Exploring the determinants of pedestrian–vehicle crash severity in New York City

► Developed a random parameter model for understanding pedestrian–vehicle crash severity. ► Modeling was conducted at both the aggregate and disaggregate borough level. ► Socio-demographic, land use, traffic and built environment variables are included in the modeling process. ► Policy and engineeri...

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Vydáno v:Accident analysis and prevention Ročník 50; s. 1298 - 1309
Hlavní autoři: Aziz, H.M. Abdul, Ukkusuri, Satish V., Hasan, Samiul
Médium: Journal Article
Jazyk:angličtina
Vydáno: Kidlington Elsevier Ltd 01.01.2013
Elsevier
Témata:
Accidents, Traffic - mortality
Accidents, Traffic - statistics & numerical data
Biological and medical sciences
Built environment
Chi-Square Distribution
Crashes
Environment. Living conditions
Female
Heterogeneity
Humans
Injury Severity Score
Land use
Lanes
Likelihood Functions
Male
Mathematical models
Medical sciences
Military technology
Miscellaneous
New York City
New York City - epidemiology
Pedestrian–vehicle crashes
Prevention and actions
Public health. Hygiene
Public health. Hygiene-occupational medicine
Quality
Random parameter model
Risk Factors
Roads
Severity modeling
Walking - injuries
Wounds and Injuries - epidemiology
Wounds and Injuries - mortality
New York
United States
North America
America
New York City
USA, New York, New York City
New York City
Random parameter model
Pedestrian–vehicle crashes
Built environment
Severity modeling
Pedestrian-vehicle crashes
Urban environment
Vehicle driving
Determinant
Pedestrian
Traffic accident
Modeling
Health and environment
Urbanization
Models
ISSN:0001-4575, 1879-2057, 1879-2057
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Shrnutí:► Developed a random parameter model for understanding pedestrian–vehicle crash severity. ► Modeling was conducted at both the aggregate and disaggregate borough level. ► Socio-demographic, land use, traffic and built environment variables are included in the modeling process. ► Policy and engineering insights to improve pedestrian safety are discussed. Pedestrian–vehicle crashes remain a major concern in New York City due to high percentage of fatalities. This study develops random parameter logit models for explaining pedestrian injury severity levels of New York City accounting for unobserved heterogeneity in the population and across the boroughs. A log-likelihood ratio test for joint model suitability suggests that separate models for each of the boroughs should be estimated. Among many variables, road characteristics (e.g., number of lanes, grade, light condition, road surface, etc.), traffic attributes (e.g., presence of signal control, type of vehicle, etc.), and land use (e.g., parking facilities, commercial and industrial land use, etc.) are found to be statistically significant in the estimated model. The study also suggests that the set of counter measures should be different for different boroughs in the New York City and the priority ranks of countermeasures should be different as well.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0001-4575
1879-2057
1879-2057
DOI:10.1016/j.aap.2012.09.034