1887
Volume 24, Issue 3
  • ISSN 1572-0373
  • E-ISSN: 1572-0381
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Abstract

Abstract

Small unmanned aerial systems (sUAS) are used more regularly and widely in disaster response. Like other personnel involved in disaster response, the sUAS pilots work for long periods, experience extreme stress and fatigue. They often arrive at the disaster fatigued (due to long drives to get there). However, unlike other personnel in this domain, there is little research on the effects of fatigue on sUAS pilots. Our experiences with a series of three real-world deployments highlight the challenges of conducting human factors research during disaster response and recovery. We specifically present lessons learned from having participant researchers embedded in three disasters with the sUAS pilot teams. These lessons result in a set of feasible and non-interruptive methods and metrics for conducting human factors research during field events. Preliminary results and recommended next steps are presented.

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2024-02-15
2024-12-08
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References

  1. Adams, J., Hart, L., McBride, J., Merrick, D., & Murphy, R.
    (2018) Use of small unmanned aerial Systems for Tactical Response during Kilauea volcano lower east rift zone event. 2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). 10.1109/SSRR.2018.8468626
    https://doi.org/10.1109/SSRR.2018.8468626 [Google Scholar]
  2. Åkerstedt, T., & Gillberg, M.
    (1990) Subjective and objective sleepiness in the active individual. International journal of neuroscience, 52(1–2), 29–37. 10.3109/00207459008994241
    https://doi.org/10.3109/00207459008994241 [Google Scholar]
  3. Alexander, D. A., & Klein, S.
    (2009) First responders after disasters: a review of stress reactions, at-risk, vulnerability, and resilience factors. Prehospital and Disaster Medicine, 24(2), 87–94. 10.1017/S1049023X00006610
    https://doi.org/10.1017/S1049023X00006610 [Google Scholar]
  4. Arsintescu, L., Kato, K. H., Cravalho, P. F., Feick, N. H., Stone, L. S., & Flynn-Evans, E. E.
    (2019) Validation of a touchscreen psychomotor vigilance task. Accident Analysis & Prevention, 1261, 173–176. 10.1016/j.aap.2017.11.041
    https://doi.org/10.1016/j.aap.2017.11.041 [Google Scholar]
  5. Basner, M., & Rubinstein, J.
    (2011) Fitness for duty: A 3 minute version of the Psychomotor Vigilance Test predicts fatigue related declines in luggage screening performance. Journal of occupational and environmental medicine/American College of Occupational and Environmental Medicine, 53(10). 10.1097/JOM.0b013e31822b8356
    https://doi.org/10.1097/JOM.0b013e31822b8356 [Google Scholar]
  6. Basner, M., Mollicone, D., & Dinges, D. F.
    (2011) Validity and sensitivity of a brief psychomotor vigilance test (PVT-B) to total and partial sleep deprivation. Acta astronautica, 691, 11–12. 10.1016/j.actaastro.2011.07.015
    https://doi.org/10.1016/j.actaastro.2011.07.015 [Google Scholar]
  7. Benedek, D. M., Fullerton, C., & Ursano, R. J.
    (2007) First responders: mental health consequences of natural and human-made disasters for public health and public safety workers. Annu. Rev. Public Health, 281, 55–68. 10.1146/annurev.publhealth.28.021406.144037
    https://doi.org/10.1146/annurev.publhealth.28.021406.144037 [Google Scholar]
  8. Burke, J., & Murphy, R.
    (2004) Human-robot interaction in USAR technical search: Two heads are better than one. RO-MAN 2004. 13th IEEE International Workshop on Robot and Human Interactive Communication (IEEE Catalog No. 04TH8759).
    [Google Scholar]
  9. Burke, J. L., Murphy, R. R., Coovert, M. D., & Riddle, D. L.
    (2004) Moonlight in Miami: Field study of human-robot interaction in the context of an urban search and rescue disaster response training exercise. Human–Computer Interaction, 19(1–2), 85–116. 10.1207/s15327051hci1901&2_5
    https://doi.org/10.1207/s15327051hci1901&2_5 [Google Scholar]
  10. Burke, J. L., Murphy, R. R., Riddle, D. R., & Fincannon, T.
    (2004) Task performance metrics in human-robot interaction: Taking a systems approach.
    [Google Scholar]
  11. Casper, J., & Murphy, R. R.
    (2003) Human-robot interactions during the robot-assisted urban search and rescue response at the world trade center. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 33(3), 367–385. 10.1109/TSMCB.2003.811794
    https://doi.org/10.1109/TSMCB.2003.811794 [Google Scholar]
  12. Casper, J. L., & Murphy, R. R.
    (2002) Workflow study on human-robot interaction in USAR. Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No. 02CH37292). 10.1109/ROBOT.2002.1014834
    https://doi.org/10.1109/ROBOT.2002.1014834 [Google Scholar]
