A framework to support human factors of automation in railway intelligent infrastructure

Abstract

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.

Abstract

Practitioner Summary: The framework reported in this paper can become the basis for human factors guidance of engineers, developers and business analysts in developing appropriate levels of information display, automation and decision aid into rail II. Guidance will be aimed at the different functions and activities within multi-layered, multi-agent control.

Keywords::

• rail systems
• intelligent infrastructure
• complex systems
• automation
• human factors guidance

Additional information

Funding

Funding

This research was funded by Network Rail Ergonomics Team and University of Nottingham Human Factors Research Group, UK. For earlier findings and work processes associated with this research program please refer to Dadashi et al. (2011a, 2011b).