Coupling analysis of risk factors in road cargo transport accidents and preventive measures with an N-K model.

Road cargo transport accidents have been rising in China, posing threats to economic stability and public safety. This study identifies key risk factors in road freight accidents by analysing 160 accident investigation reports and employs a combined N-K model and complex-network approach to evaluate...

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Main Authors: Runhua Huang, Huichao Guo
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0328074
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author Runhua Huang
Huichao Guo
author_facet Runhua Huang
Huichao Guo
author_sort Runhua Huang
collection DOAJ
description Road cargo transport accidents have been rising in China, posing threats to economic stability and public safety. This study identifies key risk factors in road freight accidents by analysing 160 accident investigation reports and employs a combined N-K model and complex-network approach to evaluate coupling effects among factors. Twenty-seven specific risk factors were classified under individual, vehicle, environment and management domains. Multi-factor coupling (e.g. I-V-E-M) markedly increases accident probability, and complex-network metrics highlight hub (overloading, brake defects, inadequate road inspection, failure to observe road conditions) and bridge (inadequate inspection, illegal lane change, brake defects, speeding) factors. Targeted enforcement of loading limits, enhanced inspection regimes and driver training are recommended. Integrating the N-K model with complex-network analysis provides a systematic basis for prioritising preventive measures and improving road-freight safety.
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publisher Public Library of Science (PLoS)
record_format Article
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spelling doaj-art-197b6d2cd6984d75a1dda8f4f5e9e4462025-08-20T02:40:47ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01207e032807410.1371/journal.pone.0328074Coupling analysis of risk factors in road cargo transport accidents and preventive measures with an N-K model.Runhua HuangHuichao GuoRoad cargo transport accidents have been rising in China, posing threats to economic stability and public safety. This study identifies key risk factors in road freight accidents by analysing 160 accident investigation reports and employs a combined N-K model and complex-network approach to evaluate coupling effects among factors. Twenty-seven specific risk factors were classified under individual, vehicle, environment and management domains. Multi-factor coupling (e.g. I-V-E-M) markedly increases accident probability, and complex-network metrics highlight hub (overloading, brake defects, inadequate road inspection, failure to observe road conditions) and bridge (inadequate inspection, illegal lane change, brake defects, speeding) factors. Targeted enforcement of loading limits, enhanced inspection regimes and driver training are recommended. Integrating the N-K model with complex-network analysis provides a systematic basis for prioritising preventive measures and improving road-freight safety.https://doi.org/10.1371/journal.pone.0328074
spellingShingle Runhua Huang
Huichao Guo
Coupling analysis of risk factors in road cargo transport accidents and preventive measures with an N-K model.
PLoS ONE
title Coupling analysis of risk factors in road cargo transport accidents and preventive measures with an N-K model.
title_full Coupling analysis of risk factors in road cargo transport accidents and preventive measures with an N-K model.
title_fullStr Coupling analysis of risk factors in road cargo transport accidents and preventive measures with an N-K model.
title_full_unstemmed Coupling analysis of risk factors in road cargo transport accidents and preventive measures with an N-K model.
title_short Coupling analysis of risk factors in road cargo transport accidents and preventive measures with an N-K model.
title_sort coupling analysis of risk factors in road cargo transport accidents and preventive measures with an n k model
url https://doi.org/10.1371/journal.pone.0328074
work_keys_str_mv AT runhuahuang couplinganalysisofriskfactorsinroadcargotransportaccidentsandpreventivemeasureswithannkmodel
AT huichaoguo couplinganalysisofriskfactorsinroadcargotransportaccidentsandpreventivemeasureswithannkmodel