Advertisement

How Should an Automated Vehicle Communicate Its Intention to a Pedestrian? – A Virtual Reality Study

  • Tanja FuestEmail author
  • Anna Sophia Maier
  • Hanna Bellem
  • Klaus Bengler
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1026)

Abstract

To analyze the influence of right of way and automated vehicle (AV) deceleration maneuvers on pedestrians’ behavior, a virtual reality study was conducted. Participants were asked to press a button when they understood the intention of an approaching AV, and to rate the driving behavior after each trial. Results showed that the AV’s driving behavior was able to communicate an intention. If the AV decelerates for pedestrians, it should decelerate early. When right of way is not defined, the AV should adapt to the expectations of pedestrians (e.g. not drive too fast). At a zebra crossing, participants expect the AV to communicate at an early stage that they are allowed to go first.

Keywords

(Automated) Vehicle-Pedestrian-Interaction Virtual reality Implicit communication Mixed traffic 

References

  1. 1.
    BMW Group: The path to autonomous driving. https://www.bmw.com/en/automotive-life/autonomous-driving.html
  2. 2.
    Fuest, T., Sorokin, L., Bellem, H., Bengler, K.: Taxonomy of traffic situations for the interaction between automated vehicles and human road users. In: Stanton, N.A. (ed.) Advances in Human Aspects of Transportation, vol. 597, pp. 708–719. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-60441-1_68CrossRefGoogle Scholar
  3. 3.
    Fuest, T., Michalowski, L., Traris, L., Bellem, H., Bengler, K.: Using the driving behavior of an automated vehicle to communicate intentions - a wizard of oz study. In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 3596–3601. IEEE (2018).  https://doi.org/10.1109/ITSC.2018.8569486
  4. 4.
    Ackermann, C., Beggiato, M., Bluhm, L.-F., Löw, A., Krems, J.F.: Deceleration parameters and their applicability as informal communication signal between pedestrians and automated vehicles. Transp. Res. Part F Traffic Psychol. Behav. 62, 757–768 (2019).  https://doi.org/10.1016/j.trf.2019.03.006CrossRefGoogle Scholar
  5. 5.
    Schneemann, F., Gohl, I.: Analyzing driver-pedestrian interaction at crosswalks: A contribution to autonomous driving in urban environments. In: 2016 IEEE Intelligent Vehicles Symposium (IV), pp. 38–43. IEEE (2016).  https://doi.org/10.1109/IVS.2016.7535361
  6. 6.
    Neukum, A., Lübbeke, T., Krüger, H.-P., Mayser, C., Steinle, J.: ACC-Stop&Go: Fahrerverhalten an funktionalen Systemgrenzen. In: Maurer, M., Stiller, C. (eds.) 5. Workshop Fahrerassistenzsysteme, pp. 141–150 (2008)Google Scholar
  7. 7.
    AASHTO: A Policy on geometric design of highways and streets. Washington (2011)Google Scholar
  8. 8.
    Bhagavathula, R., Williams, B., Owens, J., Gibbons, R.: The reality of virtual reality: a comparison of pedestrian behavior in real and virtual environments. Proc. Hum. Factors Ergon. Soc. Annu. Meet. 62, 2056–2060 (2018).  https://doi.org/10.1177/1541931218621464CrossRefGoogle Scholar
  9. 9.
    Hurwitz, D., Knodler, M., Dulaski, D.: Speed perception fidelity in a driving simulator environment. In: Conference: Driving Simulator Conference North America, pp. 343–352 (2005)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Tanja Fuest
    • 1
    Email author
  • Anna Sophia Maier
    • 1
  • Hanna Bellem
    • 2
  • Klaus Bengler
    • 1
  1. 1.Chair of ErgonomicsTechnical University of MunichGarchingGermany
  2. 2.BMW GroupNew TechnologiesGarchingGermany

Personalised recommendations