Are Human Drivers a Liability or an Asset?

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Intelligent Systems and Applications (IntelliSys 2021)

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Abstract

This paper investigates the relationship between near misses and human error that leads to a collision. A Smart wheelchair that can detect obstacles is used as an example. Many collisions are the fault of the driver and could be avoided if a sensor system was allowed more control of the vehicle. Some claim that eliminating a human driver from a control loop could eliminate collisions caused by human error. Others caution that human error may not disappear completely with the elimination of the driver and that new incidents may occur because of it. Analysis suggests that a human driver is attributable to many errors but that at the same time a human is vital for avoiding many accidents. The volume of near misses in this analysis is of a sufficient quantity to make some generalized conclusions about the nature of the detection and mitigation of collisions. It would strengthen the analysis if near misses from other types of driving were available. Near misses are a source of information about potential collisions as if a person is having more near misses then they may be becoming tired or distracted. Near misses were analyzed in order to examine what role on-board human drivers play in the occurrence and detection of the initial stages of a collision.

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References

  1. Eriksen, S.: On-board human operators: liabilities or assets? In: 19th Conference on Computer and IT Applications in the Maritime Industries, pp. 98–110 (2020)

    Google Scholar 

  2. Rødseth, Ø.J., Burmeister, H.-C.: Developments toward the unmanned ship. In: DGON ISIS 2012, Berlin (2012)

    Google Scholar 

  3. Sanders, D.A., Langner, M., Tewkesbury, G.E.: Improving wheelchair-driving using a sensor system to control wheelchair-veer and variable-switches as an alternative to digital-switches or joysticks. Ind. Robot Int. J. 32(2), 157–167 (2010)

    Article  Google Scholar 

  4. Sanders, D.A.: Using self-reliance factors to decide how to share control between human powered wheelchair drivers and ultrasonic sensors. IEEE Trans. Neural Syst. Rehabil. Eng. 25(8), 1221–1229 (2016)

    Article  Google Scholar 

  5. Allianz: Safety and Ship** Review 2017, Allianz COLINS, D. (2018), What is the Heinrich Pyramid in Safety Management? (2017). https://www.prosapien.com/blog/heinrich-pyramid

  6. Ahvenjärvi, S.: The human element and autonomous ships, TransNav. Int. J. Marine Navig. Safety Sea Transp. 10, 517–521 (2016)

    Google Scholar 

  7. Wróbel, K., Montewka, J., Kujala, P.: Towards the assessment of potential impact of unmanned vessels on maritime transportation safety. Reliab. Eng. Syst. Safety 165, 155–169 (2017)

    Article  Google Scholar 

  8. Heinrich, H.W., Petersen, D., Roos, N.: Industrial Accident Prevension: A Safety Management Approach, New York (1980)

    Google Scholar 

  9. Salminen, S., Saari, J., saarela, K.L., Räsänen, T.: Fatal and non-fatal occupational accidents: identical versus differential causation. Safety Sci. 15, 109–118 (1992)

    Google Scholar 

  10. Hale, A.: Conditions of occurrence of major and minor accidents: urban myths, deviations and accident scenarios, Tijdschrift Voor Toegepaste Arbowetenschap 15 (2002)

    Google Scholar 

  11. Perrow, C.: Normal Accidents: Living with High-Risk Technologies. Princeton University Press, Princeton (1999)

    Google Scholar 

  12. Heinrich’s accident pyramid. https://www.pro-sapien.com/blog/heinrich-pyramid

  13. Jones, S., Kirchsteiger, C., Bjerke, W.: The importance of near miss reporting to further improve safety performance. J. Loss Prev. Process Ind. 12, 59–67 (1999)

    Article  Google Scholar 

  14. Markowski, A.S., Mannan, M.S., Bigoszewska, A.: Fuzzy logic for process safety analysis. J. Loss Prev. Process Ind. 22, 695–702 (2009)

    Article  Google Scholar 

  15. https://www.cgerisk.com/knowledgebase/File:Bowtie_Diagram.png. Downloaded Jan 2021

  16. De Ruijter, A., Guldenmund, F.: The Bowtie method: a review. Safety Sci. 88, 211–218 EMSA (2014). Annual Overview of Marine Casualties and Incidents 2014, European Maritime Safety Agency, Lisboa (2016)

    Google Scholar 

  17. Sanders, D.A., Bausch, N.: Improving steering of a powered wheelchair using an expert system to interpret hand tremor. In: Liu, H., Kubota, N., Zhu, X., Dillmann, R., Zhou, D. (eds.) ICIRA 2015. LNCS (LNAI), vol. 9245, pp. 460–471. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22876-1_39

