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Task-induced fatigue when implementing high grades of railway automation

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Abstract

The study was focused on the effects of different grades of railway automation on task-induced fatigue and workload in train drivers and, when considering high grades of automation, operational staff in a control centre, so-called train operators. Train operators remotely monitor and manually drive automated trains upon system request during disruptions. As the task environment substantially differs depending on the grade of automation, effects on task- induced fatigue and workload levels were expected. To quantify and compare these effects, a simulator study with professional train drivers (N = 32) was conducted and the grade of automation was manipulated experimentally between subjects according to the railway specific automation taxonomy. Fatigue was assessed by the Karolinska Sleepiness Scale prior to and after a simulated working period of 2 h. Workload was assessed using the NASA-TLX. The results showed (a) significantly increasing fatigue levels over time (b) significantly higher fatigue ratings as a result of working with an intermediate grade of automation in comparison to working with a high grade of automation. Workload scores were (c) significantly higher in the high grade of automation group. Consequently, the introduction of high grades of automation may be used to tackle longstanding fatigue issues associated with train driving. The role of workload and limitations of the current research are discussed and recommendations for future research and operating companies are provided.

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References

  • Akerstedt T, Gillberg M (1990) Subjective and objective sleepiness in the active individual. Int J Neurosci 52(1–2):29–37. https://doi.org/10.3109/00207459008994241

    Article  Google Scholar 

  • Brandenburger N, Jipp M (2017) Effects of expertise for automatic train operations. Cogni Technol Work 19(4):699–709. https://doi.org/10.1007/s10111-017-0434-2

    Article  Google Scholar 

  • Brandenburger N, Naumann A (2018a) Enabling automatic train operation through human problem solving. Signal Draht 3:6–13

    Google Scholar 

  • Brandenburger N, Naumann A (2018b) Towards remote supervision and recovery of automated railway systems: the staff’s changing contribution to system resilience. In: Proceedings of the International Conference on Intelligent Rail Transportation. IEEE,  Singapore, pp 1–5

  • Brandenburger N, Naumann A (2018c) From in—cabin driving to remote interventions—train driver tasks change with railway automation. In de Waard D, Brookhuis K, Coelho D, Fairclough S, Manzey D, Naumann A, Onnasch L, Röttger S, Toffetti,Wiczorek R (eds) Human Factors and Ergonomics Society Europe Chapter 2018 Annual Conference. Downloaded from https://www.hfes-europe.org/wp-content/uploads/2018/10/Brandenburger2018Poster.pdf. Accessed 23 Aug 2019  

  • Brandenburger N, Hörmann HJ, Stelling D, Naumann A (2016) Tasks, skills, and competencies of future high-speed train drivers. Proc Inst Mech Eng Part F J Rail Rapid Transit. https://doi.org/10.1177/0954409716676509

    Article  Google Scholar 

  • Brandenburger N, Wittkowski M, Naumann A (2017) Countering train driver fatigue in automatic train operation. In: Golightly D, Fowler A, Ryan B, Kurup S, Mills A (eds) Proceedings of the sixth international human factors rail conference, rail safety and standards board, London, pp 57–65

  • Brandenburger N, Thomas-Friedrich B, Naumann A, Grippenkoven J (2018) Automation in railway operations: effects on signaller and train driver workload. In: Milius B, Naumann A (eds) Proceedings of the 3rd. German workshop on rail human factors. ITS mobility nord, Brunswick, pp 51–60

    Google Scholar 

  • Buck L, Lamonde F (1993) Critical incidents and fatigue among locomotive engineers. Safety Sci 16(1):1–18. https://doi.org/10.1016/0925-7535(93)90003-V

    Article  Google Scholar 

  • Caldwell JA, Mallis MM, Caldwell JL, Paul MA, Miller JC, Neri DF (2009) Fatigue countermeasures in aviation. Aviation Space Environ Med 80(1):29–59. https://doi.org/10.3357/ASEM.2435.2009

    Article  Google Scholar 

  • DaCoTA (2012) Fatigue: deliverable 4.8 h of the EC FP7 project DaCoTA. Retrieved from www.dacota-project.eu. Accessed 23 Aug 2019

  • de Waard D (1996) The measurement of drivers’ mental workload. University of Groningen, Groningen

    Google Scholar 

  • Desmond P, Hancock PA (2001) Active and passive fatigue states. In: Hancock PA, Desmond P (eds) Stress, workload, and fatigue. Lawrence Erlbaum Associates, New Jersey, pp 455–465

    Google Scholar 

  • Desmond P, Hancock PA, Monette J (1998) Fatigue and automation-induced impairments in simulated driving performance. Transp Res Rec 1628:8–14

