Literature DB >> 30448708

Factors affecting motorcyclists' injury severities: An empirical assessment using random parameters logit model with heterogeneity in means and variances.

Muhammad Waseem1, Anwaar Ahmed2, Tariq Usman Saeed3.   

Abstract

Motorcycles constitute 61% of the total registered vehicles in Pakistan and there has been a 371% growth in motorcycles in the country from year 2005-2015. Motorcycle is an essential and popular mode of transportation in Pakistan, therefore, the present study estimated a random parameters logit model to investigate the factors influencing the motorcycle injury severity using motorcycle crash data of Rawalpindi city collected by the Provincial Emergency Response Service. No injury, minor injury, severe injury and fatal injury are used as four categories of motorcyclist injury severity levels to calibrate the model. Mainly the effects of speed limits, crash-specific factors, rider attributes, roadway characteristics, weather and socio-demographics factors are considered for motorcycle-injury severity analysis. It was revealed that probability of fatal/severe injury increases for crashes: involving middle-aged riders (25-50 years) and riders with no education, occurring on roads with posted speed limit of 70 kms per hour or higher, crashes involving a motorcycle and a heavy vehicle, involving collision of a motorcycle with a fixed object and occurring during dry weather conditions. Also, the probability of minor injury increases for crashes: occurring on divided streets and road segments with a posted speed limit of less than 50 kms per hour, involving Chinese brand motorcycles, involving registered motorcycles, and where at least one motorcycle and auto rickshaw is involved. The research findings suggest that besides measures to control/ reduce the risky motorcyclists behavior there is a need to lower speed limits on roads with a higher motorcycle proportion, separate motorcycles from heavy vehicles and removal of fixed objects from the roadside. Besides data limitations, results are expected to generate more discussion and interest in motorcycle safety in the country and can be used by the enforcement agencies to improve/ enhance the current state of motorcycle safety in the country.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Injury severity; Motorcycle safety; Pakistan; Random parameters logit model

Mesh:

Year:  2018        PMID: 30448708     DOI: 10.1016/j.aap.2018.10.022

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  7 in total

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2.  How did the COVID-19 pandemic affect road crashes and crash outcomes in Alabama?

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4.  Environmental Factors Associated with Severe Motorcycle Crash Injury in University Neighborhoods: A Multicenter Study in Taiwan.

Authors:  Heng-Yu Lin; Jian-Sing Li; Chih-Wei Pai; Wu-Chien Chien; Wen-Cheng Huang; Chin-Wang Hsu; Chia-Chieh Wu; Shih-Hsiang Yu; Wen-Ta Chiu; Carlos Lam
Journal:  Int J Environ Res Public Health       Date:  2022-08-18       Impact factor: 4.614

5.  Temporal Instability of Factors Affecting Injury Severity in Helmet-Wearing and Non-Helmet-Wearing Motorcycle Crashes: A Random Parameter Approach with Heterogeneity in Means and Variances.

Authors:  Muhammad Ijaz; Lan Liu; Yahya Almarhabi; Arshad Jamal; Sheikh Muhammad Usman; Muhammad Zahid
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6.  Determinants and Prediction of Injury Severities in Multi-Vehicle-Involved Crashes.

Authors:  Xiuguang Song; Rendong Pi; Yu Zhang; Jianqing Wu; Yuhuan Dong; Han Zhang; Xinyuan Zhu
Journal:  Int J Environ Res Public Health       Date:  2021-05-15       Impact factor: 3.390

7.  Crash severity analysis of vulnerable road users using machine learning.

Authors:  Md Mostafizur Rahman Komol; Md Mahmudul Hasan; Mohammed Elhenawy; Shamsunnahar Yasmin; Mahmoud Masoud; Andry Rakotonirainy
Journal:  PLoS One       Date:  2021-08-05       Impact factor: 3.240

  7 in total

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