Driver emotion regulation via ambient lighting and music: An EEG-based ergonomic evaluation for intelligent cockpit

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Authors: Yong Peng, Ziteng Zhang, Zhuoxi Jiang, Chenxi Li, Chaojie Fan, Meng Zheng, Xianhui Wu
Cited by: 1
References: 45

Abstract

Effective regulation of drivers’ negative emotions is crucial for traffic safety, particularly in intelligent vehicles increasingly rely on multimodal human-machine interactions. This study integrates neuroergonomics and automotive engineering perspectives to investigate the neural mechanisms through which sensory modulation supports emotional recovery during driving, and to determine whether combined auditory-visual cues produce synergistic benefits beyond unimodal effects. Twenty participants were exposed to aversive audiovisual stimuli followed by simulated driving, during which EEG features (energy, differential entropy, and asymmetric entropy), behavioral indicators, and subjective ratings were obtained. Source-level analysis focused on the dorsolateral prefrontal cortex (dlPFC), one of the regions central to autonomic and affective regulation. Results within this participants group indicated that multisensory stimulation improved emotional and functional recovery, with EEG activity showing tighter coupling with driving performance than with subjective reports, suggesting neural responses may provide more direct markers of safety-relevant restoration. Fast-tempo music paired with green lighting elicited a clear synergistic effect under the tested conditions, whereas its combination with yellow lighting yielded only additive improvements. These findings advance neuroergonomic understanding of how multisensory cues modulate affective and cognitive states during driving and offer preliminary guidance for developing adaptive, emotion-aware cockpit systems aimed at improving driver safety and well-being.

Fields of Study & Subjects

Sleep and Work-Related Fatigue Human-Automation Interaction and Safety Emotion and Mood Recognition

Publication details

Journal / source
Alexandria Engineering Journal
Publisher
Elsevier BV
Volume
138
Pages
51–65
Publication date
1 February 2026
Language
EN