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

**Authors:** Runhua Huang, Huichao Guo, Mohammad Ebrahimi, Mohammad Ebrahimi, Mohammad Ebrahimi

PMC · DOI: 10.1371/journal.pone.0328074 · PLOS One · 2025-07-15

## TL;DR

This study identifies key risk factors in road cargo transport accidents in China and proposes preventive measures using a combined N–K model and complex-network analysis.

## Contribution

The integration of the N–K model with complex-network analysis offers a novel approach to evaluating coupling effects in road freight accidents.

## Key findings

- Multi-factor coupling significantly increases the probability of road cargo transport accidents.
- Hub and bridge risk factors include overloading, brake defects, and inadequate road inspection.
- Targeted enforcement and training are recommended to improve road-freight safety.

## Abstract

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.

## Full-text entities

- **Diseases:** brake defects (MESH:D000013)

## Full text

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## Figures

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## References

33 references — full list in the complete paper: https://tomesphere.com/paper/PMC12262903/full.md

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Source: https://tomesphere.com/paper/PMC12262903