Automation transparency and the design of intelligent aircraft engine interfaces

In this article we report progress on a programme of research to implement intelligent engine systems in civil aircraft. Modern turbofan engines capture data about their performance and health during flight. Until now, this information has remained hidden from the flight deck. Our research will examine how best to communicate these new information sources to the flight deck to deliver intelligent assistance in understanding engine health and offering choices to minimise disruption should an engine develop a fault that affects performance. We have adopted automation transparency as a key design pillar to ensure that flight crew have an appropriate understanding of the reasoning of the intelligent system under different operating conditions. User-centred design will inform the degree to which the different interface elements are transparent, informing the balance between the provision of information necessary to ensure safe and efficient performance. Currently, there is significant uncertainty as to whether automation transparency can confer a performance advantage in all cases. Our research will empirically investigate different levels of automation transparency to validate performance.

Content

Author and article information

Contributors

Jim Nixon

Richard Clewley

Tendai Rukasha

Conference

Publication date: July 2022

Publication date (Print): July 2022

Pages: 1-5

Affiliations

[0001]Cranfield University

Cranfield Safety and Accident Investigation Centre

College Road

Cranfield, Bedfordshire

MK43 0AL

Article

DOI: 10.14236/ewic/HCI2022.40

SO-VID: c081fc59-5fc7-44fa-844c-ac1241f276bc

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: 35th International BCS Human-Computer Interaction Conference

Conference acronym: HCI2022

Conference number: 35

Conference location: Keele, Staffordshire

Conference date: July 11th to 13th, 2022

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Towards a Human-Centred Digital Society

History

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1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2022.40

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

Asmayawati, S., & Nixon, J. (2020). Modelling and supporting flight crew decision-making during aircraft engine malfunctions: developing design recommendations from cognitive work analysis. Applied Ergonomics, 82(May 2019), 102953.
Chen, J. Y. C., Lakhmani, S. G., Stowers, K., Selkowitz, A. R., Wright, J. L., & Barnes, M. (2018). Situation awareness-based agent transparency and human-autonomy teaming effectiveness. Theoretical Issues in Ergonomics Science, 19(3), 259–282. https://doi.org/10.1080/1463922X.2017.1315750
Clewley, R., & Nixon, J. (2019). Understanding pilot response to flight safety events using categorisation theory. Theoretical Issues in Ergonomics Science, 20(5). https://doi.org/10.1080/1463922X.2019.1574929
Clewley, R., & Nixon, J. (2020). Penguins, Birds, and Pilot Knowledge: Can an Overlooked Attribute of Human Cognition Explain Our Most Puzzling Aircraft Accidents? Human Factors. https://doi.org/10.1177/0018720820960877
Clewley, R., & Nixon, J. (2021). Now you see it, now you don’t: dynamism amplifies the typicality effect. Cognition, Technology & Work. https://doi.org/10.1007/s10111-021-00686-9
Endsley, M. R. (1995). Toward a Theory of Situation Awareness in Dynamic Systems. Human Factors: The Journal of the Human Factors and Ergonomics Society, 37(1), 32–64. https://doi.org/10.1518/001872095779049543
Endsley, M. R. (2015). Situation awareness misconceptions and misunderstandings. Journal of Cognitive Engineering and Decision Making, 9(1), 4–32.
Endsley, M. R. (2017). From Here to Autonomy: Lessons Learned from Human-Automation Research. Human Factors, 59(1), 5–27.
Kaber, D. B., & Endsley, M. R. (2004). The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task. In Theoretical Issues in Ergonomics Science (Vol. 5, Issue 2). https://doi.org/10.1080/1463922021000054335.
Pritchett, A. R., Kim, S. Y., & Feigh, K. M. (2014). Modeling human-automation function allocation. Journal of Cognitive Engineering and Decision Making, 8(1), 33–51. https://doi.org/10.1177/1555343413490944
Rajabiyazdi, F., & Jamieson, G. A. (2020). A Review of Transparency (seeing-into) Models. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 302–308. https://doi.org/10.1109/SMC42975.2020.9282970
Skraaning, G., & Jamieson, G. A. (2021). Human Performance Benefits of The Automation Transparency Design Principle. Human Factors: The Journal of the Human Factors and Ergonomics Society, 63(3), 379–401. https://doi.org/10.1177/0018720819887252
van de Merwe, K., Mallam, S., & Nazir, S. (2022). Agent Transparency, Situation Awareness, Mental Workload, and Operator Performance: A Systematic Literature Review. Human Factors: The Journal of the Human Factors and Ergonomics Society, 001872082210778. https://doi.org/10.1177/00187208221077804