    Chapter  Google Scholar 

  18. Sanders, D.A., Gegov, A., Haddad, M., Ikwan, F., Wiltshire, D., Tan, Y.C.: x. Rule-based Expert System to decide on direction and speed of a powered wheelchair; Sanders, D.A.: Using self-reliance factors to decide how to share control between human powered wheelchair drivers and ultrasonic sensors. IEEE Trans. Neural Syst. Rehabil. Eng. 25(8), 1221–1229 (2016)

    Google Scholar 

  19. Sanders, D.A., Gegov, A., Haddad, M., Ikwan, F., Wiltshire, D., Tan, Y.C.: A rule-based expert system to decide on direction and speed of a powered wheelchair. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) IntelliSys 2018. AISC, vol. 868, pp. 822–832. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-01054-6_57

  20. Sanders, D.A., Haddad, M., Tewkesbury, G.E., Thabet, M., Omoarebun, P., Barker, T.: Simple expert system for intelligent control and HCI for a wheelchair fitted with ultrasonic sensors. In: 2020 IEEE 10th International Conference on Intelligent Systems (IS), pp. 211–216. IEEE, August 2020. pp. 822–832

    Google Scholar 

  21. Sanders, D.A., Haddad, M., Tewkesbury, G.E., Thabet, M., Omoarebun, P., Barker, T.: Simple expert system for intelligent control and HCI for a wheelchair fitted with ultrasonic sensors. In: 2020 IEEE 10th International Conference on Intelligent Systems (IS), pp. 211–216. IEEE (2020)

    Google Scholar 

  22. New Control Paper

    Google Scholar 

  23. Haddad, M., et al.: Use of the analytical hierarchy process to determine the steering direction for a powered wheelchair. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) IntelliSys. AISC, vol. 1252, pp. 617–630. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-55190-2_46

    Chapter  Google Scholar 

  24. Haddad, M.J., Sanders, D.A.: Selecting a best compromise direction for a powered wheelchair using PROMETHEE. IEEE Trans. Neural Syst. Rehabil. Eng. 27(2), 228–235 (2019)

    Article  Google Scholar 

  25. Sanders, D.A., Gegov, A., Haddad, M., Ikwan, F., Wiltshire, D., Tan, Y.C.: A rule-based expert system to decide on direction and speed of a powered wheelchair. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) IntelliSys. AISC, vol. 868, pp. 822–838. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-01054-6_57

    Chapter  Google Scholar 

  26. Haddad, M., et al.: Intelligent control of the steering for a powered wheelchair using a microcomputer. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) IntelliSys. AISC, vol. 1252, pp. 594–603. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-55190-2_44

    Chapter  Google Scholar 

  27. Haddad, M., Sanders, D., Ikwan, F., Thabet, M., Langner, M., Gegov, A.: Intelligent HMI and control for steering a powered wheelchair using a Raspberry Pi microcomputer. In: 2020 IEEE 10th International Conference on Intelligent Systems (IS), pp. 223–228. IEEE, Bulgaria (2020)

    Google Scholar 

  28. Haddad, M., et al.: Intelligent system to analyze data about powered wheelchair drivers. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) IntelliSys. AISC, vol. 1252, pp. 584–593. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-55190-2_43

    Chapter  Google Scholar 

  29. Haddad, M., Sanders, D., Langner, M., Omoarebun, P., Thabet, M., Gegov, A.: Initial results from using an intelligent system to analyse powered wheelchair users’ data. In: 2020 IEEE 10th International Conference on Intelligent Systems (IS), pp. 241–245. IEEE, Bulgaria (2020)

    Google Scholar 

  30. Sanders, D., Haddad, M., Tewkesbury, G., Bausch, N., Rogers, I. and Huang, Y.: Analysis of reaction times and time-delays introduced into an intelligent HCI for a smart wheelchair. In: 2020 IEEE 10th International Conference on Intelligent Systems (IS), pp. 217–222. IEEE, Bulgaria (2020)

    Google Scholar 

  31. Sanders, D., et al.: Introducing time-delays to analyze driver reaction times when using a powered wheelchair. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) IntelliSys. AISC, vol. 1252, pp. 559–570. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-55190-2_41

    Chapter  Google Scholar 

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Acknowledgment

This research was supported by the Engineering and Physical Sciences Research Council (EPSRC).

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Correspondence to David Sanders .

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Sanders, D., Haddad, M., Tewkesbury, G., Gegov, A., Adda, M. (2022). Are Human Drivers a Liability or an Asset?. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-82193-7_54

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