Trust in Warehouse Automation: A Generational Study of Workers and Automated Guided Vehicles

Abstract

Trust is essential in human–machine interaction, yet generational differences in trust remain underexplored. This study examines how different worker generations perceive and interact with Automated Guided Vehicles (AGVs) in warehouses. We conducted a two-phase study: first, contextual user study with semi-structured interviews (N = 6), using illustrated decision-making scenarios. The second phase was an online study (N = 95) featuring video-based briefings and the same scenarios. Our research addressed two key questions: (1) How do different tasks contexts influence trust in AGVs’ during collaborative activities? and (2) How do perceptions of safety and reliability impact trust in HMI across generations? Findings indicate that task success and visible safety features enhance trust, while task failures reduce it. Although generational differences were not always significant, specific scenarios revealed notable variations, suggesting that context and prior experience shape trust development. Moreover, discrepancies between reported trust and actual reliance behaviours highlight the need for dynamic trust calibration strategies. These insights contribute to understanding trust in human–machine interaction, emphasizing the importance of designing AGVs that balance safety and efficiency. Our findings underscore the necessity of adaptive systems that account for varying trust levels across generations to foster effective human-machine collaboration in warehouse environments.