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Adaptation of Human Licensing Examinations to the Certification of Autonomous Systems

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Safe, Autonomous and Intelligent Vehicles

Part of the book series: Unmanned System Technologies ((UST))

Abstract

In aviation and surface transportation settings, pilots and drivers are certified to operate vehicles through a licensing process that includes an assessment of physical readiness, a written knowledge exam, and a practical exam, sometimes referred to as a “checkride.” This is a process whereby a human examiner assesses whether humans can effectively operate autonomously either in actual or simulated conditions. Given the rise of autonomous transportation technologies and the debate as to how such technologies that leverage probabilistic reasoning could and should be certified, could such licensing approaches be extended to certification of autonomous systems? This chapter will discuss how machine and human autonomy are similar and different, how and why licensing processes have developed historically across the two transportation domains, and how autonomous transportation systems could adapt the principles of human-based licensing processes for certification.

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References

  1. V. Nneji, A. Stimpson, M.L. Cummings, K. Goodrich, in Exploring Concepts of Operations for on-Demand Passenger Air Transportation. Paper Presented at the AIAA Aviation, Denver, CO (2017)

    Google Scholar 

  2. D. Shinar, F. Schieber, Visual requirements for safety and mobility of older drivers. Hum. Factors 33(5), 507–519 (1991)

    Article  Google Scholar 

  3. American Medical Association, in Physician’s Guide to Assessing and Counseling Older Drivers. Chapter 9: Medical conditions and medications that may impair driving (National Highway Transportation and Safety Administration, Washington, 2003)

    Google Scholar 

  4. American Association of Motor Vehicle Administrators, AAMVA Guidelines for Noncommercial Knowledge and Skills Test Development. Retrieved from Arlington, VA (2014)

    Google Scholar 

  5. Virginia Department of Motor Vehicles, Virginia Driver's Manual. Commonwealth of Virginia (2017)

    Google Scholar 

  6. Flight Standards Service, Commercial Pilot – Airplane Airman Certification Standards. FAA-S-ACS-7 (Changes 1 & 2). (U.S. Department of Transportation, Washington, 2017)

    Google Scholar 

  7. M.L. Cummings, Man vs. Machine or Man + Machine? IEEE Intell. Syst. 29(5), 62–69 (2014)

    Article  Google Scholar 

  8. J. Rasmussen, Skills, rules, and knowledge: Signals, signs, and symbols, and other distinctions in human performance models. IEEE Trans. Syst. Man Cybern. 13(3), 257–266 (1983)

    Article  Google Scholar 

  9. M.L. Cummings, A. Stimpson, M. Clamann, in Functional Requirements for Onboard Intelligent Automation in Single Pilot Operations. Paper Presented at the AIAA SciTech Conference, San Diego, CA (2016)

    Google Scholar 

  10. National Center for Statistics and Analysis, Traffic Safety Facts: Research Note (Department of Transportation, Washington, 2017)

    Google Scholar 

  11. D.A. Wiegmann, S.A. Shappell, A Human Error Analysis of Commercial Aviation Accidents Using the Human Factors Analysis and Classification System (HFACS) (Federal Aviation Administration, Washington, 2001)

    Book  Google Scholar 

  12. R.J. Jagacinski, J.M. Flach, Control Theory for Humans: Quantitative Approaches to Modeling Performance (Lawrence Erlbaum Associates, New Jersey, 2003)

    Google Scholar 

  13. P.J. Smith, C.E. McCoy, C. Layton, in Brittleness in the Design of Cooperative Problem-Solving Systems: The Effects on User Performance. Paper Presented at the IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans (1997)

    Article  Google Scholar 

  14. NTSB, Highway Accident Report: Collision Between a Car Operating with Automated Vehicle Control Systems and a Tractor-Semitrailer Truck near Williston, Florida May 7, 2016. NTSB/HAR-17/02 PB2017–102600. Washington (2017)

    Google Scholar 

  15. I. Evtimov, K. Eykholt, E. Fernandes, T. Kohno, B. Li, A. Prakash, D. Song, Robust physical-world attacks on deep learning models. arXiv preprint 1707.08945 (2017)

    Google Scholar 

  16. H.A. Simon, Models of Bounded Rationality, vol 2 (MIT Press, Cambridge, 1982)

    Google Scholar 

  17. L. Fraade-Blanar, N. Kalra, Autonomous Vehicles and Federal Safety Standards: An Exemption to the Rule? Retrieved from Santa Monica, CA (2017)

    Google Scholar 

  18. T. Miller, P. Howe, L. Sonenberg, in Explainable AI: Beware of Inmates Running the Asylum. Paper Presented at the IJCAI-17 Workshop on Explainable AI (XAI) Proceedings, Melbourne, Australia (2017)

    Google Scholar 

  19. A. Tversky, D. Kahneman, Judgment under uncertainty: Heuristics and biases. Science 185(4157), 1124–1131 (1974)

    Article  Google Scholar 

  20. S. Erwin, UAV Programs Illustrate DoD’s broken Procurement System. National Defense (2009)

    Google Scholar 

  21. M.L. Cummings, The Brave New World of Driverless Cars: The Need for Interdisciplinary Research and Workforce Development (TR News, 2017), pp. 34–37

    Google Scholar 

  22. D. Douglas, M.A. Fletcher Toyota Reaches $1.2 Billion Settlement to End Probe of Accelerator Problems. Washington Post (2014)

    Google Scholar 

  23. N. Steinkamp, in 2016 Automotive Warranty & Recall Report (2016)

    Google Scholar 

  24. NTSB Auxiliary power unit battery fire Japan Airlines Boeing 787–8, JA829J Boston, Massachusetts January 7, 2013. NTSB/AIR-14/01 PB2014–108867 (National Transportation Safety Board, Washington, 2014)

    Google Scholar 

  25. J. Bredereke, A. Lankenau, in A rigorous view of mode confusion. Paper presented at the SafeComp, Bremen, Germany (2002)

    Google Scholar 

  26. M.L. Cummings, F. Gao, Boredom in the workplace: A new look at an old problem. Hum. Factors 58(2), 279–300 (2016)

    Article  Google Scholar 

  27. T.A. Ranney, Driver Distraction: A Review of the Current State-of-Knowledge (Department of Transportation, Washington, 2008)

    Google Scholar 

  28. H. Petroski, To Engineer is Human (Vintage Books, New York, 1992)

    Google Scholar 

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Acknowledgements

This work was inspired by Dr. Michael Francis and supported in part by the US Department of Transportation and the University of North Carolina’s Collaborative Sciences Center for Road Safety (CSCRS).

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Correspondence to M. L. Cummings .

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Cummings, M.L. (2019). Adaptation of Human Licensing Examinations to the Certification of Autonomous Systems. In: Yu, H., Li, X., Murray, R., Ramesh, S., Tomlin, C. (eds) Safe, Autonomous and Intelligent Vehicles. Unmanned System Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-97301-2_8

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  • DOI: https://doi.org/10.1007/978-3-319-97301-2_8

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  • Online ISBN: 978-3-319-97301-2

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