Task-based human error probability assessment in maritime pilotage using a dual-intuitionistic fuzzified SLIM framework

Maritime pilotage is a critical navigational practice that ensures the safe passage of vessels through high-risk areas such as ports, straits, and canals. These operations require advanced ship-handling skills and deep local knowledge, particularly when bridge teams are unfamiliar with the operating environment. The complexity of pilotage, which arises from variable vessel characteristics, changing environmental conditions, and regulatory demands, makes human reliability a central concern. Traditional human reliability methods often struggle to fully capture the uncertainty inherent in expert judgment. To address this, the present study proposes a novel framework based on the Intuitionistic Fuzzy Success Likelihood Index Method (IF-SLIM) for estimating human error probabilities (HEPs) during pilotage operations. By integrating intuitionistic fuzzy set theory into SLIM, the model allows expert input to be captured through membership and non-membership functions improving the realism of performance assessment under uncertainty. The dual-fuzzification approach is applied to both performance shaping factors and manoeuvring tasks, offering detailed insights into task-specific risk. The proposed framework aims to support pilotage authorities and maritime safety stakeholders in identifying high-risk areas, enhancing pilot assignment strategies, and improving overall reliability in manoeuvring operations.