Abstract
An external Human-Machine-Interface (eHMI) signaling the vehicle’s intended movements facilitates pedestrians’ encounters with self-driving vehicles (SDV). However, there is no standard for automated driving system (ADS) lamps today. This study compares the efficacy of a steady, a flashing and a sweeping light signal to communicate an SDV’s intention to yield. The eHMI designs were evaluated at an unsignalized intersection with participants crossing in front of a yielding Wizard-of-Oz SDV. We analyzed crossing behavior and conducted questionnaires and structured interviews with N = 30 participants to identify eHMI design recommendations. Our research provides evidence that a steady and a flashing signal facilitate user experience, learnability and likeability more than a sweeping light. With a flashing signal, pedestrians tend to cross sooner compared to a sweeping signal, and thus improving traffic flow. Design adjustments to the present signals are proposed. This paper provides guidance in the development of a standardized yielding light signal.
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References
SAE International: Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles (J3016) (2018)
Šucha, M., Dostal, D., Risser, R.: Pedestrian-driver communication and decision strategies at marked crossings. Accid. Anal. Prev. 102, 41–50 (2017)
Mahadevan, K., Somanath, S., Sharlin, E.: Communicating awareness and intent in autonomous vehicle-pedestrian interaction. In: 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–12 (2018)
Matthews, M., Chowdhary, G.V., Kieson, E.: Intent communication between autonomous vehicles and pedestrians (2017)
Lagström, T., Lundgren, V.M.: Automated vehicle’s interaction with pedestrians (2015)
Rothenbücher, D., Li, J., Sirkin, D., Mok, B., Ju, W.: Ghost driver: a field study investigating the interaction between pedestrians and driverless vehicles. In: 25th IEEE International Symposium on Robot and Human Interactive Communication, pp. 795–802 (2016)
Stadler, S., Cornet, H., Theoto, T.N., Frenkler, F.: A tool, not a toy: using virtual reality to evaluate the communication between autonomous vehicles and pedestrians. In: tom Dieck, M.C., Jung, T. (eds.) Augmented Reality and Virtual Reality, pp. 203–216. Springer, Cham (2019)
Merat, N., Louw, T., Madigan, R., Wilbrink, M., Schieben, A.: What externally presented information do VRUs require when interacting with fully automated road transport systems in shared space? Accid. Anal. Prev. 118, 244–252 (2018)
Petzoldt, T., Schleinitz, K., Banse, R.: The potential safety effects of a frontal brake light for motor vehicles. Intell. Transp. Syst. 12, 449–453 (2018)
UNECE. https://wiki.unece.org/download/attachments/78742442/AVSR-04-05e.docx?api=v2
ISO: Road Vehicles: Ergonomic aspects of external visual communication from automated vehicles to other road users (ISO/TR 23049:2018) (2018)
SAE International: Automated Driving System (ADS) Marker Lamp (J3134_201905) (2019)
Dietrich, A., Willrodt, J.-H., Wagner, K., Bengler, K.: Projection-based external human machine interfaces: Enabling interaction between automated vehicles and pedestrians. In: 17th European VR, Driving Simulation and Virtual Reality Conference, pp. 43–50 (2018)
Werner, A.: New colors for autonomous driving: an evaluation of chromaticities for the external lighting equipment of autonomous vehicles. Colour Turn 1, 1–15 (2018)
The Ford Motor Company. https://media.ford.com/content/fordmedia/fna/us/en/news/2017/13/ford-virginia-tech-autonomous-vehicle-human-testing.html
UEQ Data Analysis Tool. https://www.ueq-online.org/Material/Short_UEQ_Data_Analysis_Tool.xlsx
Bartneck, C., Kulic, D., Croft, E., Zoghbi, S.: Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int. J. Soc. Robot. 1, 71–81 (2009)
Mayring, P.: Qualitative content analysis: theoretical foundation, basic procedures and software solution (2014)
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Faas, S.M., Baumann, M. (2020). Yielding Light Signal Evaluation for Self-driving Vehicle and Pedestrian Interaction. In: Ahram, T., Karwowski, W., Pickl, S., Taiar, R. (eds) Human Systems Engineering and Design II. IHSED 2019. Advances in Intelligent Systems and Computing, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-27928-8_29
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DOI: https://doi.org/10.1007/978-3-030-27928-8_29
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