Abstract
Reorganization of a rail control post may affect its ability to cope with unexpected disruptions. The term ‘resilience’, the ability to manage spare adaptive capacity when unexpected events occur, encapsulates this situation. This paper focuses on the workload adaptive capacity through a method for revealing workload weak-resilience-signals (WRS). Three different workload measurements are adapted to identify structural changes in workload. The first, executed cognitive task load, targets system activities. The second, integrated workload scale, is a subjective measure. The last, heart rate variability, identifies physiological arousal because of workload. An experiment is designed to identify the workload change and distribution across group members during disruptions. A newly defined Stretch, the reaction of the system to an external cluster-event, is used to reveal a workload WRS. The method is suitable for real-time usage and provides the means for the rail signaler to influence the system through his subjective workload perception.
Chapter PDF
Similar content being viewed by others
Keywords
References
Hollnagel, E., Woods, D.D., Leveson, N. (eds.): Resilience engineering: concepts and percepts. Ashgate Publishing Limited, Hampshire (2006)
Siegel, A.W., Schraagen, J.M.: Developing resilience signals for the Dutch railway system. In: 5th Resilience Engineering Symposium (in press)
Pickup, L., Wilson, J.R., Nichols, S., Smith, S.: A conceptual framework of mental workload and the development of a self-supporting integrated workoad scale for railway signallers. In: Wilson, J., Norris, B.J., Clarke, T., Mills, A. (eds.) Rail Human Factors, pp. 319–329. Ashgate, Surrey (2005)
Veltman, J.A., Gaillard, A.W.K.: Pilot workload evaluated with subjective and physiological measures. In: Brookhuis, K., Weikert, C., Moraal, J., de Waard, D. (eds.) Aging and Human Factors, pp. 107–128. University of Groningen, Haren (1996)
Neerincx, M.A.: Cognitive task load analysis: allocating tasks and designing support. In: Hollnagel, E. (ed.) Handbook of Cognitive Task Design, pp. 283–305. Lawrence Erlbaum Associates, Mahwah (2003)
Pickup, L., Wilson, J.R., Norris, B.J., Mitchell, L., Morrisroe, G.: The integrated workload scale (IWS): a new self-report tool to assess railway signaller workload. Appl. Ergon. 36, 681–693 (2005)
Billman, G.E.: Heart rate variability - a historical perspective. Front. Physiol. 2, 86 (2011)
Goedhart, A.D., van der Sluis, S., Houtveen, J.H., Willemsen, G., de Geus, E.J.C.: Comparison of time and frequency domain measures of RSA in ambulatory recordings. Psychophysiology 44, 203–215 (2007)
Hoover, A., Singh, A., Fishel-Brown, S., Muth, E.: Real-time detection of workload changes using heart rate variability. Biomed. Signal Process. Control 7, 333–341 (2012)
Jorna, P.G.A.M.: Spectral analysis of heart rate and psychological state: A review of its validity as a workload index. Biol. Psychol. 34, 237–257 (1992)
Malik, M.: Heart Rate Variability. Ann. Noninvasive Electrocardiol. 1, 151–181 (1996)
Togo, F., Takahashi, M.: Heart rate variability in occupational health-a systematic review. Ind. Health 47, 589–602 (2009)
Rasmussen, J.: Risk management in a dynamic society: a modelling problem. Saf. Sci. 27, 183–213 (1997)
Wilms, M.S., Zeilstra, M.P.: Subjective mental workload of Dutch train dispatchers: Validation of IWS in a practical setting. In: 4th International Conference on Rail Human Factor, pp. 641–650 (2013)
Shadish, W.R., Cook, T.D., Campbell, D.T.: Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin Company, Boston (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Siegel, A.W., Schraagen, J.M. (2014). A Method to Reveal Workload Weak-Resilience-Signals at a Rail Control Post. In: Harris, D. (eds) Engineering Psychology and Cognitive Ergonomics. EPCE 2014. Lecture Notes in Computer Science(), vol 8532. Springer, Cham. https://doi.org/10.1007/978-3-319-07515-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-07515-0_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07514-3
Online ISBN: 978-3-319-07515-0
eBook Packages: Computer ScienceComputer Science (R0)