Investigating the Impact of Music on Driver Safety with a Focus on Biometric Indicators and Personality Traits

Document Type : Scientific - Research

Authors
Alireza Sadeghi 1
Saeid Sherafatipour 2
Hojatollah Farahani 3
1 M.Sc. in Transportation Planning, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran
2 Assistant Professor, Department of Transportation Planning, Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran
3 Associate Professor, Department of Psychology, Tarbiat Modares University, Tehran, Iran
10.22119/jte.2025.553437.2750
Abstract
This research investigates driving performance and physiological arousal as influenced by structural features of music using a within-subject design with 50 licensed participants. Fifteen music trials, created using fractional factorial design with factors including manipulated musical emotion, musical tempo, and volume, are conducted in the BeamNG-Drive simulator. The physiological measure SR was logged and scaled to create a common Arousal Index. The driving variables logged include driving errors, speeding pattern, lateral deviation from lanes, and reaction time. PCA on music-attitude data validated data adequacy, while k-means clustering extracted five distinct types of attitudes on music. Cluster analysis on features related to performance and physiology also extracted four stable patterns of responses from “low-error/low-arousal” to “high-error/high-arousal.” On within-subject statistical tests, musical condition had significant effects on both error rates and levels of arousal, and highest arousal and number of errors occurred for anxiety-inducing musical content, followed by “happy” music, with “sad” music in between. This research has important implications for how music can affect behavioral safety systematically through physiological arousal, and how inter-individual differences are important to this process. Their work directly applies to developing intelligent in-car music recommendation systems, physiological detection technologies to prevent excessive arousal, and procedures for safe management of audio content, especially in challenging driving environments.
Keywords
Traffic safety
In-vehicle music
Electrodermal activity (EDA)
Cluster analysis
Driving simulator
Subjects
- شیخ‌الاسلامی، س.، صفارزاده، م.، و ممدحی، ا. (۱۴۰۲). نقش عوامل هیجانی در سبک رانندگی، رساله دکتری، دانشگاه تربیت مدرس، دانشکده عمران و محیط زیست.
 
- Belin, M. A., Tillgren, P., & Vedung, E. (2012). Vision Zero—a road safety policy innovation. International Journal of Injury Control and Safety Promotion, 19(2), 171–179.
https://doi.org/10.1080/17457300.2011.635213
 
- Brodsky, W. (2002). The effects of music tempo on simulated driving performance and vehicular control. Transportation Research Part F: Traffic Psychology and Behaviour, 4, 219–241.
 
- Ghojazadeh, M., Akbari, H., Kachooei, M., Samiei, F., & Mirnasab, M. (2023). The effect of music on driving performance: A systematic review and meta-analysis. Health Promotion Perspectives, 13(4), 267–279.
https://doi.org/10.34172/hpp.2023.32
 
- Hayashi, Y., Friedel, J. E., Foreman, A. M., & Wirth, O. (2023). Hierarchical cluster analysis of texting while driving: A look at intention–behavior gap. Journal of Safety Research, 85, 398–404. 
https://doi.org/10.1016/j.jsr.2023.04.007
 
- North, A. C., & Hargreaves, D. J. (1999). The functions of music in everyday life: Redefining the social in music psychology. Psychology of Music, 27(1), 71–83.
 
- Reason, J. (1990). Human Error. Cambridge University Press.
 
- Rasmussen, J. (1983). Skills, rules, and knowledge: Signals, signs, and symbols, and other distinctions in human performance models. IEEE Transactions on Systems, Man and Cybernetics, SMC-13, 257–266.
https://doi.org/10.1109/TSMC.1983.6313160
 
- Ünal, A. B., de Waard, D., Epstude, K., & Steg, L. (2013). Driving with music: Effects on arousal and performance. Transportation Research Part F: Traffic Psychology and Behaviour, 21, 52–65.
https://doi.org/10.1016/j.trf.2013.09.004
 
- Navarro, J., Osiurak, F., Gaujoux, V., Ouimet, M. C., & Reynaud, E. (2019). Driving under the influence: How music listening affects driving behaviors. Journal of Visualized Experiments, 145, e58342.
 
- Navarro, J., Gaujoux, V., Ouimet, M. C., Ferreri, L., Reynaud, E., & Osiurak, F. (2023). How does background music affect drivers’ behaviours, emotions and mood behind the wheel? Transportation Research Part F: Traffic Psychology and Behaviour, 95, 271–285.
 
- Wickens, C. D. (2008). Multiple resources and mental workload. Human Factors, 50(3), 449–455.
https://doi.org/10.1518/001872008X288394
 
- Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habit-formation. Journal of Comparative Neurology and Psychology, 18, 459–482.
 
- Schubert, E. (2004). Modeling perceived emotion with continuous musical features. Music Perception, 21(4), 561–585.
 
- Taubman-Ben-Ari, O., Mikulincer, M., & Gillath, O. (2005). From parents to children–similarity in parents and offspring driving styles. Transportation Research Part F: Traffic Psychology and Behaviour, 8(1), 19–29.
Quarterly Journal of Transportation Engineering
Volume 17, Issue 4 - Serial Number 69
Spring 2026
Pages 5737-5750

  • Receive Date 15 October 2025
  • Revise Date 23 November 2025
  • Accept Date 08 December 2025