    Article  Google Scholar 

  • Di Milla L, Smolensky MH, Costa G, Howarth HD, Ohayon MM, Philip P (2011) Demographic factors, fatigue, and driving accidents: an examination of the published literature. Accid Anal Prevent 43(2):516–532. https://doi.org/10.1016/j.aap.2009.12.018

    Article  Google Scholar 

  • Dinges DF (1995) An overview of sleepiness and accidents. J Sleep Res 4:4–14

    Article  Google Scholar 

  • Dinges DF, Kribbs NB (1991) Performing while sleepy: effects of experimentally-induced sleepiness. In: Monk TH (ed) Human performance and cognition. Sleep, sleepiness and performance. Wiley, Oxford, pp 97–128

    Google Scholar 

  • Dorrian J, Roach GD, Fletcher A, Dawson D (2006) The effects of fatigue on train handling during speed restrictions. Transp Res Part F Traff Psychol Behav 9(4):243–257. https://doi.org/10.1016/j.trf.2006.01.003

    Article  Google Scholar 

  • Dorrian J, Roach GD, Fletcher A, Dawson D (2007) Simulated train driving: fatigue, self-awareness and cognitive disengagement. Appl Ergon 38(2):155–166. https://doi.org/10.1016/j.apergo.2006.03.006

    Article  Google Scholar 

  • Dunn N, Williamson A (2012) Driving monotonous routes in a train simulator: the effect of task demand on driving performance and subjective experience. Ergonomics 55(9):997–1008

    Article  Google Scholar 

  • Endsley M, Kiris E (1995) The out-of-the-loop performance problem and level of control in automation. Human Fact 37(2):381–394

    Article  Google Scholar 

  • European Commission (2011) White paper on transport: roadmap to a single European transport area—towards a competitive and resource-efficient transport system. European Union, Brussels. https://ec.europa.eu/transport/sites/transport/files/themes/strategies/doc/2011_white_paper/white-paper-illustrated-brochure_en.pdf. Accessed 23 Aug 2019

  • European Railway Agency (2007) ERTMS/ETCS: Functional requirements specification FRS. https://www.era.europa.eu/sites/default/files/filesystem/ertms/ccs_tsi_annex_a_-_mandatory_specifications/set_of_specifications_1_etcs_b2_gsm-r_b1/index001_-_era_ertms_003204_v500.pdf. Accessed 23 Aug 2019

  • European Railway Agency (2016) ATO operational requirements. Retrieved from http://www.era.europa.eu/Document-Register/Documents/ATO_Ops_Requirements_v1_7.pdf. Accessed 23 Aug 2019

  • Filtness AJ, Naweed A (2017) Causes, consequences and countermeasures to driver fatigue in the rail industry: the train driver perspective. Appl Ergon 60:12–21. https://doi.org/10.1016/j.apergo.2016.10.009

    Article  Google Scholar 

  • Friswell R, Williamson A (2008) Exploratory study of fatigue in light and short haul transport drivers in NSW, Australia. Accid Anal Prevent 40(1):410–417. https://doi.org/10.1016/j.aap.2007.07.009

    Article  Google Scholar 

  • Grant JS (1971) Concepts of fatigue and vigilance in relation to railway operation. Ergonomics 14(1):111–118. https://doi.org/10.1080/00140137108931229

    Article  Google Scholar 

  • Grippenkoven J, Rodd J, Brandenburger N (2018) DLR-WAT: Ein Instrument zur Untersuchung des optimalen Beanspruchungsniveaus in hochautomatisierten Mensch-Maschine-Systemen. In: AAET- Automatisiertes und vernetztes Fahren. ITS automotive nord, Brunswick Germany, pp 199–213 [publication in German]

  • Harris WC, Hancock PA, Arthur EJ, Caird JK (1995) Performance, workload, and fatigue changes associated with automation. Int J Aviat Psychol 5(2):169–185. https://doi.org/10.1207/s15327108ijap0502_3

    Article  Google Scholar 

  • International Association of public Transport (2012) Metro automation facts, figures and trends: a global bid for automation: UITP observatory of automated metros confirms sustained growth rates for the coming years. Retrieved from www.uitp.org/metro-automation-facts-figures-and-trends. Accessed 23 Aug 2019

  • Jap B, Fischer P, Bekiaris E (2007) Using spectral analysis to extract frequency components from electroencephalography: application for fatigue countermeasure in train drivers. In: The 2nd international conference on wireless broadband and ultra wideband communication. IEEE, Sydney, pp 13–13

  • Jap B, Lal S, Fischer P (2011) Comparing combinations of EEG activity in train drivers during monotonous driving. Expert Systems with Applications 38(1):996–1003

    Article  Google Scholar 

  • Jipp M, Ackerman PL (2016) The impact of higher levels of automation on performance and situation awareness: a function of information-processing ability and working-memory capacity. J Cogni Eng Decis Mak. https://doi.org/10.1177/1555343416637517