Comments

Comment on this article

[1] Asmayawati, S., & Nixon, J. (2020). Modelling and supporting flight crew decision-making during aircraft engine malfunctions: developing design recommendations from cognitive work analysis. Applied Ergonomics, 82(May 2019), 102953.

[2] Chen, J. Y. C., Lakhmani, S. G., Stowers, K., Selkowitz, A. R., Wright, J. L., & Barnes, M. (2018). Situation awareness-based agent transparency and human-autonomy teaming effectiveness. Theoretical Issues in Ergonomics Science, 19(3), 259–282. https://doi.org/10.1080/1463922X.2017.1315750

[3] Clewley, R., & Nixon, J. (2019). Understanding pilot response to flight safety events using categorisation theory. Theoretical Issues in Ergonomics Science, 20(5). https://doi.org/10.1080/1463922X.2019.1574929

[4] Clewley, R., & Nixon, J. (2020). Penguins, Birds, and Pilot Knowledge: Can an Overlooked Attribute of Human Cognition Explain Our Most Puzzling Aircraft Accidents? Human Factors. https://doi.org/10.1177/0018720820960877

[5] Clewley, R., & Nixon, J. (2021). Now you see it, now you don’t: dynamism amplifies the typicality effect. Cognition, Technology & Work. https://doi.org/10.1007/s10111-021-00686-9

[6] Endsley, M. R. (1995). Toward a Theory of Situation Awareness in Dynamic Systems. Human Factors: The Journal of the Human Factors and Ergonomics Society, 37(1), 32–64. https://doi.org/10.1518/001872095779049543

[7] Endsley, M. R. (2015). Situation awareness misconceptions and misunderstandings. Journal of Cognitive Engineering and Decision Making, 9(1), 4–32.

[8] Endsley, M. R. (2017). From Here to Autonomy: Lessons Learned from Human-Automation Research. Human Factors, 59(1), 5–27.

[9] Kaber, D. B., & Endsley, M. R. (2004). The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task. In Theoretical Issues in Ergonomics Science (Vol. 5, Issue 2). https://doi.org/10.1080/1463922021000054335.

[10] Pritchett, A. R., Kim, S. Y., & Feigh, K. M. (2014). Modeling human-automation function allocation. Journal of Cognitive Engineering and Decision Making, 8(1), 33–51. https://doi.org/10.1177/1555343413490944

[11] Rajabiyazdi, F., & Jamieson, G. A. (2020). A Review of Transparency (seeing-into) Models. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 302–308. https://doi.org/10.1109/SMC42975.2020.9282970

[12] Skraaning, G., & Jamieson, G. A. (2021). Human Performance Benefits of The Automation Transparency Design Principle. Human Factors: The Journal of the Human Factors and Ergonomics Society, 63(3), 379–401. https://doi.org/10.1177/0018720819887252

[13] van de Merwe, K., Mallam, S., & Nazir, S. (2022). Agent Transparency, Situation Awareness, Mental Workload, and Operator Performance: A Systematic Literature Review. Human Factors: The Journal of the Human Factors and Ergonomics Society, 001872082210778. https://doi.org/10.1177/00187208221077804

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