Modeling crashes involving pedestrians and motorized traffic

This paper presents an empirical inquiry into the predictive modeling of crashes involving pedestrians and motorized traffic on roadways. Empirical models based on the negative binomial distribution and mixing distributions, such as the zero-inflated Poisson distribution, are presented and discussed...

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Bibliographic Details
Published inSafety science Vol. 41; no. 7; pp. 627 - 640
Main Authors Shankar, Venkataraman N., Ulfarsson, Gudmundur F., Pendyala, Ram M., Nebergall, MaryLou B.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier India Pvt Ltd 01.08.2003
Elsevier
Subjects
Biological and medical sciences
General aspects
Medical sciences
Planification. Prevention (methods). Intervention. Evaluation
Public health. Hygiene
Public health. Hygiene-occupational medicine
Human
Prevention
Organization
Empirical method
Infrastructure
Pedestrian
Traffic accident
Safety
Modeling
Public health
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Summary:This paper presents an empirical inquiry into the predictive modeling of crashes involving pedestrians and motorized traffic on roadways. Empirical models based on the negative binomial distribution and mixing distributions, such as the zero-inflated Poisson distribution, are presented and discussed in terms of their applicability to pedestrian crash phenomena. Key modeling issues relating to the presence of excess zeros as well as unobserved heterogeneity in pedestrian crash distributions are addressed. The empirical results show that zero-inflated count distributions, such as the zero-inflated Poisson, are promising methodologies for providing explanatory insights into the causality behind pedestrian-traffic crashes.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0925-7535
1879-1042
DOI:10.1016/S0925-7535(02)00017-6