Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34277
Title: Modeling the injury severity of small-displacement motorcycle crashes in Hanoi City, Vietnam
Authors: NGUYEN, Dinh Vinh Man 
Tuan Vu, Ahn
POLDERS, Evelien 
ROSS, Veerle 
BRIJS, Tom 
WETS, Geert 
BRIJS, Kris 
Advisors: Brijs
Issue Date: 2021
Publisher: 
Source: SAFETY SCIENCE, 142 (Art N° 105371)
Abstract: Hanoi City is a typical motorcycle dominant city in Vietnam with a modal share of motorcycles of more than 80% and motorcycle riders involved in more than 70% of road fatalities. It is important to understand the major causes of motorcycle crash severity to suggest effective countermeasures. There have been studies elsewhere examining factors related to small-displacement motorcycle crash severity, but work in Vietnam is scarce. This study uses ordinal logistic regression to investigate contributory factors to the odds of severe crashes involving motorcycle riders. A distinction is made between crashes where motorcyclists are involved as the second party (i. e., as victims of the crash) on the one hand and as the first party (i.e., as the person responsible for causing the crash) on the other hand. Results show that age and gender of the first party person, size of the vehicle collided with, and presence of a pillion passenger significantly contribute to the severity of crashes in which motorcyclists are involved as the second party. Significant factors to the severity of crashes in which motorcyclists are involved as the first party are age, time of the crash, road class, size of the second party vehicle, pillion passenger presence, and riding speed. The findings contribute to a deeper understanding of fatal crashes with small-displacement motorcycles in a developing city. This study helps to identify countermeasures to improve road safety of small-displacement motorcycle riders.
Keywords: Small-displacement motorcycle;Crash severity;Motorcycle-dominant city;Ordinal logistic regression
Document URI: http://hdl.handle.net/1942/34277
ISSN: 0925-7535
e-ISSN: 1879-1042
DOI: 10.1016/j.ssci.2021.105371
ISI #: WOS:000675899400019
Category: A1
Type: Journal Contribution
Validations: ecoom 2022
Appears in Collections:Research publications

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