Monitoring System of Driver’s Health Condition to Prevent Traffic Collision Caused by Health Condition Risks and Cognitive Decline

Driving risks for elderly drivers are known to be associated with age-related diseases and cognitive decline. Furthermore, daily physical conditions such as drowsiness and fatigue also affect cognitive function and driving behavior. Therefore, in order to prevent traffic accidents involving elderly drivers, it is important to provide personal driver support that takes into consideration the effects of daily physical conditions. In this study, the authors explored the feasibility of a monitoring system utilizing daily physical condition data that can be assessed by wearable devices on elderly subjects. Focusing on the sleep characteristics that affect the physical condition, the authors found the relationship between attention function and driving behavior. As a result of the attention function evaluation by the Attention Network Test, irregular sleep time was associated with greater variation in attention function, suggesting that people with irregular sleep time had more unstable attention function. In addition, as a result of the driving behavior evaluation by the Driving Simulator Test, greater variation of the attention function was associated with the larger steering entropy and maximum acceleration of the car. These results suggest that instability of the attention function may cause the rough driving. Combined with the results of relationship between variability of sleep time and attention function, these results suggest that people with irregular sleep time are more likely to engage in rough steering and pedal operation, which may lead to sudden steering and acceleration that can cause accidents. It is also known that elderly people have problems in falling asleep and maintaining sleep than younger people. In order to eliminate traffic accidents involving elderly drivers, a support system that incorporates information on sleep habits will become more important. In recent years, the use of wearable devices has made it possible to objectively acquire daily activity and sleep data, and it is expected to utilize a wider range of daily activity data. In the future, the authors are planning to acquire actual vehicle driving data to understand the relationship between physical condition and driving behavior in more detail.

Language

  • English

Media Info

  • Media Type: Web
  • Features: Figures; Photos; References; Tables;
  • Pagination: 10p
  • Monograph Title: 27th International Technical Conference on the Enhanced Safety of Vehicles (ESV): Enhanced and Equitable Vehicle Safety for All: Toward the Next 50 Years

Subject/Index Terms

Filing Info

  • Accession Number: 01890228
  • Record Type: Publication
  • Report/Paper Numbers: 23-0226
  • Files: TRIS, ATRI, USDOT
  • Created Date: Aug 18 2023 5:25PM