Skip to main content

A Workflow Perspective in Aviation

  • Chapter
  • First Online:
Cognitive Informatics

Part of the book series: Health Informatics ((HI))

  • 710 Accesses

Abstract

During the last three decades, aircraft cockpits have been highly automated and incrementally digitized to the point that we now talk about “interactive cockpits”, not because pilots interact with the mechanical part of the aircraft directly, but because they use a pointing device to interact with computer screens. More generally, computers invaded the airspace ranging from onboard aircraft to air traffic control (ATC) ground services. In terms of workflow, the elimination of the flight-engineer onboard commercial aircraft cockpits drastically transformed the way pilots fly—this was done in the beginning of the 1980s. Pilot’s activity shifted from manual control to cognitive management of embedded systems (performing some of the tasks the flight engineer used to do). Aircraft automation considerably improved commercial aviation safety. Today, main issues come from the exponential increase of the number of aircraft in the sky. Air traffic complexity imposes drastic reengineering of air traffic workflow. ATC is shifting towards air traffic management (ATM). Same thing: moving from control to management, expanding cockpit’s single agent problems and solutions to air traffic multi-agent problems and solutions. The main emphasis is therefore social cognition. During the twentieth century, we automated physical systems—we now talk about cyber-physical systems (i.e., we shifted from hardware mechanical engineering issues to software cognitive problems). During the beginning of the twenty-first century, almost all systems are first ideated and designed as pieces of software, and they are transformed into tangible things. Consequently, workflow can be modeled and simulated very early during the design process and, unlike during the twentieth century, functions and therefore activities can be tested before anything is physically built. This provides great possibilities that should be operationalized and implemented. This chapter will show that the main issue has become tangibility, instead of automation. At the same time, these new possibilities provided by our emerging digital world enable a brand-new move towards more autonomous systems that need to be coordinated. We will illustrate this shift from automation towards autonomy, by providing salient examples and generic patterns of this evolution of workflow in the aviation domain.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Fitt’s HABA-MABA (humans-are-better-at/machines-are-better-at) approach provided generic strengths and weaknesses of humans and machines.

  2. 2.

    “Airlines recorded zero accident deaths in commercial passenger jets last year, according to a Dutch consulting firm and an aviation safety group that tracks crashes, making 2017 the safest year on record for commercial air travel” (https://www.reuters.com/article/us-aviation-safety/2017-safest-year-on-record-for-commercial-passenger-air-travel-groups-idUSKBN1EQ17L).

References

  • Athènes S, Averty P, Puechmorel S, Delahaye D, Collet C. ATC complexity and controller workload: trying to bridge the gap. In: Hansman J, Chatty S, Boy G, editors. Proceedings of HCI-Aero’02. Boston; 2002.

    Google Scholar 

  • Bainbridge L. Forgotten alternatives in skill and workload. Ergonomics. 1978;21:169–85.

    Article  CAS  Google Scholar 

  • Boy GA. The MESSAGE system: a first step toward computer-supported analysis of human-machine interactions (in French). Le Travail Humain J. 1983;46(2).

    Google Scholar 

  • Boy GA. Operator assistant systems. Int J Man Mach Stud. 1987;27:541–54.

    Article  Google Scholar 

  • Boy GA. Cognitive function analysis. New York: Praeger/Ablex; 1998. ISBN 9781567503777.

    Google Scholar 

  • Boy GA. Maturity, automation and user experience (maturité, automation et experience des utilisateurs). In: Proceeding of the French conference on human-computer interaction. New York: ACM; 2005.

    Google Scholar 

  • Boy GA, editor. Handbook of human-machine interaction: a human-centered design approach. Farnham: Ashgate; 2011. ISBN: 978-0-7546-7580-8.

    Google Scholar 

  • Boy GA. Orchestrating human-centered design. London: Springer; 2013. ISBN: 978-1-4471-4338-3.

    Book  Google Scholar 

  • Boy GA. On the complexity of situation awareness. In: Proceedings 19th Triennial Congress of the IEA, Melbourne, Australia, 9–14; 2015.

    Google Scholar 

  • Boy GA. Tangible interactive systems: grasping the real world with computers. London: Springer; 2016. ISBN: 978-3-319-30270-6.

    Book  Google Scholar 

  • Boy GA, Grote G. Authority in increasingly complex human and machine collaborative systems: application to the future air traffic management construction. In: Proceedings of the 2009 International Ergonomics Association World Congress, Beijing, China; 2009.

    Google Scholar 

  • Boy GA, Tessier C. Cockpit analysis and assessment by the MESSAGE methodology. In: Proceedings of the 2nd IFAC/IFIP/IFORS/IEA conf. on analysis, design and evaluation of man-machine systems, Villa-Ponti, Italy, September 10–12. Oxford: Pergamon Press; 1985. p. 73–9.

    Google Scholar 

  • Callon M. Techno-economic networks and irreversibility. In: Law J, editor. A sociology of monsters: essays on power, technology and domination. London: Routledge; 1991. p. 132–61.

    Google Scholar 

  • Carroll JM. Scenario-based design: envisioning work and technology in system development. New York: Wiley; 1995.

    Google Scholar 

  • Cooper GE, White MD, Lauber JI. Resource management on the flight deck. In: Proceedings of a NASA/Industry Workshop Held at San Francisco, California June 26-28, 1979. NASA Conference Publication 2120, NASA Ames Research Center, CA; 1980.