  13. Fernandes, O., Murphy, R., Adams, J., & Merrick, D.
    (2018) Quantitative Data Analysis: CRASAR Small Unmanned Aerial Systems at Hurricane Harvey. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 1–6. 10.1109/SSRR.2018.8468647
    https://doi.org/10.1109/SSRR.2018.8468647 [Google Scholar]
  14. Fernandes, O., Murphy, R. R., Merrick, D., Adams, J., Hart, L., & Broder, J.
    (2019) Quantitative Data Analysis: Small Unmanned Aerial Systems at Hurricane Michael. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 116–117. 10.1109/SSRR.2019.8848935
    https://doi.org/10.1109/SSRR.2019.8848935 [Google Scholar]
  15. Harris, A.
    (2018) Eruption crisis at Kilauea Caldera (Big Island of Hawaii, USA). Bulletin of Volcanology, 80(8), 66. 10.1007/s00445‑018‑1240‑2
    https://doi.org/10.1007/s00445-018-1240-2 [Google Scholar]
  16. Hart, S. G., & Staveland, L. E.
    (1988) Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. InAdvances in Psychology (Vol.521, pp.139–183). Elsevier.
    [Google Scholar]
  17. Hopko, S., Wang, J., & Mehta, R.
    (2022) Human Factors Considerations and Metrics in Shared Space Human-Robot Collaboration: A Systematic Review. Frontiers in Robotics and AI, 91. 10.3389/frobt.2022.799522
    https://doi.org/10.3389/frobt.2022.799522 [Google Scholar]
  18. Hopko, S. K., Khurana, R., Mehta, R. K., & Pagilla, P. R.
    (2021) Effect of Cognitive Fatigue, Operator Sex, and Robot Assistance on Task Performance Metrics, Workload, and Situation Awareness in Human-Robot Collaboration. IEEE Robotics and Automation Letters, 6(2), 3049–3056. 10.1109/LRA.2021.3062787
    https://doi.org/10.1109/LRA.2021.3062787 [Google Scholar]
  19. Kaplan, S., Karklis, L., & Tierney, L.
    (2018, May17 2018) Where the Earth is erupting on Hawaii’s Big Island. The Washington Post.
    [Google Scholar]
  20. Karthikeyan, R., McDonald, A., & Mehta, R. K.
    (2023) Stress Detection During Motor Activity: A Comparison of Neural and Physiological Biomarkers in Older Adults. IEEE Transactions on Affective Computing. 14(3), 2224–2237. 10.1109/TAFFC.2022.3148234
    https://doi.org/10.1109/TAFFC.2022.3148234 [Google Scholar]
  21. Korshøj, M., Krustrup, P., Jørgensen, M. B., Prescott, E., Hansen, Å. M., Kristiansen, J., Skotte, J. H., Mortensen, O. S., Søgaard, K., & Holtermann, A.
    (2012) Cardiorespiratory fitness, cardiovascular workload and risk factors among cleaners; a cluster randomized worksite intervention. BMC Public Health, 12(1), 1–9. 10.1186/1471‑2458‑12‑645
    https://doi.org/10.1186/1471-2458-12-645 [Google Scholar]
  22. Mehta, R. K., & Agnew, M. J.
    (2012) Influence of mental workload on muscle endurance, fatigue, and recovery during intermittent static work. European journal of applied physiology, 112(8), 2891–2902. 10.1007/s00421‑011‑2264‑x
    https://doi.org/10.1007/s00421-011-2264-x [Google Scholar]
  23. Mehta, R. K., Nuamah, J., Peres, S. C., & Murphy, R. R.
    (2020) Field methods to quantify emergency responder fatigue: lessons learned from sUAS deployment at the 2018 Kilauea Volcano eruption. IISE transactions on occupational ergonomics and human factors, 8(3), 166–174. 10.1080/24725838.2020.1855272
    https://doi.org/10.1080/24725838.2020.1855272 [Google Scholar]
  24. Mehta, R. K., Peres, S. C., Kannan, P., Rhee, J., Shortz, A. E., & Mannan, M. S.
    (2017) Comparison of objective and subjective operator fatigue assessment methods in offshore shiftwork. Journal of loss prevention in the process industries, 481, 376–381. 10.1016/j.jlp.2017.02.009
    https://doi.org/10.1016/j.jlp.2017.02.009 [Google Scholar]
  25. Mueller, S. T., & Piper, B. J.
    (2014) The psychology experiment building language (PEBL) and PEBL test battery. Journal of neuroscience methods, 2221, 250–259. 10.1016/j.jneumeth.2013.10.024
    https://doi.org/10.1016/j.jneumeth.2013.10.024 [Google Scholar]
  26. Murphy, R. R.
    (2004a) Human-robot interaction in rescue robotics. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 34(2), 138–153. 10.1109/TSMCC.2004.826267
    https://doi.org/10.1109/TSMCC.2004.826267 [Google Scholar]
  27. (2004b) Trial by fire [rescue robots]. IEEE Robotics & Automation Magazine, 11(3), 50–61. 10.1109/MRA.2004.1337826
    https://doi.org/10.1109/MRA.2004.1337826 [Google Scholar]
  28. (2012) A decade of rescue robots. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. 10.1109/IROS.2012.6386301
    https://doi.org/10.1109/IROS.2012.6386301 [Google Scholar]
  29. (2014) Disaster robotics. MIT press. 10.7551/mitpress/9407.001.0001
    https://doi.org/10.7551/mitpress/9407.001.0001 [Google Scholar]
  30. (2019) Humans and robots in off-normal applications and emergencies. International Conference on Applied Human Factors and Ergonomics.
