Enhancing safety and workload management in eVTOL cockpits through the assessment of pilot’s perception of HMI models

DOI: https://doi.org/10.3846/aviation.2026.26073

Abstract

The rapid emergence of electric vertical take-off and landing (eVTOL) aircraft is expected to revolutionize Urban Air Mobility (UAM) as eVTOL enabling low-emission, point-to-point aerial transportation. The viability of these aircraft is deeply tied to the concept of Single-Pilot Operations, which places intense cognitive, operational, and decision-making loads on the pilot, particularly in dense urban environments. In this context, the Human–Machine Interface (HMI) plays a critical role as it acts as pilot’s “crew member”, effectively functioning and supporting the pilot and increasing situational awareness, workload management, and safe decision-making. This study is a combined method of research design that was implemented, combining a structured online survey and interviews among aviation professionals, including pilots, engineers and human factors specialists to understand and detect their perceptions of HMI requirements for single-pilot eVTOL operations, focusing on workload management, situational awareness, automation interaction, and trust in advanced cockpit technologies. Moreover, open-source flight simulator FlightGear was used to partially depict the results. The findings revealed that maintaining situational awareness without a co-pilot is the dominant challenge, with strong preferences for “eyes-out” displays like physical controls and Head-Up Displays in high-workload scenarios. A significant connection was found between professional expertise and trust in AI copilots. Quantitative data from the survey were analyzed using descriptive and inferential statistics (e.g., t-tests, ANOVA, correlation, regression), supported by graphical representations. The findings show the crucial importance of pilot-focused HMIs for the most important determining factors namely, the problem of maintaining Situation Awareness, multi-tasking and managing cognitive load, the pilot’s central problem without the assistance or presence of the co-pilot in the aircraft. This paper presents the Adaptive, Multimodal, Context-Aware (AMCA) HMI design framework that will benefit the future design of single-pilot eVTOL aircraft cockpits. The study provides concrete design inputs for manufacturers and regulatory and training bodies regarding the challenge of certification and operation of the newly developing Urban Air Mobility solutions.

Keywords:

eVTOL, Urban Air Mobility, Human–Machine Interface, situational awareness, cognitive workload, single-pilot operations

How to Cite

Alomar, I., & Shafqat, A. (2026). Enhancing safety and workload management in eVTOL cockpits through the assessment of pilot’s perception of HMI models. Aviation, 30(1), 49–61. https://doi.org/10.3846/aviation.2026.26073

Share

Published in Issue
March 13, 2026
Abstract Views
30

References

Airbus. (2024). CityAirbus NextGen: The future of urban air mobility. Airbus UAM.

Ahmed, S. S., Hulme, K. F., Fountas, G., Eker, U., Benedyk, I. V., Still, S. E., & Anastasopoulos, P. Ch. (2020). The flying car – Challenges and strategies toward future adoption. Frontiers in Built Environment, 6. https://doi.org/10.3389/fbuil.2020.00106

Arthur, J. J., Bailey, R. E., Williams, S. P., Prinzel, L. J., Shelton, K. J., Jones, D. R., & Houston, V. E. (2017). Review of head-worn displays for the next generation air transportation system. Optical Engineering, 56(5), Article 051405. https://doi.org/10.1117/1.OE.56.5.051405

Cummings, M. L., Stimpson, A. J., & Clamann, M. P. (2020). Workload, situation awareness, and trust in human-robot interactions for single-pilot operations. Journal of Cognitive Engineering and Decision Making, 14(1), 45–65.

Carmody, K., Chauhan, D. B., Namukasa, M., Adorno, Y., & Carroll, M. (2024). Novel human factors challenges, unexpected events, and safety hazards associated with operation of battery-powered eVTOL aircraft. In Proceedings of the AIAA AVIATION 2024 Forum (pp. 1–13). Florida Institute of Technology.

Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). Sage Publications.

European Union Aviation Safety Agency. (2023). Special condition for small-category VTOL aircraft (SC-VTOL). EASA.

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., & Garland, D. J. (2000). Situation awareness analysis and measurement. CRC Press. https://doi.org/10.1201/b12461

Fadden, S., Ververs, P. M., & Wickens, C. D. (1998). Costs and benefits of head-up display use: A meta-analytic approach. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 42(1), 16–20. https://doi.org/10.1177/154193129804200105

Frost & Sullivan. (2023). Global urban air mobility market outlook 2023–2050. Frost & Sullivan.

Garrow, L. A., German, B. J., & Leonard, C. E. (2021). Urban air mobility: A comprehensive review and comparative analysis with autonomous and electric ground transportation for informing future research. Transportation Research Part C: Emerging Technologies, 132, Article 103377. https://doi.org/10.1016/j.trc.2021.103377

Green, R. G. (2017). Human factors for pilots (2nd ed.). Routledge. https://doi.org/10.4324/9781351217545

Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human mental workload (pp. 139–183). North-Holland. https://doi.org/10.1016/S0166-4115(08)62386-9

Hart, S. G., & Wickens, C. D. (1990). Workload assessment and prediction. In H. R. Booher (Ed.), Manprint: An approach to systems integration (pp. 257–296). Springer. https://doi.org/10.1007/978-94-009-0437-8_9

Hu, L., Yan, X., & Yuan, Y. (2024). Development and challenges of autonomous electric vertical take-off and landing aircraft. Heliyon, 11(1), Article e41055. https://doi.org/10.1016/j.heliyon.2024.e41055

Janetzko, D., & Kacem, B. (2024). What do you need? Information requirements and task analysis of (future) advanced air mobility pilots in the emergency medical service. Aerospace, 11(3), Article 197. https://doi.org/10.3390/aerospace11030197

Johnson, W., & Silva, C. (2022). NASA concept vehicles and the engineering of advanced air mobility aircraft. The Aeronautical Journal, 126(1295), 59–91. https://doi.org/10.1017/aer.2021.92

Joby Aviation. (2023). Joby’s pilot interface: Designing for single-pilot eVTOL operations. Joby Aviation.

