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Displaying Vehicle Driving Mode - Effects on Pedestrian Behavior and Perceived Safety

Joisten, Philip ; Alexandi, Emanuel ; Drews, Robin ; Klassen, Liane ; Petersohn, Patrick ; Pick, Alexander ; Schwindt, Sarah ; Abendroth, Bettina
Hrsg.: Ahram, Tareq ; Karwowski, Waldemar ; Pickl, Stefan ; Taiar, Redha (2020)
Displaying Vehicle Driving Mode - Effects on Pedestrian Behavior and Perceived Safety.
Proceedings of the 2nd International Conference on Human Systems Engineering and Design (IHSED2019): Future Trends and Applications. Universität der Bundeswehr München, München, Deutschland (16.09.2019-18.09.2019)
doi: 10.1007/978-3-030-27928-8_38
Konferenzveröffentlichung, Bibliographie

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Kurzbeschreibung (Abstract)

The type and amount of information pedestrians should receive while interacting with an autonomous vehicle (AV) remains an unsolved challenge. The information about the vehicle driving mode could help pedestrians to develop the right expectations regarding further actions. The aim of this study is to investigate how the information about the vehicle driving mode affects pedestrian crossing behavior and perceived safety. A controlled field experiment using a Wizard-of-Oz approach to simulate a driverless vehicle was conducted. 28 participants experienced a driverless and a human-operated vehicle from the perspective of a pedestrian. The vehicle was equipped with an external human machine interface (eHMI) that displayed the driving mode of the vehicle (driverless vs. human-operated). The results show that the crossing behavior, measured by critical gap acceptance, and the subjective reporting of perceived safety did not differ statistically significantly between the driverless and the human-operated driving condition.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2020
Herausgeber: Ahram, Tareq ; Karwowski, Waldemar ; Pickl, Stefan ; Taiar, Redha
Autor(en): Joisten, Philip ; Alexandi, Emanuel ; Drews, Robin ; Klassen, Liane ; Petersohn, Patrick ; Pick, Alexander ; Schwindt, Sarah ; Abendroth, Bettina
Art des Eintrags: Bibliographie
Titel: Displaying Vehicle Driving Mode - Effects on Pedestrian Behavior and Perceived Safety
Sprache: Englisch
Publikationsjahr: 2020
Ort: Cham, Switzerland
Verlag: Springer Natur Switzland AG
Buchtitel: Human Systems Engeneering and Design II
Reihe: Advances in Intelligent Systems and Computing
Band einer Reihe: Volume 1026
Veranstaltungstitel: Proceedings of the 2nd International Conference on Human Systems Engineering and Design (IHSED2019): Future Trends and Applications
Veranstaltungsort: Universität der Bundeswehr München, München, Deutschland
Veranstaltungsdatum: 16.09.2019-18.09.2019
DOI: 10.1007/978-3-030-27928-8_38
URL / URN: https://link.springer.com/book/10.1007/978-3-030-27928-8#toc
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Kurzbeschreibung (Abstract):

The type and amount of information pedestrians should receive while interacting with an autonomous vehicle (AV) remains an unsolved challenge. The information about the vehicle driving mode could help pedestrians to develop the right expectations regarding further actions. The aim of this study is to investigate how the information about the vehicle driving mode affects pedestrian crossing behavior and perceived safety. A controlled field experiment using a Wizard-of-Oz approach to simulate a driverless vehicle was conducted. 28 participants experienced a driverless and a human-operated vehicle from the perspective of a pedestrian. The vehicle was equipped with an external human machine interface (eHMI) that displayed the driving mode of the vehicle (driverless vs. human-operated). The results show that the crossing behavior, measured by critical gap acceptance, and the subjective reporting of perceived safety did not differ statistically significantly between the driverless and the human-operated driving condition.

Freie Schlagworte: Vehicle Driving Mode · Automation Status · Pedestrian Behavior · Perceived Safety · Human Machine Interface · Human Machine Interaction
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Institut für Arbeitswissenschaft (IAD)
Hinterlegungsdatum: 03 Sep 2019 05:48
Letzte Änderung: 03 Jul 2024 02:40
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