Abstract
Misunderstandings between automated vehicles and surrounding traffic sometimes occur in interactions because AV do not always act human-like. Knowledge on AV is likely to influence expectations of vehicle behavior in interaction situations and drivers might change their behavior accordingly when interacting with AV. It might thus be important to understand how human drivers expect AV to interact in traffic and whether human driving behavior changes in interaction with AV. In a video-based approach, the expectations of non-automated road users towards AV were compared to the expectations towards human drivers in the same situation. Results show that drivers expect AV to show a less aggressive, more safety-oriented driving style. However, drivers showed a similar frequency of cooperation towards AV and human drivers. Although a clear difference in behavior expectations was identified, no negative consequences for interactions were found.
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References
SAE On-Road Automated Vehicle Standards Committee. Information Report J3016: Taxonomy and Definitions (2014). https://www.sae.org/misc/pdfs/automated_driving.pdf
Fahrenkrog, F., Wang, L., Rösener, C., Sauerbier, J., Breunig, S.: Impact analysis for supervised automated driving applications. Deliverable D7.3. AdaptIVe (2017)
Nilsson, J., Silvlin, J., Brännström, M., Coelingh, E., Fredriksson, J.: If, when, and how to perform lane change maneuvers on highways. IEEE Intell. Transp. Syst. Mag. 8, 68–78 (2016)
Do, Q.H., Mita, S., Tehrani, H., Egawa, M., Muto, K., Yoneda, K.: Human drivers based active-passive model for automated lane change. IEEE Intell. Transp. Syst. Mag. 9, 42–56 (2017)
Färber, B.: Communication and communication problems between autonomous vehicles and human drivers. In: Gerdes, J., Lenz, B., Maurer, M., Winner, H. (eds.) Autonomous Driving. Technical, Legal and Social Aspects, pp. 125–144. SpringerOpen, Heidelberg (2016)
Brown, B., Laurier, E.: The trouble with autopilots: assisted and autonomous driving on the social road. In: CHI 2017: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, CO, USA, pp. 416–429 (2017)
Sommer, K.C.: Vorausschauendes Fahren. Erfassung, Beschreibung und Bewertung von Antizipationsleistungen im Straßenverkehr. Ph.D. thesis, University of Regensburg (2013). https://epub.uni-regensburg.de/28290/
Endsley, M.R.: Toward a theory of situation awareness in dynamic systems. Hum. Factors 37, 31–64 (1995)
Stahl, P., Donmez, B., Jamieson, G.A.: Anticipation in driving: the role of experience in the efficacy of pre-event conflict cues. IEEE Trans. Hum.-Mach. Syst. 44, 603–613 (2014)
Pöhler, G., Heine, T., Deml, B.: Einfluss der Erwartungshaltung auf das Übernahmeverhalten in automatischer Fahrzeugführung. In: 11. Workshop Fahrerassistenzsysteme und automatisiertes Fahren, FAS 2017. Walting, Germany, pp. 53–62 (2017)
Beggiato, M., Krems, J.F.: The evolution of mental model, trust and acceptance of adaptive cruise control in relation to initial information. Transp. Res. Part F 18, 47–57 (2013)
Van Loon, R.J., Martens, M.H.: Automated driving and its effect on the safety ecosystem: how do compatibility issues affect the transition period? Procedia Manuf. 3, 3280–3285 (2015)
TRL: Driver responses to encountering automated vehicles in an urban environment. GATEway Project Report RPR807 (2017). https://gateway-project.org.uk/ppr807/
Josten, J., Zlocki, A., Eckstein, L.: Untersuchung der Bewältigungsleistung des Fahrers von kurzfristig auftretenden Wiederübernahmesituationen nach teilautomatischem, freihändigen Fahren. FAT-Schriftenreihe 289 (2016)
Zeeb, K., Buchner, A., Schrauf, M.: Is take-over time all that matters? The impact of visual-cognitive load on driver take-over quality after conditionally automated driving. Accid. Anal. Prev. 92, 230–239 (2016)
Merat, N., Jamson, A.H., Lai, F.C.H., Carsten, O.M.J.: Highly automated driving, secondary task performance, and driver state. Hum. Factors 54, 762–771 (2012)
Lajunen, T., Parker, D., Summala, H.: The manchester driver behavior questionnaire: a cross-cultural study. Accid. Anal. Prev. 36, 231–238 (2004)
Karrer, K., Glaser, C., Clemens, C., Bruder, C.: Technikaffinität erfassen – der Fragebogen TA-EG. In: A. Lichtenstein, C. Stößel, C. Clemens (eds.) Der Mensch im Mittelpunkt technischer Systeme. 8. Berliner Werkstatt Mensch-Maschine-Systeme (ZMMS Spektrum) 22 (29), pp. 196–201. VDI Verlag GmbH, Düsseldorf (2009)
Jian, J.-Y., Bisantz, A.M., Drury, C.: Foundations for an empirically determined scale of trust in automated systems. Int. J. Cognit. Ergon. 4, 53–71 (2000)
Pöhler, G., Heine, T., Deml, B.: Itemanalyse und Faktorstruktur eines Fragebogens zur Messung von Vertrauen im Umgang mit automatischen Systemen. Zeitschrift für Arbeitswissenschaft 70, 151–160 (2016)
Damböck, D., Weißgerber, T., Kienle, M., Benlger, K.: Requirements for cooperative vehicle guidance. In: Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportations Systems (ITSC 2013), pp. 1656–1661 (2013)
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This research was supported by the Profile Area ICT of RWTH Aachen University (RWTH-PH-ICT).
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Josten, J., Kotte, J., Eckstein, L. (2019). Expectations of Non-automated Road Users for Interactions in Mixed Traffic. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2018. Advances in Intelligent Systems and Computing, vol 786. Springer, Cham. https://doi.org/10.1007/978-3-319-93885-1_42
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DOI: https://doi.org/10.1007/978-3-319-93885-1_42
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