Impact of automation: Measurement of performance, workload and behaviour in a complex control environment. (March 2015)

• Record Type: Journal Article
• Authors: Balfe, Nora; Sharples, Sarah; Wilson, John R.
• Is Part Of: Applied ergonomics. Volume 47(2015:Mar.)
• Page Start: 52
• Page End: 64
• Publication Date: 2015-03
• Subjects: Automation -- Rail human factors -- Workload -- Performance; Human engineering -- Periodicals; 620.82
• DOI: 10.1016/j.apergo.2014.08.002
• Languages: English
• ISSNs: 0003-6870

Abstract

Abstract: This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a Rail Automation Model based on previous automation theory (Parasuraman et al., 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity. Highlights: We compared three levels of automation in an ecologically valid rail signalling environment. We measured performance, subjective workload and operator activity for each level. Workload decreased as automation increased for both normal and disrupted conditions. Performance became more consistent across participants as automation increased. Individual operators engage in different strategies when working with automation.