Impact of External Human–Machine Interface Communication Strategies of Automated Vehicles on Pedestrians’ Crossing Decisions and Behaviors in an Urban Environment

Marc Wilbrink, Merle Lau, Johannes Illgner, Anna Schieben and Michael Oehl
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Marc Wilbrink: Institute of Transportation Systems, German Aerospace Center (DLR), 38108 Braunschweig, Germany
Merle Lau: Institute of Transportation Systems, German Aerospace Center (DLR), 38108 Braunschweig, Germany
Johannes Illgner: Department of Psychology, University of Münster, 48149 Münster, Germany
Anna Schieben: Institute of Transportation Systems, German Aerospace Center (DLR), 38108 Braunschweig, Germany
Michael Oehl: Institute of Transportation Systems, German Aerospace Center (DLR), 38108 Braunschweig, Germany

Sustainability, 2021, vol. 13, issue 15, 1-18

Abstract: The development of automated vehicles (AVs) and their integration into traffic are seen by many vehicle manufacturers and stakeholders such as cities or transportation companies as a revolution in mobility. In future urban traffic, it is more likely that AVs will operate not in separated traffic spaces but in so-called mixed traffic environments where different types of traffic participants interact. Therefore, AVs must be able to communicate with other traffic participants, e.g., pedestrians as vulnerable road users (VRUs), to solve ambiguous traffic situations. To achieve well-working communication and thereby safe interaction between AVs and other traffic participants, the latest research discusses external human–machine interfaces (eHMIs) as promising communication tools. Therefore, this study examines the potential positive and negative effects of AVs equipped with static (only displaying the current vehicle automation status (VAS)) and dynamic (communicating an AV’s perception and intention) eHMIs on the interaction with pedestrians by taking subjective and objective measurements into account. In a Virtual Reality (VR) simulator study, 62 participants were instructed to cross a street while interacting with non-automated (without eHMI) and automated vehicles (equipped with static eHMI or dynamic eHMI). The results reveal that a static eHMI had no effect on pedestrians’ crossing decisions and behaviors compared to a non-automated vehicle without any eHMI. However, participants benefit from the additional information of a dynamic eHMI by making earlier decisions to cross the street and higher certainties regarding their decisions when interacting with an AV with a dynamic eHMI compared to an AV with a static eHMI or a non-automated vehicle. Implications for a holistic evaluation of eHMIs as AV communication tools and their safe introduction into traffic are discussed based on the results.

Keywords: human factors; human–machine interaction; external human–machine interface; automated vehicles; vulnerable road users (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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