Human factors of future rail intelligent infrastructure

Dadashi, Nastaran (2012) Human factors of future rail intelligent infrastructure. PhD thesis, University of Nottingham.

PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (6MB) | Preview


The introduction of highly reliable sensors and remote condition monitoring equipment will change the form and functionality of maintenance and engineering systems within many infrastructure sectors. Process, transport and infrastructure companies are increasingly looking to intelligent infrastructure to increase reliability and decrease costs in the future, but such systems will present many new (and some old) human factor challenges. As the first substantial piece of human factors work examining future railway intelligent infrastructure, this thesis has an overall goal to establish a human factors knowledge base regarding intelligent infrastructure systems, as used in tomorrow’s railway but also in many other sectors and industries.

An in-depth interview study with senior railway specialists involved with intelligent infrastructure allowed the development and verification of a framework which explains the functions, activities and data processing stages involved. The framework includes a consideration of future roles and activities involved with intelligent infrastructure, their sequence and the most relevant human factor issues associated with them, especially the provision of the right information in the right quantity and form to the right people.

In a substantial fieldwork study, a combination of qualitative and quantitative methods was employed to facilitate an understanding of alarm handling and fault finding in railway electrical control and maintenance control domains. These functions had been previously determined to be of immediate relevance to work systems in the future intelligent infrastructure. Participants in these studies were real railway operators as it was important to capture users’ cognition in their work settings. Methods used included direct observation, debriefs and retrospective protocols and knowledge elicitation.

Analyses of alarm handling and fault finding within real-life work settings facilitated a comprehensive understanding of the use of artefacts, alarm and fault initiated activities, along with sources of difficulty and coping strategies in these complex work settings. The main source of difficulty was found to be information deficiency (excessive or insufficient information). Each role requires different levels and amounts of information, a key to good design of future intelligent infrastructure.

The findings from the field studies led to hypotheses about the impact of presenting various levels of information on the performance of operators for different stages of alarm handling. A laboratory study subsequently confirmed these hypotheses.

The research findings have led to the development of guidance for developers and the rail industry to create a more effective railway intelligent infrastructure system and have also enhanced human factors understanding of alarm handling activities in electrical control.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Wilson, J.R
Golightly, D.
Sharples, S.C.
Keywords: Interactive computer systems, railroads, electronic equipment, maintenance and repair, intelligent control systems
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering systems. Automatic machinery
Faculties/Schools: UK Campuses > Faculty of Engineering > Department of Mechanical, Materials and Manufacturing Engineering
Item ID: 13157
Depositing User: EP, Services
Date Deposited: 20 Mar 2013 11:56
Last Modified: 16 Dec 2017 17:11

Actions (Archive Staff Only)

Edit View Edit View