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Modelling decision making within rail maintenance control rooms

Lookup NU author(s): Dr David GolightlyORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


This paper presents a cognitive task analysis to derive models of decision making for rail maintenance processes. Maintenance processes are vital for safe and continuous availability of rail assets and services. These processes are increasingly embracing the ‘Intelligent Infrastructure’ paradigm, which uses automated analysis to predict asset state and potential failure. Understanding the cognitive processes of maintenance operators is critical to underpin design and acceptance of Intelligent Infrastructure. A combination of methods, including observation, interview and an adaption of critical decision method, was employed to elicit the decision-making strategies of operators in three different types of maintenance control centre, with three configurations of pre-existing technology. The output is a model of decision making, based on Rasmussen’s decision ladder, that reflects the varying role of automation depending on technology configurations. The analysis also identifies which types of fault were most challenging for operators and identifies the strategies used by operators to manage the concurrent challenges of information deficiencies (both underload and overload). Implications for design are discussed.

Publication metadata

Author(s): Dadashi N, Golightly D, Sharples S

Publication type: Article

Publication status: Published

Journal: Cognition, Technology and Work

Year: 2021

Volume: 23

Pages: 255-271

Print publication date: 01/05/2021

Online publication date: 20/06/2020

Acceptance date: 08/06/2020

Date deposited: 08/06/2020

ISSN (print): 1435-5558

ISSN (electronic): 1435-5566

Publisher: Springer Verlag


DOI: 10.1007/s10111-020-00636-x


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