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Related Experiment Video

Updated: Aug 10, 2025

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
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Communication between Autonomous Vehicles and Pedestrians: An Experimental Study Using Virtual Reality.

Symbat Zhanguzhinova1, Emese Makó1, Attila Borsos1

  • 1Department of Transport Infrastructure and Water Resources Engineering, University of Győr, Egyetem tér 1, 9026 Győr, Hungary.

Sensors (Basel, Switzerland)
|February 11, 2023
PubMed
Summary

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Autonomous vehicles (AV) use LED signals to communicate intent to pedestrians. This study found explicit communication patterns are quickly learned and effective for safe road crossing decisions.

Area of Science:

  • Human-Computer Interaction
  • Autonomous Systems
  • Transportation Psychology

Background:

  • Pedestrian interaction with autonomous vehicles (AV) presents significant challenges.
  • Traditional human drivers use non-verbal cues (gestures, eye contact) to signal intent.
  • Developing effective communication methods for AVs is crucial for safety.

Purpose of the Study:

  • To investigate the influence of explicit communication patterns on pedestrian decision-making when crossing roads.
  • To assess pedestrian reactions to an LED light display on a virtual AV.
  • To determine if communication patterns are self-explaining and facilitate safe crossing behavior.

Main Methods:

  • A virtual reality (VR) experiment was conducted in an urban pedestrian crossing setting.
Keywords:
LED communicationautonomous vehiclecrossingpedestrianvirtual reality

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  • Participants (n=51) observed a virtual AV with an LED red/green light display approaching.
  • Four scenarios varied AV speed and display signals; participants decided when it was safe to cross.
  • Main Results:

    • The majority of participants correctly identified safe crossing windows based on the AV's signals.
    • While males decided slightly faster, no significant differences in decision-making were found based on gender or age.
    • Participants demonstrated a rapid learning process regarding the LED communication patterns.

    Conclusions:

    • Explicit communication patterns, such as the tested LED display, are effective and quickly understood by pedestrians.
    • AVs can enhance pedestrian safety through clear, self-explaining visual signals.
    • Further research into non-verbal communication for AVs is warranted to improve human-AV interaction.