Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
Computer Sciences, *human – machine relations
Abstract
The introduction of systems such as Traffic Management (TM) will result in a number of changes in how the railway is managed for operations and maintenance staff such as, an increase in collaborative working styles and shared responsibilities. In order to react to these changing operational demands and user needs, TM workstation designs need to have greater flexibility and be configurable to support the information requirements for each specific role as well as support each role during different scenarios. Although this flexibility in system design has the potential to enhance performance, it increases the complexity of measuring operator workload. The In2Rail project explored these issues and this paper summarises the outputs; key future workload principles to consider, a proposed toolset to forecast workload and modifications to existing measurement techniques.
DOI
https://doi.org/10.21427/D79S5T
Recommended Citation
Evans, J. (2017). A systems approach to predicting and measuring workload in rail traffic management systems. H-Workload 2017: The first international symposium on human mental workload, Dublin Institute of Technology, Dublin, Ireland, June 28-30. doi:10.21427/D79S5T isbn:9781900454637 (vol)
Included in
Artificial Intelligence and Robotics Commons, Behavior and Behavior Mechanisms Commons, Graphics and Human Computer Interfaces Commons
Publication Details
H-Workload 2017: The first international symposium on human mental workload, Dublin Institute of Technology, Dublin, Ireland, June 28-30.