Owing to the increasing prevalence of autonomous vehicles in mixed-traffic environments, developing effective approaches for them to interact with road users is essential. One widely investigated method is external human-machine interfaces (eHMIs), which help communicate a vehicle’s intentions. However, most previous studies have focused on interactions with pedestrians. This study investigates the effect of eHMI messages on the situation awareness of drivers following autonomous buses. Using a virtual-reality driving simulator, we recreated realistic traffic scenarios to examine this interaction. The findings indicate that eHMI messages can improve the awareness of the following drivers. Additionally, we observed that the timing of these messages involves balancing between helping drivers decide more rapidly and avoiding potential safety risks. Although this study was conducted in a simulated environment, the results provide useful insights into the future implementation of autonomous buses in real-world traffic systems.

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Effect of eHMI on Driver Situation Awareness in Autonomous-Bus Environment

  • Yuga Kato,
  • Naomi Kuwata,
  • Yu Ichihashi,
  • Kai Kitayama,
  • Takehiko Yamaguchi,
  • Shinji Miyake,
  • Daiji Kobayashi

摘要

Owing to the increasing prevalence of autonomous vehicles in mixed-traffic environments, developing effective approaches for them to interact with road users is essential. One widely investigated method is external human-machine interfaces (eHMIs), which help communicate a vehicle’s intentions. However, most previous studies have focused on interactions with pedestrians. This study investigates the effect of eHMI messages on the situation awareness of drivers following autonomous buses. Using a virtual-reality driving simulator, we recreated realistic traffic scenarios to examine this interaction. The findings indicate that eHMI messages can improve the awareness of the following drivers. Additionally, we observed that the timing of these messages involves balancing between helping drivers decide more rapidly and avoiding potential safety risks. Although this study was conducted in a simulated environment, the results provide useful insights into the future implementation of autonomous buses in real-world traffic systems.