    Google Scholar 

  • Cummings ML, Tsonis CG. Partitioning complexity in air traffic management tasks. Int J Aviat Psychol. 2006;16(3):277–95.

    Article  Google Scholar 

  • Doyon-Poulin P, Ouellette B, Robert JM. Effects of visual clutter on pilot workload, flight performance and gaze pattern. In: Proceedings of HCI-Aero 2014, Santa Clara, CA. Also in the ACM Digital Library; 2014.

    Google Scholar 

  • Endsley MR. Situation awareness global assessment technique (SAGAT). In: Paper presented at the National Aerospace and Electronic Conference (NAECON), Dayton, OH; 1988.

    Google Scholar 

  • Endsley MR. Automation and situation awareness. In: Parasuraman R, Mouloua M, editors. Automation and human performance: theory and applications. Mahwah, NJ: Laurence Erlbaum; 1996. p. 163–81.

    Google Scholar 

  • Fitts PM, editor. Human engineering for an effective air navigation and traffic control system. Washington, DC: National Research Council; 1951.

    Google Scholar 

  • Gander P, Graeber C, Belenky G. Operator fatigue: implications for human-machine interaction. In: Handbook of human-machine interaction: a human-centered design approach. London: Ashgate; 2011.

    Google Scholar 

  • Grote G. Uncertainty management at the core of system design. Annu Rev Control. 2004;28:267–74.

    Article  Google Scholar 

  • Hamilton S. Thinking outside the box at the IHMC. IEEE Computer, January, 0018-9162/01; 2001. p. 61–71.

    Google Scholar 

  • Hart SG. Theoretical basis for workload assessment. TM ADP001150. Moffett Field, CA: NASA-Ames Research Center; 1982.

    Google Scholar 

  • Helmreich RL, Merritt AC, Wilhelm JA. The evolution of crew resource management training in commercial aviation. Int J Aviat Psychol. 1999;9(1):19–32.

    Article  CAS  Google Scholar 

  • Hemingway CJ. Toward a socio-cognitive theory of information systems: an analysis of key philosophical and conceptual issues. In: IFIP WG 8.2 and 8.6 Joint Working Conference on information systems: current issues and future changes. Helsinki: IFIP; 1999. p. 275–86.

    Google Scholar 

  • Hilburn B. Cognitive complexity in air traffic control: a literature review. Project COCA—COmplexity and CApacity. EEC Note No. 04/04; 2004.

    Google Scholar 

  • Hoc JM, Lemoine MP. Cognitive evaluation of human-human and human-machine cooperation modes in Air Traffic control. Int J Aviat Psychol. 1998;8(1):1–32.

    Article  Google Scholar 

  • Hutchins E. How a cockpit remembers its speeds. Cogn Sci. 1995;19:265–88.

    Article  Google Scholar 

  • Latour B. Science in action: how to follow scientists and engineers through society. Cambridge, MA: Harvard University Press; 1987.

    Google Scholar 

  • Laudeman IV, Shelden SG, Branstrom R, Brasil CL. Dynamic density. An Air Traffic management metric. Mountain View, CA: National Aeronautics and Space Administration, Ames Research Center; 1998. NASA/TM-1998-112226.

    Google Scholar 

  • Leveson N, Dulac N, Marais K, Carroll J. Moving beyond normal accidents and high reliability organizations: a systems approach to safety in complex systems. Organ Stud. 2009;30(2-3).

    Article  Google Scholar 

  • Mogford RH. Mental models and situation awareness in air traffic control. Int J Aviat Psychol. 1997;7(4):331–41.

    Article  Google Scholar 

  • Paulk M, Curtis B, Chrissis M, Weber C. Capability maturity model for software (Version 1.1). Technical Report CMU/SEI-93-TR-024; 1993.

    Google Scholar 

  • Schwaber K. Scrum development process. In: Sutherland J, Patel D, Casanave C, Miller J, Hollowell G, editors. OOPSLA business objects design and implementation workshop proceedings. London: Springer; 1997.

    Google Scholar 

  • Sharples M, Jeffery N, du Boulay JBH, Teather D, Teather B, du Boulay GH. Socio-cognitive engineering: A methodology for the design of human-centered technology. Eur J Oper Res. 2002;136(2):310–23.

    Article  Google Scholar 

  • Sperandio JC. La psychologie en ergonomie (Psychology in ergonomics). Paris: PUF; 1980.

    Google Scholar 

  • Sutherland J. Scrum: the art of doing twice the work in half the time. New York: Crown Business; 2014. ISBN-13: 978-0385346450.

    Google Scholar 

  • Wickens CD. Engineering psychology and human performance. 2nd ed. New York: Harper Collins; 1992. ISBN: 0673461610.

    Google Scholar 

  • Wiener EL. Human factors of advanced technology (“glass cockpit”) transport aircraft. (NASA Contractor Report No. 177528). Moffett Field, CA: NASA-Ames Research Center; 1989.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guy André Boy .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Boy, G.A. (2019). A Workflow Perspective in Aviation. In: Zheng, K., Westbrook, J., Kannampallil, T., Patel, V. (eds) Cognitive Informatics. Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-16916-9_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-16916-9_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16915-2

  • Online ISBN: 978-3-030-16916-9

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics