Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia

The chances of a road user getting involved in a crash increase with an increased number of vehicles. Because of the rise in mobility, especially Heavy Goods Vehicle (HGV), a comprehensive study of the causes of a road crash involving HGV is required. Univariate binary logistic Regression was applie...

Full description

Bibliographic Details
Published in:AIP Conference Proceedings
Main Author: Zainuddin N.I.; Arshad A.K.; Hashim W.; Hamidun R.
Format: Conference paper
Language:English
Published: American Institute of Physics Inc. 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179828850&doi=10.1063%2f5.0178559&partnerID=40&md5=813483ef923028800c318462e3c6bbb0
id 2-s2.0-85179828850
spelling 2-s2.0-85179828850
Zainuddin N.I.; Arshad A.K.; Hashim W.; Hamidun R.
Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia
2023
AIP Conference Proceedings
2896
1
10.1063/5.0178559
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179828850&doi=10.1063%2f5.0178559&partnerID=40&md5=813483ef923028800c318462e3c6bbb0
The chances of a road user getting involved in a crash increase with an increased number of vehicles. Because of the rise in mobility, especially Heavy Goods Vehicle (HGV), a comprehensive study of the causes of a road crash involving HGV is required. Univariate binary logistic Regression was applied to HGV crash data collected from police records to examine the contribution of several road elements factors to accident severity. A total of 3,663 crash cases involving HGV were analyzed for three years (2015-2017). Accident severity (the dependent variable) in this study is a dichotomous variable with two categories, fatal and non-fatal. Therefore, the subjects sampled were classified as either fatal or non-fatal crashes. As a result, from eight independent variables of road elements obtained from police crash reports, five were most significantly associated with accident severity: road geometry, road defect, shoulder type, quality of surface and lane markings. A statistical interpretation is estimated in terms of the odds ratio concept. In conclusion, the significant factors identified in this study can be used as a guide to mitigate the probability of severe injuries and deaths. The significant factors can also help relevant authorities plan and design a sufficient and safe road element, especially for HGV safety. © 2023 Author(s).
American Institute of Physics Inc.
0094243X
English
Conference paper

author Zainuddin N.I.; Arshad A.K.; Hashim W.; Hamidun R.
spellingShingle Zainuddin N.I.; Arshad A.K.; Hashim W.; Hamidun R.
Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia
author_facet Zainuddin N.I.; Arshad A.K.; Hashim W.; Hamidun R.
author_sort Zainuddin N.I.; Arshad A.K.; Hashim W.; Hamidun R.
title Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia
title_short Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia
title_full Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia
title_fullStr Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia
title_full_unstemmed Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia
title_sort Exploring the factors affecting the severity of heavy good vehicle crashes in Malaysia
publishDate 2023
container_title AIP Conference Proceedings
container_volume 2896
container_issue 1
doi_str_mv 10.1063/5.0178559
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179828850&doi=10.1063%2f5.0178559&partnerID=40&md5=813483ef923028800c318462e3c6bbb0
description The chances of a road user getting involved in a crash increase with an increased number of vehicles. Because of the rise in mobility, especially Heavy Goods Vehicle (HGV), a comprehensive study of the causes of a road crash involving HGV is required. Univariate binary logistic Regression was applied to HGV crash data collected from police records to examine the contribution of several road elements factors to accident severity. A total of 3,663 crash cases involving HGV were analyzed for three years (2015-2017). Accident severity (the dependent variable) in this study is a dichotomous variable with two categories, fatal and non-fatal. Therefore, the subjects sampled were classified as either fatal or non-fatal crashes. As a result, from eight independent variables of road elements obtained from police crash reports, five were most significantly associated with accident severity: road geometry, road defect, shoulder type, quality of surface and lane markings. A statistical interpretation is estimated in terms of the odds ratio concept. In conclusion, the significant factors identified in this study can be used as a guide to mitigate the probability of severe injuries and deaths. The significant factors can also help relevant authorities plan and design a sufficient and safe road element, especially for HGV safety. © 2023 Author(s).
publisher American Institute of Physics Inc.
issn 0094243X
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
_version_ 1809677579344412672