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An Analysis of the Injury Severity of Motorcycle Crashes in Brazil Using Mixed Ordered Response Models

Título
An Analysis of the Injury Severity of Motorcycle Crashes in Brazil Using Mixed Ordered Response Models
Tipo
Artigo em Revista Científica Internacional
Ano
2017
Autores
Sara Ferreira
(Autor)
FEUP
Flávio J. C. Cunto
(Autor)
Outra
A pessoa não pertence à instituição. A pessoa não pertence à instituição. A pessoa não pertence à instituição. Sem AUTHENTICUS Sem ORCID
Revista
Vol. 9 S1
Páginas: 33-46
ISSN: 1943-9970
Editora: Taylor & Francis
Indexação
Publicação em ISI Web of Science ISI Web of Science
EBSCO
Outras Informações
ID Authenticus: P-00M-HNZ
Resumo (PT):
Abstract (EN): The Brazilian traffic environment has experienced a disproportionate growth in motorcycle use over the last 15 years. Unfortunately the same trend has been observed for crash frequency and severity in the category in part by their relative exposure as well as vulnerability. This study investigates factors that influence the severity of motorcycle accidents in urban streets of Fortaleza. Traditional and mixed ordered logit models were calibrated using a sample of 3,232 observations of traffic accidents from 2004 to 2011. Physical levels of injury inflicted to motorcyclists were grouped as no apparent injury, slight injury, serious injury, and fatal injury. The models were developed using several variables as risk factors. Results suggested that motorcyclists using helmets reduced their chances by 9% of suffering severe and fatal injuries after the crash. Accidents during the daylight as well as on weekdays presented lower risk of resulting in fatal injuries. Also, crashes involving motorcyclists older than age 61 years have 22% more probability of resulting in severe and fatal injuries as compared to young riders. Most of these findings can be associated with commonly reported risky behavior from motorcyclists such as speeding, improper lane changes, and red light running.
Idioma: Inglês
Tipo (Avaliação Docente): Científica
Nº de páginas: 14
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