Incident Factor Classification System

Gibson, Winifred; Smith, Samantha; Lowe, Emma; Mills, Albert J.; Morse, Geoff; Carpenter, S. R.

doi:10.1201/b13827-86

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…The findings in this paper could be used to analyze further how the R-PSFs affect human performance. Building on existing research, that is, the incident factors classification system (28), which is used to classify the factors that contribute to railway incident errors, the results of this study could be used to suggest a universal investigation reporting scheme focusing not only on the technical parts of an accident but also on the underlying factors.…”

Section: Discussionmentioning

confidence: 99%

Railway Accidents Caused by Human Error

Kyriakidis

Pak

Majumdar

2015

Transportation Research Record

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Accident investigation and analysis are key to reinforcing and improving railway safety. Many railway accidents have been caused by degraded human performance and human error, and the tasks of train drivers and signalers have remained essentially the same. Although new technologies and equipment have gradually reduced railway operation accidents, no investigation has been conducted to investigate whether railway performance shaping factors (R-PSFs), attributed to degraded human performance, have changed or remained constant. Focusing on UK railways, this paper analyzes railway accidents involving human error for the period 1945 to 2012. The purpose of the analysis is twofold: to identify whether the number and type of factors that affect human performance and contribute to human errors have changed during this period and to assess the quality of data collected by investigation reports and to determine whether the collection of such data has evolved and improved. The analysis identifies the number of R-PSFs and their relationship to such variables as responsible personnel, immediate causes, and the time and location of the event. The contribution of those variables to the severity of an accident is calculated. Moreover, any changes in trends and patterns in the number of R-PSFs over time are explored through smoothing techniques of time series analysis. Finally, the quality of the collected data is analyzed with the data quality index. Results show that data investigation and data collection have significantly improved. However, although accident rates have decreased, the average number and type of factors that affect human performance have remained the same.

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Section: Discussionmentioning

confidence: 99%

Railway Accidents Caused by Human Error

Kyriakidis

Pak

Majumdar

2015

Transportation Research Record

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“…the Swiss Federal Railways (SBB) and the UK Network Rail. Both the SBB (Swiss Federal Railways, 2010) and Network Rail (Gibson et al, 2013) have acknowledged the need to collect specific information with respect to human factors as significant contributors to railway occurrences.…”

Section: Data Requirements and Characteristicsmentioning

confidence: 99%

Data based framework to identify the most significant performance shaping factors in railway operations

2015

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A Comparison of Three Systemic Accident Analysis Methods Using 46 SPAD (Signals Passed at Danger) Incidents

Dixon

Waterson

Barnes

2017

Advances in Intelligent Systems and Computing

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During the period 1996-2003 there were five fatal accidents on the UK railway network, three of which were Signals Passed at Danger (SPAD) events (Watford Junction, 1996; Southall, 1997; Ladbroke Grove, 1999). SPAD events vary in severity and whilst most are not fatal there is the potential to cause serious injuries to passengers and train staff and damage to railway infrastructure. This paper investigates how the current system accident analysis tool used within the railway, the Incident Factor Classification System (IFCS) identifies and analyses causal factors of SPAD events. To evaluate the effectiveness IFCS was used to analysis SPAD incident reports (n=46) and the outputs were compared with two systemic accident analysis methods and relevant outputs (the Human Factors Analysis and Classification System-HFACS and Acci-Maps). The initial reporting process proved to hinder all systemic accident analysis methods in the extraction of causal factors. However, once extracted, all system accident analysis methods were successful in categorizing causal factors and demonstrated various outputs to illustrate the findings.

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Incident Factor Classification System

Cited by 5 publications

References 2 publications

Railway Accidents Caused by Human Error

Railway Accidents Caused by Human Error

Data based framework to identify the most significant performance shaping factors in railway operations

A Comparison of Three Systemic Accident Analysis Methods Using 46 SPAD (Signals Passed at Danger) Incidents

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