Analysing human error contribution to ship collision risk in congested waters under the evidential reasoning SPAR-H extended fault tree analysis

Abstract

Human error plays a crucial role in maritime transportation risk analysis, as a significant percentage of accidents, including collisions, groundings, capsizing, fires, and explosions, can be attributed to human errors. However, obtaining a dataset that quantifies human error probabilities for maritime risk analysis is challenging due to commercial constraints. To address this issue, this paper proposes a conceptual framework that integrates evidential reasoning (ER) and the standardized plant analysis risk-human reliability analysis (SPAR-H) method to quantify human errors, while employing fault tree analysis (FTA) to predict risk. The specific focus of this study is ship collision risk in congested waters, which serves as a demonstration case to showcase the proposed method and illustrate a detailed analysis of collision risk. The findings reveal that “inadequate watchkeeping due to sole lookout”, “improper RADAR monitoring”, and “ineffective execution of COLREG-related actions” are the most significant human errors contributing to collision risk in congested waters. The outcomes of this research provide valuable insights for ship owners, safety professionals, ship masters, inspectors, and researchers in the maritime industry. The findings can assist in minimizing collision risk and improving navigational safety in congested waters.