A Study of Chinese Professional Drivers' Electroencephalogram Characteristics under Angry Driving Based on Field Experiments

Although some characteristics of physiological signals under different emotions have been studied previously, the differences in electroencephalograms (EEG) between normal driving and angry driving are generally unknown. Moreover, motorists from different countries may have different EEG characteristics because of their different customs, lifestyles, and cultures. Because of this, it is believed that the traffic environment and driving behaviors in China are very different from those in developed countries. Therefore, a study of a motorist's EEG characteristics under angry driving conditions is necessary and beneficial for better understanding the impacts of aggressive driving on traffic safety in China, where "road rage" is common. This study is different from traditional laboratory simulation experiments because ten professional drivers were recruited to drive along a real and particularly busy route in Wuhan. The EEG data and driver anger level scale (reported by the driver himself) were recorded. Study results show that the amplitude of the EEG signal is significantly bigger under angry driving conditions. Furthermore, the mean value of frequency percentage of β waves is significantly larger under angry driving conditions than the value under normal driving conditions. Finally, the mean value of the frequency percentage of δ waves is much smaller under angry driving conditions than the value under normal driving conditions. The results can provide an effective method to distinguish between angry driving and normal driving, which can then provide theoretical support for designing emotion recognition equipment in the future.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 2192-2208
  • Monograph Title: CICTP 2014: Safe, Smart, and Sustainable Multimodal Transportation Systems

Subject/Index Terms

Filing Info

  • Accession Number: 01531536
  • Record Type: Publication
  • ISBN: 9780784413623
  • Files: TRIS, ASCE
  • Created Date: Jul 2 2014 3:03PM