    [Google Scholar]
  31. Murphy, R. R., & Burke, J. L.
    (2005) Up from the rubble: Lessons learned about HRI from search and rescue. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 10.1177/154193120504900347
    https://doi.org/10.1177/154193120504900347 [Google Scholar]
  32. (2008) From remote tool to shared roles. IEEE Robotics & Automation Magazine, 15(4), 39–49. 10.1109/MRA.2008.929928
    https://doi.org/10.1109/MRA.2008.929928 [Google Scholar]
  33. Orr, T., Heliker, C., & Patrick, M.
    (2012) The ongoing Puʻu ʻŌʻō eruption of Kīlauea Volcano, Hawaiʻi – 30 years of eruptive activity. US Geol. Surv. Fact Sheet, 3127(6).
    [Google Scholar]
  34. Peschel, J. M., & Murphy, R. R.
    (2012) On the human–machine interaction of unmanned aerial system mission specialists. IEEE Transactions on Human-Machine Systems, 43(1), 53–62. 10.1109/TSMCC.2012.2220133
    https://doi.org/10.1109/TSMCC.2012.2220133 [Google Scholar]
  35. Pontifex, M. B., McGowan, A. L., Chandler, M. C., Gwizdala, K. L., Parks, A. C., Fenn, K., & Kamijo, K.
    (2019) A primer on investigating the after effects of acute bouts of physical activity on cognition. Psychology of Sport and Exercise, 401, 1–22. 10.1016/j.psychsport.2018.08.015
    https://doi.org/10.1016/j.psychsport.2018.08.015 [Google Scholar]
  36. Preisser, A. M., Zhou, L., Garrido, M. V., & Harth, V.
    (2016) Measured by the oxygen uptake in the field, the work of refuse collectors is particularly hard work: Are the limit values for physical endurance workload too low?International Archives of Occupational and Environmental Health, 89(2), 211–220. 10.1007/s00420‑015‑1064‑8
    https://doi.org/10.1007/s00420-015-1064-8 [Google Scholar]
  37. Reid, G. B., & Nygren, T. E.
    (1988) The subjective workload assessment technique: A scaling procedure for measuring mental workload. In Advances in psychology, 521, 185–218. 10.1016/S0166‑4115(08)62387‑0
    https://doi.org/10.1016/S0166-4115(08)62387-0 [Google Scholar]
  38. Sebastian, T., Lendering, K., Kothuis, B., Brand, N., Jonkman, B., van Gelder, P., Godfroij, M., Kolen, B., Comes, T., & Lhermitte, S.
    (2017) Hurricane Harvey Report: A fact-finding effort in the direct aftermath of Hurricane Harvey in the Greater Houston Region.
    [Google Scholar]
  39. Shortz, A. E., Hoyle, W. S., Peres, S. C., & Mehta, R. K.
    (2018) Fatigue indicators of 12-hour day and night shifts in simulated offshore well control scenarios. Proceedings of the Human Factors and Ergonomics Society Annual Meeting.
    [Google Scholar]
  40. Shultz, J. M., & Galea, S.
    (2017) Mitigating the mental and physical health consequences of Hurricane Harvey. Jama, 318(15), 1437–1438. 10.1001/jama.2017.14618
    https://doi.org/10.1001/jama.2017.14618 [Google Scholar]
  41. Sikder, M. S., Ahmad, S., Hossain, F., Gebregiorgis, A. S., & Lee, H.
    (2019) Case study: rapid urban inundation forecasting technique based on quantitative precipitation forecast for Houston and Harris county flood control district. Journal of Hydrologic Engineering, 24(8), 05019017. 10.1061/(ASCE)HE.1943‑5584.0001807
    https://doi.org/10.1061/(ASCE)HE.1943-5584.0001807 [Google Scholar]
  42. Zhu, Y., Jankay, R. R., Pieratt, L. C., & Mehta, R. K.
    (2017) Wearable sensors and their metrics for measuring comprehensive occupational fatigue: A scoping review. Human Factors and Ergonomics Society Annual Meeting, Austin, TX, USA.
    [Google Scholar]
  43. Zomeren, M. V., Peschel, J. M., Mann, T., Knezek, G., Doebbler, J., Davis, J., Hammond, T. A., Oomes, A. H., & Murphy, R. R.
    (2009) Human-robot interaction observations from a proto-study using SUAVs for structural inspection. Proceedings of the 4th ACM/IEEE international conference on Human robot interaction. 10.1145/1514095.1514153
    https://doi.org/10.1145/1514095.1514153 [Google Scholar]
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  • Article Type: Research Article
Keyword(s): field studies; human-robotic interaction; small uncrewed aerial systems
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