A framework to support human factors of automation in railway intelligent infrastructure
Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the genera...
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| Format: | Article |
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Taylor & Francis
2014
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| Online Access: | https://eprints.nottingham.ac.uk/45236/ |
| _version_ | 1848797094151716864 |
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| author | Dadashi, Nastaran Wilson, John R. Golightly, David Sharples, Sarah |
| author_facet | Dadashi, Nastaran Wilson, John R. Golightly, David Sharples, Sarah |
| author_sort | Dadashi, Nastaran |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications. |
| first_indexed | 2025-11-14T19:58:24Z |
| format | Article |
| id | nottingham-45236 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:58:24Z |
| publishDate | 2014 |
| publisher | Taylor & Francis |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-452362020-05-04T16:44:08Z https://eprints.nottingham.ac.uk/45236/ A framework to support human factors of automation in railway intelligent infrastructure Dadashi, Nastaran Wilson, John R. Golightly, David Sharples, Sarah Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications. Taylor & Francis 2014-03-27 Article PeerReviewed Dadashi, Nastaran, Wilson, John R., Golightly, David and Sharples, Sarah (2014) A framework to support human factors of automation in railway intelligent infrastructure. Ergonomics, 57 (3). pp. 387-402. ISSN 1366-5847 rail systems intelligent infrastructure complex systems automation human factors guidance http://www.tandfonline.com/doi/abs/10.1080/00140139.2014.893026 doi:10.1080/00140139.2014.893026 doi:10.1080/00140139.2014.893026 |
| spellingShingle | rail systems intelligent infrastructure complex systems automation human factors guidance Dadashi, Nastaran Wilson, John R. Golightly, David Sharples, Sarah A framework to support human factors of automation in railway intelligent infrastructure |
| title | A framework to support human factors of automation in railway intelligent infrastructure |
| title_full | A framework to support human factors of automation in railway intelligent infrastructure |
| title_fullStr | A framework to support human factors of automation in railway intelligent infrastructure |
| title_full_unstemmed | A framework to support human factors of automation in railway intelligent infrastructure |
| title_short | A framework to support human factors of automation in railway intelligent infrastructure |
| title_sort | framework to support human factors of automation in railway intelligent infrastructure |
| topic | rail systems intelligent infrastructure complex systems automation human factors guidance |
| url | https://eprints.nottingham.ac.uk/45236/ https://eprints.nottingham.ac.uk/45236/ https://eprints.nottingham.ac.uk/45236/ |