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Articles

Human factors related to major road traffic accidents in China

ORCID Icon, ORCID Icon, ORCID Icon, &
Pages 796-800 | Received 09 Jun 2018, Accepted 17 Sep 2019, Published online: 11 Nov 2019
 

Abstract

Objective: The goals of this research are to: (i) investigate the contributing factors of major road traffic accidents using a human factors classification that follows the ideas of the human factors analysis and classification system (HFACS); (ii) quantitatively examine the relationships between the human factors of the cross levels in an entire system.

Methods: This study examined 234 major road traffic accidents recorded in 27 Chinese provinces from 1997 to 2014. Odds ratio (OR) was used to quantitatively analyze the relationships among the contributing factors.

Results: The frequencies of unsafe acts, violations, and inadequate regulation are the highest in five categories, 15 subcategories, and 63 indicators, respectively. This study has demonstrated a number of associations between the upper and adjacent lower levels. At the outside factors level, “failure to provide supervision for regulatory” can be viewed as a strong predictor to “formal accountability for actions,” “norms and rules,” and “values and beliefs.” At the organizational influences level, “formal accountability for actions,” “norms and rules,” and “values and beliefs” were strong predictors. At the unsafe supervision level, “failure to provide oversight,” “failure to initiate corrective action,” and “failure to enforce rules and regulations” had strong prediction on “fatigue driving.” At the preconditions for unsafe acts level, “visual limitation”, “fatigue driving,” and “vehicle faults” were strong predictors.

Conclusions: The generic HFACS failure types were interpreted and applied successfully to the road safety context, and such examination of major accidents has provided significant findings concerning the main contributing factors of those accidents. Using the OR technique, this study has demonstrated a number of associations between the upper level and adjacent lower levels in the entire system and has found the routes to failure, which is particularly important for developing countermeasures and remediation strategies, as it ensures that these countermeasures are targeted to a wider range of systems. Furthermore, these findings demonstrate the efficiency and applicability of the HFACS as a retrospective tool for the analysis of major road traffic accidents.

Funding

This work was supported by the National Social Science Fund of China (Project ID: 16BGL176, 19BGL233).

Notes

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