different crash severity levels. We develop a two-stage bivariate logistic-Tobit model of the crash severity and crash risk at different severity levels. The first stage uses a binary logistic model to determine the overall crash severity level. The second stage develops a bivariate Tobit model to simultaneously evaluate the risk of a crash resulting in a slight injury and the risk of a crash resulting in a kill or serious injury (KSI). The model uses 420 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during 2002 and 2003. The results obtained from the first-stage binary logistic model indicate that the overall crash severity level is significantly influenced by the annual average daily traffic and number of pedestrian crossings. The results obtained from the second-stage bivariate Tobit model indicate that the factor that significantly influences the numbers of both slight injury and KSI crashes is the proportion of commercial vehicles. The existence of four or more approaches, the reciprocal of the average turning radius and the presence of a turning pocket increase the likelihood of slight injury crashes. The average lane width and cycle time affect the likelihood of KSI crashes. A comparison with existing approaches suggests that the bivariate logistic-Tobit model provides a good statistical fit and offers an effective alternative method for evaluating the safety performance at signalized intersections.-
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.journals.elsevier.com/analytic-methods-in-accident-research/-
dc.relation.ispartofAnalytic Methods in Accident Researchen_US
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Analytic Methods in Accident Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Analytic Methods in Accident Research, 2014, v. 3-4, p. 1-10. DOI: 10.1016/j.amar.2014.08.001-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleA two-stage bivariate logistic-Tobit model for the safety analysis of signalized intersectionsen_US
dc.typeArticleen_US
dc.identifier.emailWong, SC: hhecwsc@hku.hken_US
dc.identifier.authorityWong, SC=rp00191en_US
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.amar.2014.08.001en_US
dc.identifier.hkuros241527en_US
dc.identifier.volume3-4en_US
dc.identifier.spage1en_US
dc.identifier.epage10en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats