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Are you fit to continue?: approaching rail systems thinking at the cusp of safety and the apex of performance

Version 2 2022-08-25, 21:35
Version 1 2017-12-06, 00:00
journal contribution
posted on 2022-08-25, 21:35 authored by Anjum NaweedAnjum Naweed, Sophia Rainbird, C Dance
The incidence of driving a train through a stop signal continues to have implications for safety on railways. Industry rulebooks advise how to manage these events, but there has been very little investigation of causality from the systems-view. The increasing trend for maximising rail capacities could be exacerbating the issue and warrants investigation from this perspective to determine the factors impinging on safety decisions in train driving. A participative research approach incorporating cab rides, focus groups, and a generative scenario simulation exercise was used to investigate how train movements and safety risk was managed, and the implications of this on the rail organisation. Twenty-eight train drivers participated from eight passenger rail organisations across Australia and New Zealand. Inductive thematic analysis of the data revealed factors associated with (1) changes to signal meaning, (2) the nature of the driver-signal relationship, and (3) the confounding practice of asking a driver if they were “fit to continue” driving after going through a stop signal. The findings reflected a strong pattern of a normalisation of deviance. The results are discussed in terms of the mechanisms underlying the observed phenomenon and a model outlining prospective solutions for future research is presented to contribute to the development of novel ideas for further thinking and research.

Funding

Category 4 - CRC Research Income

History

Volume

76

Start Page

101

End Page

110

Number of Pages

10

ISSN

0925-7535

Publisher

Elsevier

Peer Reviewed

  • Yes

Open Access

  • No

External Author Affiliations

Rail Corporation New South Wales, Australia

Author Research Institute

  • Appleton Institute

Era Eligible

  • Yes

Journal

Safety Science