Electrodermal Insights into Stress Dynamics of AR-Assisted Safety Warnings in Virtual Roadway Work Zone Environments

Abstract

This study examines stress levels in roadway workers utilizing AR-assisted multi-sensory warning systems under varying work intensities. A high-fidelity Virtual Reality environment was used to replicate real-world scenarios, allowing safe exploration of high-risk situations while focusing on the physiological impacts of work conditions. Wearable sensors were used to continuously and non-invasively collect physiological data, including electrodermal activity to monitor stress responses. Analysis of data from 18 participants revealed notable differences in EDR between light- and medium-intensity activities, reflecting variations in autonomic nervous system activity under stress. Also, a feature importance analysis revealed that peak and central tendency metrics of EDR were robust indicators of physiological responses, between light- and medium-intensity activities. The findings emphasize the relationship between AR-enabled warnings, work intensity, and worker stress, offering an approach to active stress monitoring and improved safety practices. By leveraging real-time physiological insights, this methodology has the potential to support better stress management and the development of more effective safety warning systems for roadway work zones. This research also provides valuable guidance for designing interventions to enhance worker safety, productivity, and well-being in high-risk settings.