인적오류로 인한 철도사고 예방을 위한 Framework 개발

초록

Recent incidents of railway derailments and staff fatalities have highlighted the persistent issue of railway accidents. Despite advancements in high-speed trains and automated, complex railway systems, operations and maintenance still heavily rely on human workers. Human error remains a significant factor in railway accidents, underscoring the critical need for system improvements and advanced safety management frameworks to prioritize safety and mitigate human error-related risks. This study aims to develop an advanced framework for preventing railway accidents caused by human errors. The research encompasses four major areas: (1) the development of a system for collecting and analyzing data on railway workers, including health information, work hours, camera footage, and biometric data such as blood pressure and heart rate; (2) the implementation of real-time safety support systems for railway workers using smart helmets and paperless tools; (3) the development of an integrated management system to evaluate and predict human errors through task analysis, identify safety and non-safety tasks, and quantify impact factors, similar to human reliability analysis; and (4) the development of a multiuser virtual training system for joint emergency response training; this system will enable multiple railway workers to train simultaneously, with real-time comprehensive analysis of training effectiveness based on the biometric signals of trainees.

키워드