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Enhancing human reliability in ECDIS application and usability during navigational watch in congested waters: A SOHRA method analysis

  • Esma Uflaz
  • , Cagatay Kandemir
  • , Serap Goksu*
  • *Bu çalışma için yazışmadan sorumlu yazar
  • Ordu University
  • Recep Tayyip Erdogan University

Araştırma çıktısı: Dergi yayınıMakaleHakem

Özet

The Electronic Chart Display and Information System (ECDIS), introduced to improve navigation through real-time integration of multiple data sources, has become the primary tool for route planning and monitoring. However, groundings have shown that incorrect configuration, muted alarms, or overreliance on the system can result in accidents. While most studies focus on technical issues, limited research has explored the human reliability dimension of ECDIS use during navigational watch. This study applies the SOHRA method to evaluate human error in ECDIS tasks on crude oil tankers operating in congested waters. A total of 56 subtasks were examined across four accident-based scenarios, and Human Error Probabilities (HEPs) were calculated by linking task types with error-producing conditions. The results reveal differences between task types. Routine actions such as time settings, unit adjustments, and waypoint entry show low error probabilities, whereas tasks involving ENC setup, route planning and monitoring, overlay functions, and alarm configuration exhibit higher error likelihoods. Alarm-related tasks consistently demonstrate higher error probabilities. The findings indicate that human reliability in ECDIS operations is more strongly influenced by configuration and monitoring activities than by routine tasks. The results provide insights for improving operational procedures, training, and safety management, contributing to enhance navigational safety.

Orijinal dilİngilizce
Makale numarası125588
DergiOcean Engineering
Hacim357
DOI'lar
Yayın durumuYayınlandı - 1 Haz 2026

Bibliyografik not

Publisher Copyright:
© 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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