A Comparison of Contributing Factors between Young and Old Riders of Motorcycle Crash Severity on Local Roads

Journal article

Authors/Editors

TASSANA BOONYOO

Strategic Research Themes

Transport Safety, Policy & Planning (Sustainable Mobility)

Publication Details

Author list: Champahom, Thanapong; Se, Chamroeun; Jomnonkwao, Sajjakaj; Boonyoo, Tassana; Ratanavaraha, Vatanavongs;

Publisher: MDPI

Publication year: 2023

Volume number: 15

Issue number: 3

ISSN: 2071-1050

eISSN: 2071-1050

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147998524&doi=10.3390%2fsu15032708&partnerID=40&md5=e1dc3033599822603c7c5355ac2cda8b

Languages: English-Great Britain (EN-GB)

View in Web of Science | View on publisher site | View citing articles in Web of Science

Abstract

This study aims to identify the factors that influence the severity of motorcycle crashes on local roads, particularly given the high speeds often observed for motorcycles on these roads with low traffic volumes and numerous multi-leg intersections. Previous research has shown that a rider’s age can impact their speed behavior. To explore this issue, data on motorcycle crashes from 2015 to 2020 in Thailand—a middle-income developing country—were analyzed using a random parameter logit model with unobserved heterogeneity in means and variances, comparing young (<30-year-old) and older (>50-year-old) riders. The contributing factors were divided into four groups: driver, crash, environmental, and road factors. The transferability test yielded different results for the young rider and old rider models, indicating that it is appropriate to analyze these models separately. A constant value revealed that old riders were more likely to die in a crash than young riders. In terms of the random parameter, the local address and road surface variables were found to be significant in both models. The results of unobserved heterogeneity in means and variances identified significant variables in both models, including gender, exceeding the speed limit, lit roads, unlit roads, mobile phone use, and road surface. These findings were used to develop policy recommendations for reducing the severity of motorcycle crashes on local roads. © 2023 by the authors.

Keywords

crash fatality, random parameter logit model, rider age, unobserved heterogeneity