    Article  Google Scholar 

  • Johns MW (2000) A sleep physiologist’s view of drowsy driving. Transp Res Part F Traff Psychol Behav 3:241–249

    Article  Google Scholar 

  • Kaida K, Takahashi M, Akerstedt T, Nakata A, Otsuka Y, Haratani T, Fukasawa K (2006) Validation of the Karolinska sleepiness scale against performance and EEG variables. Clin Neurophysiol 117(7):1574–1581. https://doi.org/10.1016/j.clinph.2006.03.011

    Article  Google Scholar 

  • Lal SK, Craig A (2002) Driver fatigue: electroencephalography and psychological assessment. Psychophysiology 39(3):313–321. https://doi.org/10.1017/S0048577201393095

    Article  Google Scholar 

  • Mackworth NH (1948) The breakdown of vigilance during prolonged visual search. Q J Exp Psychol 1(1):6–21. https://doi.org/10.1080/17470214808416738

    Article  Google Scholar 

  • Naweed A (2013) Investigations into the skills of modern and traditional train driving. Appl Ergon 45(3):462–470. https://doi.org/10.1016/j.apergo.2013.06.006

    Article  Google Scholar 

  • Onnasch L, Wickens CD, Li H, Manzey D (2014) Human performance consequences of stages and levels of automation: an integrated meta-analysis. Human Fact 56(3):476–488. https://doi.org/10.1177/0018720813501549

    Article  Google Scholar 

  • Parasuraman R, Sheridan T, Wickens C (2000) A model for types and levels of human interaction with automation. In: IEEE Transactions on systems, man and cybernetics-Part A: systems and humans, vol 30, issue 3. IEEE, pp 286–297

  • Parasuraman R, Sheridan TB, Wickens CD (2008) Situation awareness, mental workload, and trust in automation: viable, empirically supported cognitive engineering constructs. J Cognit Eng Dec Mak 2(2):140–160. https://doi.org/10.1518/155534308X284417

    Article  Google Scholar 

  • Persson R, Garde AH, Hansen ÅM, Ørbaek P, Ohlsson K (2003) The influence of production systems on self-reported arousal, sleepiness, physical exertion and fatigue-consequences of increasing mechanization. Stress Health 19(3):163–171. https://doi.org/10.1002/smi.967

    Article  Google Scholar 

  • Saxby DJ, Matthews G, Hitchcock EM, Warm JS (2007) Development of active and passive fatigue manipulations using a driving simulator. In: Proceedings of the human factors and ergoniomics society 51st annual meeting. Human factors and ergonomics society, Baltimore, pp 1237–1241

  • Saxby DJ, Matthews G, Hitchcock EM, Warm J S, Funke G, Gantzer T (2008) Effect of active and passive fatigue on performance using a driving simulator. In: Proceedings of the human factors and ergoniomics society 52nd annual meeting. Human Factors and Ergonomics Society, New York City, pp 1751–1755

  • Spring P, McIntosh A, Caponecchia C, Baysari M (2008) Level of automation: effects on train driver vigilance. 44th annual human factors and ergonomics society of Australia Conference, pp 264–271

  • Spring P, McIntosh A, Baysari M (2009) Counteracting the negative effects of high levels of train automation on driver vigilance. HFESA Conf Proc 45:93–101

    Google Scholar 

  • Staveland L, Hart S (1988) Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. Adv Psychol 52:139–183

    Article  Google Scholar 

  • Stein J, Naumann A (2016) Monotony, fatigue and microsleeps—train drivers daily routine: a simulator study. In: Milius B, Naumann A (eds) Proceedings of the 2nd workshop on human factors. ITS automotive nord, Braunschweig, pp 96–102

    Google Scholar 

  • Vogelpohl T, Kühn M, Hummel T, Vollrath M (2019) Asleep at the automated wheel—sleepiness and fatigue during highly automated driving. Acc Anal Prevent 126:70–84. https://doi.org/10.1016/j.aap.2018.03.013

    Article  Google Scholar 

  • Wickens CD, Li H, Santamaria A, Sebok A, Sarter NB (2010) Stages and levels of automation: an integrated meta-analysis. Proc Human Fact Ergon Soc Ann Meet 54(4):389–393. https://doi.org/10.1177/154193121005400425

    Article  Google Scholar 

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Funding

This work was part of the projects Next Generation Train and Next Generation Railway Systems of the German Aerospace Center (DLR). These projects are funded by the Helmholtz Association.

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Correspondence to Anja Naumann.

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Brandenburger, N., Naumann, A. & Jipp, M. Task-induced fatigue when implementing high grades of railway automation. Cogn Tech Work 23, 273–283 (2021). https://doi.org/10.1007/s10111-019-00613-z

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