Pathways to Failure? Using Work Domain Analysis to Predict Accidents in Complex Systems

Abstract

Forecasting accidents before they occur is the final frontier for safety science. Although this has long been recognized, the discipline of human factors has yet to produce an appropriate methodology for achieving this. This paper presents some of the findings from an exploratory study in which the abstraction hierarchy method from the work domain analysis phase of cognitive work analysis was used to predict potential accidents. Using rail level crossings as a test case, the exploratory study revealed that the abstraction hierarchy method was able to predict a range of failure pathways that could potentially lead to a collision between a road user and a train at rail level crossings. In addition, certain features of the abstraction hierarchy method were found to make it highly consistent with contemporary systems level views on accident causation, including that it provides a systems level analysis of potential accident pathways, that is does not support a focus on broken human components (since the abstraction hierarchy model is actor independent), and that the primary focus is on the relationships between components rather than the components themselves. Further testing of the approach is recommended, including sensitivity and validity testing whereby the predictions made are compared to real world events.

Keywords: Rail Level Crossing Safety, Accident Prediction, Cognitive Work Analysis

DOI: 10.54941/ahfe100688