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How do angry drivers respond to emotional music? A comprehensive perspective on assessing emotion

  • S. Maryam FakhrHosseini
  • Myounghoon JeonEmail author
Original Paper

Abstract

Emotions influence the way drivers process and react to internal or environmental factors, but relatively little research has focused on drivers’ emotions. Of many emotional states, anger is considered the most serious threat on the road. Therefore, having an affective intelligent system in the car that can estimate drivers’ anger and respond to it appropriately can help drivers adapt to moment-to-moment changes in driving situations. To this end, we integrated behavioral, physiological, and subjective data to monitor drivers’ affective states in various driving contexts to address the question: “can self-selected music mitigate the effects of anger on driving performance?” In our experiment, three groups of participants (in total 52) drove using a driving simulator: anger without music, anger with music, and neutral without music. Results showed that angry drivers who did not listen to music had riskier driving behavior than emotion-neutral drivers. Results from heart rate, oxygenation level in prefrontal cortex, and self-report questionnaires showed that music could help angry drivers react at the similar level to emotion-neutral drivers. Regarding personality characteristics, drivers who had anger-expression out style had riskier driving behavior. Divers’ workload data showed lower performance and higher effort for angry drivers without music. In conclusion, this study shows that multimodal sensing can be effectively used to holistically assess drivers’ emotional states and that music can be used as a possible multimodal strategy to mitigate the anger effects on driving performance as well as drivers’ subjective experiences.

Keywords

Emotions Music effects on driving fNIRS Heart rate Driving simulation 

Notes

Acknowledgements

This research was supported by a Grant (Code 17TLRP-B131486-01) from Transportation and Logistics R&D Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Cognitive and Learning SciencesMichigan Technological UniversityHoughtonUSA
  2. 2.Department of Industrial and Systems EngineeringVirginia TechBlacksburgUSA

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