Abstract
To ensure acceptance and conformity to society’s expectations for Automated Vehicles (AV), not only objective, but also subjective measures of safety in encounters between AV and Vulnerable Road Users (VRU) must be investigated. Objective safety of a traffic situation can be measured using Inoue et al.’s Safety Cushion Time (SCT) [8], which describes the additional braking distance available due to preventive driver actions.
Method. This work describes an online study (within-subject design) with videos of different traffic scenarios with N = 36 participants. This study measured the influence of visibility of a driving person (yes/no) and Safety Cushion Times (1.5 s/ 2 s/ 2.5 s) on pedestrian’s perceived safety. Outcome variables included perceived safety, acceptance, conformity of vehicle behavior to pedestrians’ expectations, and emotional reaction.
Results & Conclusion. Low SCT values (= high acceleration combined with late braking) resulted in a low subjective safety assessment of a situation, low acceptance of vehicle behavior and negative emotional reaction of pedestrians. High SCT values (=low acceleration and early braking) resulted in high subjective safety ratings, high acceptance, and high conformity to expectations, thus resulting in a positive emotional reaction.
Visibility of a driving person had a lower influence on ratings of subjective safety. Therefore, it is recommended to incorporate our findings into a model for driving behavior for AV if the AV needs to be seen as considerate and subjectively safe.
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References
Matthaei, R., et al.: Autonomes fahren. In: Winner, H., Hakuli, S., Lotz, F., Singer, C. (eds.) Handbuch Fahrerassistenzsysteme. A, pp. 1139–1165. Springer, Wiesbaden (2015). https://doi.org/10.1007/978-3-658-05734-3_61
Zwicker, L., Petzoldt, T., Schade, J., Schaarschmidt, E.: Kommunikation zwischen automatisierten Kraftfahrzeugen und anderen Verkehrsteilnehmern - Was brauchen wir überhaupt [Communication between Automated Vehicles and Other Road Users - What Do We Need Anyway]. In: Bruder, R., Winner, H. (eds.) Hands off, Human Factors off? - Welche Rolle spielen Human Factors in der Fahrzeugautomation, pp. 47–57. Universitäts- und Landesbibliothek Darmstadt, Darmstadt (2019)
Schewe, S.: Subjektives Sicherheitsgefühl [Subjective feeling of safety]. In: Lange, H.-J., Gasch, M. (eds.) Wörterbuch zur Inneren Sicherheit, 1st edn., pp. 322–325. VS Verlag für Sozialwissenschaften, Wiesbaden (2006)
Fraedrich, E., Lenz, B.: Gesellschaftliche und individuelle Akzeptanz des autonomen Fahrens [Social and individual acceptance of autonomous driving]. In: Maurer, M., Gerdes, J.C., Lenz, B., Winner, H. (eds.) Autonomes Fahren, pp. 639–660. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-45854-9_29
Van der Laan, J.D., Heino, A., De Waard, D.: A simple procedure for the assessment of acceptance of advanced transport telematics. Transp. Res. Part C Emerg. Technol. 5(1), 1–10 (1997)
Pillai, A.K.: Virtual reality based study to analyse pedestrian attitude towards autonomous vehicles. Master’s thesis, KTH Royal Institute of Technology (2017). http://urn.fi/URN:NBN:fi:aalto-201710307409
Yang, S.: Driver behavior impact on pedestrians’ crossing experience in the conditionally autonomous driving context. Master’s thesis, KTH Royal Institute of Technology (2017). https://www.diva-portal.org/smash/record.jsf?pid=diva2:1169360
Inoue, H., El-Haji, M., Freudenmann, T., Zhang, H., Raksincharoensak, P., Saito, Y.: Validation methodology to establish safe autonomous driving algorithms with a high driver acceptance using a virtual environment. In: Proceedings of the 5th International Symposium on Future Active Safety Technology Towards Zero-Traffic Accident (FAST-zero 2019), Blacksburg, Virgina, USA (2019)
Färber, B.: Kommunikationsprobleme zwischen autonomen Fahrzeugen und menschlichen Fahrern. In: Maurer, M., Gerdes, JChristian, Lenz, B., Winner, H. (eds.) Autonomes Fahren, pp. 127–146. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-45854-9_7
Bradley, M.M., Lang, P.J.: Measuring emotion: The self-assessment manikin and the semantic differential. J. Behav. Ther. Exp. Psychiatry 25(1), 49–59 (1994). https://doi.org/10.1016/0005-7916(94)90063-9
Saito, Y., Inoue, H., El-Haji, M., Freudenmann, T., Raksincharoensak, P.: Context-sensitive hazard anticipation based on driver behavior analysis and cause-and-effect chain study. In: Keqiang Li (ed.), Proceedings of the 14th International Symposium on Advanced Vehicle Control. AVEC 2018, Beijing, China, 16–20 July 2018 (2018)
Lee, J.D., See, K.A.: Trust in automation: designing for appropriate reliance. Hum. Factors (2004). https://doi.org/10.1518/hfes.46.1.50_30392
Rupp, J.D., King, A.G.: Autonomous Driving - A Practical Roadmap. SAE Technical Paper 2010-01-2335 (2010). https://doi.org/10.4271/2010-01-2335
Neukum, A., Lübbeke, T., Krüger, H.-P., Mayser, C., Steinle, J.: ACC-Stop&Go: Fahrerverhalten an funktionalen Systemgrenzen [ACC-Stop&Go: Driver behavior at functional system limits]. In: Maurer, M., Stiller, C. (eds.) 5. Workshop Fahrerassistenzsysteme - FAS 2008, pp. 141–150 (2008)
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Bopp-Bertenbreiter, V., Pottin, D., Wagner-Hartl, V. (2022). How Should Automated Vehicles Approach Pedestrians? – The Influence of Different Approximation Behaviors & Driver Visibility on Perceived Situation Criticality. In: Stephanidis, C., Antona, M., Ntoa, S., Salvendy, G. (eds) HCI International 2022 – Late Breaking Posters. HCII 2022. Communications in Computer and Information Science, vol 1655. Springer, Cham. https://doi.org/10.1007/978-3-031-19682-9_45
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