User Centered Ecological Interface Design (UCEID): A Novel Method Applied to the Problem of Safe and User-Friendly Interaction Between Drivers and Autonomous Vehicles

  • Kirsten Revell
  • Pat Langdon
  • Mike Bradley
  • Ioannis Politis
  • James Brown
  • Neville Stanton
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 722)

Abstract

User Centered Ecological Interface Design (UCEID) is a novel Human Factors method that integrates relationships between Ecological Interface Design (EID) and inclusive Human Centered Design. It combines existing methodology from the Cognitive Work Analysis (CWA) framework [1, 2, 3] and Inclusive User Centered Design [4, 5]. This paper offers a practical guide to UCEID by providing a high-level summary for practitioners using the example of vehicle to driver handover in a BASt Level 3 autonomous vehicle.

Keywords

Human Factors methods Human-systems integration Autonomous vehicles User Centered Design Cognitive Work Analysis EID Inclusive design 

Notes

Acknowledgments

This work was supported by Jaguar Land Rover and the UK-EPSRC grant EP/011899/1 as part of the jointly funded Towards Autonomy: Smart and Connected Control (TASCC) Programme.

References

  1. 1.
    Rasmussen, J., Pejtersen, A., Goodstein, L.P.: Cognitive Systems Engineering. Wiley, New York (1994)Google Scholar
  2. 2.
    Vicente, K.J.: Cognitive Work Analysis: Toward Safe, Productive, and Healthy Computer-Based Work. Lawrence Erlbaum Associates, Mahwah (1999)Google Scholar
  3. 3.
    Jenkins, D.P., Stanton, N.A., Salmon, P.A., Walker, G.H.: Cognitive Work Analysis: Coping with Complexity. Ashgate Publishing Ltd., Farnham (2009)Google Scholar
  4. 4.
    Czajkowski, K., Fitzgerald, S., Foster, I., Kesselman, C.: Grid information services for distributed resource sharing. In: 10th IEEE International Symposium on High Performance Distributed Computing, pp. 181–184. IEEE Press, New York (2001)Google Scholar
  5. 5.
    Langdon, P., Thimbleby, H.: Inclusion and interaction: designing interaction for inclusive populations. Editor. Spec. Ed. Interact. Comput. 22, 439–448 (2010)CrossRefGoogle Scholar
  6. 6.
    Stanton, N.A., Salmon, P.M., Rafferty, L.A., Walker, G.H., Baber, C., Jenkins, D.P.: Human Factors Methods: A Practical Guide for Engineering and Design. Ashgate Publishing Ltd., Aldershot (2013)CrossRefGoogle Scholar
  7. 7.
    Green, W.S., Jordan, P.W.: Human Factors in Product Design: Current Practice and Future Trends. Taylor & Francis, London (1999)Google Scholar
  8. 8.
    Langdon, P.M., Lazar, J., Heylighen, A., Dong, H. (eds.): Inclusive Designing: Joining Usability, Accessibility, and Inclusion. Springer, Heidelberg (2014)Google Scholar
  9. 9.
    McIlroy, R.C., Stanton, N.A.: Ecological interface design two decades on: whatever happened to the SRK taxonomy? IEEE Trans. Hum-Mach. Syst. 45(2), 145–163 (2015)CrossRefGoogle Scholar
  10. 10.
    Handover/Takeover of Operational ATC Working Positions/Responses. https://www.skybrary.aero/index.php/Handover/Takeover_of_Operational_ATC_Working_Positions/Responses
  11. 11.
    Roadcraft: the police driver and rider handbooks for better, safer driving. http://www.roadcraft.co.uk
  12. 12.
  13. 13.
    Glaser, B.G., Strauss, A.L.: The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine, Chicago (1967)Google Scholar
  14. 14.
    Breakwell, G.M.: Introducing Research Methods in Psychology. Research Methods in Psychology. Sage, London (2000)Google Scholar
  15. 15.
    Ewe, F.: An Introduction to Qualitative Research, 3rd edn. Sage, London (2006)Google Scholar
  16. 16.
    Naikar, N., Moylan, A., Pearce, B.: Analysing activity in complex systems with cognitive work analysis: concepts, guidelines, and case study for control task analysis. Theor. Issues Ergon. Sci. 7(4), 371–394 (2006)CrossRefGoogle Scholar
  17. 17.
    Naikar, N.: An examination of the key concepts of the five phases of cognitive work analysis with examples from a familiar system. In: Proceedings of the Human Factors and Ergnomics Society 50th Annual Meeting, pp. 447–451 (2006)Google Scholar
  18. 18.
    Rasmussen, J.: The role of hierarchical knowledge representation in decision making and system management. IEEE Trans. Syst. Man Cybern. 15, 234–243 (1985)CrossRefGoogle Scholar
  19. 19.
    Pugh, S.: Total Design: Integrated Methods for Successful Product Engineering. Addison, Wokingham (1993)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Kirsten Revell
    • 1
  • Pat Langdon
    • 2
  • Mike Bradley
    • 2
  • Ioannis Politis
    • 2
  • James Brown
    • 1
  • Neville Stanton
    • 1
  1. 1.Human Factors Engineering, Transportation Research GroupUniversity of SouthamptonSouthamptonUK
  2. 2.Department of Engineering, Engineering Design CentreUniversity of CambridgeCambridgeUK

Personalised recommendations