Interactions Between Workers and Automated Guided Vehicles: Impact of eHMI Design
Published in Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2025
As manufacturing facilities integrate Autonomated Guided Vehicles (AGVs) to improve workflow efficiency, enhancing human-AGV interaction remains critical for workplace safety. While prior research has focused on vehicle and pedestrian motion prediction, effective interaction requires two-way communication, where the AGVs clearly convey intentions to the workers to enhance safety. This study investigates the impact of external Human-Machine Interface (eHMI) integrated with a predictive model on AGV-worker interaction. We designed LED light strip patterns to convey intentions and selected optimal designs through an online survey. We deployed three types of AGVs in a virtual reality (VR) environment: Control, Prediction, and eHMI + Prediction. Participants completed tasks while interacting with AGVs, followed by subjective assessments of trust, perceived safety, perceived performance, and understandability. A one-way repeated measures ANOVA revealed a significant improvement in perceived safety from eHMI + Prediction condition compared to the Control condition, suggesting that explicit communication via eHMI enhances perceived safety in AGV interactions.
Recommended citation: Han, D. W., Bhat, S., Yang, S., Smith, J., Salour, A., Stroup, T., Pridham, P., Liu, Y., & Yang, X. J. (2025). Interactions Between Workers and Automated Guided Vehicles: Impact of eHMI Design. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 69(1), 1166-1172. https://doi.org/10.1177/10711813251372529
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