Parseh Designers Transportation Research Institute Quarterly Journal of Transportation Engineering 2008-6598 Articles in Press 2025 12 21 The Evaluation of the Effects of Music Characteristics on Driving Performance and Physiological Arousal in a Simulator Environment The Evaluation of the Effects of Music Characteristics on Driving Performance and Physiological Arousal in a Simulator Environment 236803 10.22119/jte.2025.553437.2750 FA Alireza Sadeghi Transportation Planning, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran Saeid Sherafatipour Department of Transportation Planning ,Faculty of Civil and Environmental Engineering,Tarbiat Modares University, Tehran, Iran 0009-0004-2291-1718 Hojatollah Farahani Associate Professor, Department of Psychology, Tarbiat Modares University, Tehran, Iran 0000-0002-9799-7008 Journal Article 2025 10 15 This study quantifies the effects of the structural components of in-cabin music on driving performance and physiological arousal in a within-subject design with 50 licensed drivers. Fifteen music scenarios, derived from a fractional factorial plan manipulating three structural variables—emotion conveyed by the music, tempo, and playback volume—were implemented in a driving simulator; scenario order was counterbalanced with 5-min inter-scenario breaks. The physiological index was recorded from a GSR sensor as skin resistance (SR) and mapped to a unified metric Arousal Index = −z(log SR); performance measures included driving errors, mean/variability of speed, lateral lane deviation, and reaction time. Music-attitude profiling via PCA confirmed data adequacy and, using k-means, yielded an optimal K = 5 attitude typology. Clustering on performance–physiology features revealed four stable driver response types (K = 4; Silhouette = 0.463): (1) low errors/low arousal, (2) medium errors/medium arousal, (3) high errors/high arousal, and (4) low errors/high arousal. Within-subject tests showed significant differences across musical conditions (Friedman for errors: χ² = 24.33, df = 2, p < 0.001; for SR/Arousal: χ² = 22.11, df = 2, p < 0.001); Wilcoxon pairwise comparisons with Holm correction indicated robust contrasts for happy ↔ anxiety-inducing and sad ↔ anxiety-inducing music across both domains (p ≤ 0.003), while happy ↔ sad differed only in SR/Arousal (p = 0.021). Findings indicate that music-induced arousal modulates both behavioral safety and physiological state, and that inter-individual heterogeneity is decomposable into stable response types. This study quantifies the effects of the structural components of in-cabin music on driving performance and physiological arousal in a within-subject design with 50 licensed drivers. Fifteen music scenarios, derived from a fractional factorial plan manipulating three structural variables—emotion conveyed by the music, tempo, and playback volume—were implemented in a driving simulator; scenario order was counterbalanced with 5-min inter-scenario breaks. The physiological index was recorded from a GSR sensor as skin resistance (SR) and mapped to a unified metric Arousal Index = −z(log SR); performance measures included driving errors, mean/variability of speed, lateral lane deviation, and reaction time. Music-attitude profiling via PCA confirmed data adequacy and, using k-means, yielded an optimal K = 5 attitude typology. Clustering on performance–physiology features revealed four stable driver response types (K = 4; Silhouette = 0.463): (1) low errors/low arousal, (2) medium errors/medium arousal, (3) high errors/high arousal, and (4) low errors/high arousal. Within-subject tests showed significant differences across musical conditions (Friedman for errors: χ² = 24.33, df = 2, p < 0.001; for SR/Arousal: χ² = 22.11, df = 2, p < 0.001); Wilcoxon pairwise comparisons with Holm correction indicated robust contrasts for happy ↔ anxiety-inducing and sad ↔ anxiety-inducing music across both domains (p ≤ 0.003), while happy ↔ sad differed only in SR/Arousal (p = 0.021). Findings indicate that music-induced arousal modulates both behavioral safety and physiological state, and that inter-individual heterogeneity is decomposable into stable response types.