Literature DB >> 33387713

A spatiotemporal analysis of motorcyclist injury severity: Findings from 20 years of crash data from Pennsylvania.

Xiaobing Li1, Jun Liu2, Zihe Zhang3, Allen Parrish4, Steven Jones5.   

Abstract

Motorcyclists face higher risks of severe injuries in crashes compared to motor vehicle drivers who are often protected by seatbelts and airbags during collisions. A report by the National Highway Traffic Safety Administration reveals that motorcyclists have 27 times the risk of fatality in traffic crashes as much as motor vehicle drivers. Previous studies have identified a list of risk factors associated with motorcyclist injury severity and generated valuable insights for countermeasures to protect motorcyclists in crashes. These studies have shown that wearing helmets and/or motorcycle-specific reflective clothing and boots, driving alcohol/drug-free, and obeying traffic regulations are good practices for safe motorcycling. However, these practices and other risk factors are likely to interact with local geographic, socio-economic, and cultural contexts, leading to diversified correlations with motorcyclist injury severity, which remains under-explored. Such correlations may exhibit variations across space and time. The objective of this study is to revisit the correlates of motorcyclist injury severity with a focus on the spatial and temporal variations of correlations between risk factors and injury severity. This study employed an integrated spatiotemporal analytical approach to mine comprehensive statewide 20 years' motorcycle-involved traffic crashes (N = 50,823) in Pennsylvania. Non-stationarity tests were performed to examine the significance of variations in spatially and temporally local correlations. The results show that most factors, such as helmet, engine size, vehicle age, pillion passenger, at-fault striking, and speeding, hold significant non-stationary relationships with motorcyclist injury severity. Furthermore, cluster analysis of estimations reveals the regional similarities of correlates, which may help practitioners develop regional motorcyclist safety countermeasures.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Clustering; Injury severity; Motorcyclist; Non-stationarity; Spatio-temporal

Mesh:

Year:  2020        PMID: 33387713     DOI: 10.1016/j.aap.2020.105952

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


  3 in total

1.  Key Factors Analysis of Severity of Automobile to Two-Wheeler Traffic Accidents Based on Bayesian Network.

Authors:  Lining Liu; Xiaofei Ye; Tao Wang; Xingchen Yan; Jun Chen; Bin Ran
Journal:  Int J Environ Res Public Health       Date:  2022-05-15       Impact factor: 4.614

2.  A knowledge elicitation approach to traffic accident analysis in open data: comparing periods before and after the Covid-19 outbreak.

Authors:  ChienHsing Wu; Shu-Chen Kao; Chia-Chen Chang
Journal:  Heliyon       Date:  2022-08-24

3.  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

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.