Matching vs. Mismatching Signals of External Human-Machine Interface and Vehicle Kinematics: An Examination of Pedestrian Crossing Behavior and Trust, Safety, and Affective Ratings in Interactions with Differently Sized Automated Vehicles

Highly automated vehicles (HAVs) will soon be introduced into mixed urban traffic. Pedestrians might have an idea of HAVs. Nevertheless, they probably have never interacted with them before. Moreover, pedestrians will not be able to communicate with HAVs like they are used to with manual vehicles. External human–machine interfaces (eHMIs) are possible design solutions for HAVs to ensure safe interaction with other road users. Light-based eHMIs positively affected pedestrians’ trust ratings, perceived safety, and willingness to cross. However, previous studies often neglected the effect of vehicle size, although larger-sized HAVs could be potentially perceived as the more significant threat. Additionally, the relationship between vehicle kinematics and eHMIs for differently sized HAVs remains an underexplored research topic. This study investigated the effects of vehicle size (small vs. large), eHMI state (dynamic eHMI vs. static eHMI vs. no eHMI), and vehicle kinematics (yielding vs. non-yielding) on pedestrian crossing behavior and their subjective assessment. In virtual reality, the authors created a shared space traffic scenario, in which the eHMI and vehicle kinematics matched or did not match. For yielding conditions, the results showed that participants felt more aroused with larger HAVs than with smaller HAVs. Moreover, pedestrians initiated their crossing significantly earlier when both vehicle sizes had a dynamic eHMI compared to a static eHMI vs. no eHMI. Additionally, pedestrians evaluated a dynamic eHMI with higher trust ratings, higher perceived safety, and more positive affective reactions. The results manifested that the use of dynamic eHMIs can effectively enhance pedestrian-vehicle communication with a large and a small HAV. For non-matching conditions, the participants tended to rely on the vehicle kinematics for both vehicle sizes. Overall, the study highlighted the potential of eHMIs for pedestrian interactions with HAVs of varying sizes when they are well-coordinated with the vehicle kinematics, aiming to enhance safety and efficiency in mixed-traffic environments.

• Record URL:
  • https://doi.org/10.1016/j.trf.2024.10.022
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1369847824002997
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13698478
• Supplemental Notes:
  • © 2024 The Author(s). Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Lau, Merle
  • Wilbrink, Marc
  • Oehl, Michael
• Publication Date: 2024-11

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 1092-1104
• Serial:
  • Transportation Research Part F: Traffic Psychology and Behaviour
  • Volume: 107
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1369-8478
  • Serial URL: http://www.sciencedirect.com/science/journal/13698478

Subject/Index Terms

• TRT Terms: Attitudes; Autonomous vehicles; Kinetics; Pedestrian movement; Pedestrian vehicle interface; Urban areas
• Subject Areas: Highways; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01937796
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 22 2024 2:27PM