Kim, Y. W., & Ji, Y. G. (2024). Designing for trust: How human-machine interface can shape the future of urban air mobility. International Journal of Human–Computer Interaction, 41(2), 1190–1203. https://doi.org/10.1080/10447318.2024.2313289

Klaproth, O. W., Halbrügge, M., Krol, L. R., Vernaleken, C., Zander, T. O., & Russwinkel, N. (2020). Tracing pilots’ situation assessment by neuroadaptive cognitive modeling. Frontiers in Neuroscience, 14. https://doi.org/10.3389/fnins.2020.00795

Li, W., Zhang, J., Wang, Y., & Chen, Z. (2023). Cognitive workload assessment in single-pilot operations: A comparative study of traditional and advanced HMI systems. International Journal of Aerospace Psychology, 33(2), 134–152.

Li, Q., Zhang, J., Wang, Y., & Chen, Z. (2024). Single-pilot operations in commercial flight: Effects on neural activity and visual behaviour under abnormalities and emergencies. Chinese Journal of Aeronautics, 37(8), 277–292. https://doi.org/10.1016/j.cja.2024.04.007

Li, S., & Zhang, Z. (2025). Research on human-machine interface for enhancing pilot situational awareness in urban air mobility with eye-tracking technology. In D. D. Schmorrow & C. M. Fidopiastis (Eds.), Augmented cognition (pp. 32–43). Springer. https://doi.org/10.1007/978-3-031-93724-8_3

Mobility Engineering. (2024). Head-worn displays for urban air mobility: A technology review. Mobility Engineering, 12(3), 28–35.

Namukasa, M., Tennett, G. K., & Haskins, C. L. (2024). Evaluating the influence of eVTOL pilot interface visual density and information density on pilot situation awareness, workload, and search performance. Journal of Cognitive Engineering and Decision Making.

OpenAI. (2026). GPT 5.3 [Large language model]. https://chatgpt.com/

Ovezmyradov, B., Jumayev, A., Utanov, B., & Gromova, E. (2025). Statistical analysis of responses to Likert scale questions in management science: Simulation model using utility function and beta distribution (Working paper). Valar Institute.

Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000). A model for types and levels of human interaction with automation. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, 30(3), 286–297. https://doi.org/10.1109/3468.844354

Parasuraman, R. (2011). Neuroergonomics: Brain, cognition, and performance at work. Current Directions in Psychological Science, 20(3), 181–186. https://doi.org/10.1177/0963721411409176

Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors: The Journal of the Human Factors and Ergonomics Society, 39(2), 230–253. https://doi.org/10.1518/001872097778543886

Rasmussen, J. (1983). Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. IEEE Transactions on Systems, Man, and Cybernetics, SMC-13(3), 257–266. https://doi.org/10.1109/TSMC.1983.6313160

Sanderson, P., & Burns, C. (2017). Rasmussen and the boundaries of empirical evaluation. Applied Ergonomics, 59, 649–656. https://doi.org/10.1016/j.apergo.2016.10.003

Sullivan, G., & Artino, A. R. Jr. (2013). Analyzing and interpreting data from Likert-type scales. Journal of Graduate Medical Education, 5(4), 541–542. https://doi.org/10.4300/JGME-5-4-18

Thipphavong, D. P., Apaza, R., Barmore, B., Battiste, V., Belcastro, Ch. M., Burian, B., Dao, Q., Feary, M., Go, S., Goodrich, K. H., Homola, J., Idris, H. R., Kopardekar, P. H., Lachter, J. B., Neogi, N. A., Ng, H. K., Oseguera-Lohr, R. M., Patterson, M. D., & Verma, S. A. (2018). Urban air mobility airspace integration concepts and considerations. In 2018 Aviation Technology, Integration, and Operations Conference. AIAA. https://doi.org/10.2514/6.2018-3676

Vo, D.-B., Pauchet, S., Jolly, I., Simon, F., Brock, A. M., & Garcia, J. (2023). Tactilient: Turbulence resilient tactile icons for pilot feedback. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ‘23) (pp. 1–13). Association for Computing Machinery. https://doi.org/10.1145/3544548.3580951

Vu, K.-P. L., Lachter, J., Battiste, V., & Strybel, T. Z. (2018). Single pilot operations in domestic commercial aviation. Human Factors, 60(6), 755–762. https://doi.org/10.1177/0018720818791372

View article in other formats

CrossMark check

CrossMark logo

Published

2026-03-13

Issue

Section

Articles

How to Cite

Alomar, I., & Shafqat, A. (2026). Enhancing safety and workload management in eVTOL cockpits through the assessment of pilot’s perception of HMI models. Aviation, 30(1), 49–61. https://doi.org/10.3846/aviation.2026.26073

Share