A seafarers’ cognitive error mining model based on IDA and TRACEr and mitigation measures for ship collision accidents

Yue Ma, Qing Liu and Liu Yang

Journal of Risk and Reliability, 2025, vol. 239, issue 4, 720-735

Abstract: Human factor is the main cause of maritime accidents. However, the in-depth study on the mechanism of cognitive errors in seafarers’ human error needs to be supplemented. This study empirically analyzes 116 collision cargo ships along the Yangtze River trunk line. To explore the relationship between seafarers’ task errors and the cognitive process of accidents, a seafarers’ cognitive error mining model is proposed, which integrates the Information, Decision, and Action (IDA) cognitive model into the Technique for the Retrospective and Predictive Analysis of Cognitive Errors (TRACEr). According to the approach of mining from the outside to the inside, firstly, the error mode in the cognitive stage of seafarer tasks are identified. Then the fine-grained main manifestation of the task errors is mined by K-means, and Apriori algorithm is employed to mine the hidden features between the external and internal error modes. The results show that there are four main problems of Yangtze River ship accidents, and seafarers have four to seven corresponding causal chains from psychological error mechanism to performance shaping factors for each major issue in the cognitive stage. On the basis of the results, this study summarizes the guiding principles of accident prevention and seafarer management measures to provide decision support for water traffic safety.

Keywords: Maritime transportation; shipping management; human factors; cognition; data mining; countermeasure (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:239:y:2025:i:4:p:720-735

DOI: 10.1177/1748006X241274514

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