Frontiers in Psychology：超长隧道驾驶中男性驾驶员情感与工作负荷反应的多模态刻画

ORIGINAL RESEARCH article

Front. Psychol.

Sec. Environmental Psychology

Abstract

Extra-long tunnels can impose sustained perceptual, physiological, and regulatory demands on drivers, but affect-relevant and workload-related responses are difficult to assess continuously in naturalistic driving because subjective ratings are retrospective and cannot capture fine-grained spatial variation. This study developed a multimodal, label-free framework to characterize latent affect-relevant and workload-related response patterns during extra long tunnel driving. A naturalistic driving experiment was conducted in a 4.9 km tunnel, during which physiological responses, driving behavior, and gaze measures were collected and organized as a third-order tensor (driver×indicator×segment). CANDECOMP/PARAFAC tensor decomposition was then applied to extract the dominant latent structure without subjective labels. The selected rank-1 solution showed an association with route familiarity. Heart rate and frontal gaze measures contributed most strongly to the latent structure, with additional contributions from vehicle speed and electrodermal activity, suggesting a coupling among autonomic activation, visual attention regulation, and behavioral adaptation. Spatially, elevated factor loadings were observed near tunnel entrances, exits, and several interior segments, indicating that the response patterns observed in male drivers are not limited to transition zones but may also emerge during prolonged tunnel exposure. The study provides exploratory multimodal evidence that may support the interpretation of affect-relevant and workload-related response structures and identifying spatially differentiated response patterns in tunnel transport safety.

Keywords

Affective processes, Driving workload, Multimodal data, Naturalistic driving, Psychophysiological response, Safety risk identification

Received

27 May 2026

Accepted

18 September 2026

Copyright

© 2026 Kang, He, Chen, Chen, Yi, Wang and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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