A Multimodal Approach for Monitoring Driving Behavior and Emotions

Studies have indicated that emotions can significantly be influenced by environmental factors; these factors can also significantly influence driver’s emotional state and, accordingly, driving behavior. Furthermore, as the demand for autonomous vehicles is expected to significantly increase within the next decade, a proper understanding of the driver/passenger(s)’ emotions, behavior, and preferences will be needed in order to create an acceptable level of trust with humans. This paper proposes a novel semi-automated approach for understanding the effect of environmental factors on driver’s emotions and behavioral changes through a naturalistic driving study. This setup includes a frontal road and facial camera, smart watch for tracking physiological measurements, and a Controller Area Network (CAN) serial data logger. The results suggest that the driver’s emotion is highly affected by the type of road, presence of a passenger, and weather condition, which potentially can change the driving behaviors. For instance, by defining emotions metrics as valence and engagement, there exist significant differences between human emotion in different weather conditions and road types. Participant’s engagement was higher in rainy and clear weather compared to cloudy weather. Moreover, his engagement was higher in city streets and highways compared to one lane roads and two lane highways. In addition, presence of a passenger increases the amount of engagement of the driver.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation.
  • Corporate Authors:

    Transportation Research Board

    ,    
  • Authors:
    • Tavakoli, Arash
    • Balali, Vahid
    • Heydarian, Arsalan
  • Conference:
  • Date: 2019

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References;
  • Pagination: 14p

Subject/Index Terms

Filing Info

  • Accession Number: 01698156
  • Record Type: Publication
  • Report/Paper Numbers: 19-05204
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:47AM