Analysis and identification of driver posture and state of mind

Creative Commons License

Ibolar C., Çetin E., Akdoğan E.


  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.554-561


 Most of the traffic accidents are because of driver distraction that may be as a result of engagement in a

secondary activity (such as texting, eating), or the driver's state of mind (sleepy, tired, angry, nervous, etc.). There are

many studies available in the literature about determining and monitoring the driver attention. These studies can be

physical measures; 4) driving performance measures; and 5) hybrid measures. The first 2 approach is not suitable for

real-time applications. Physical measures are related to driver posture and can be analyzed real-time by using

appropriate sensors. Almost all academic studies and commercial products on some luxury intelligent cars on the

market use vision based systems for this purpose. Furthermore, researches are ongoing to improve the algorithms that

interpret the driver‘s physical measures. On the other hand, driver performance can be interpreted using the variables

collected in intelligent cars by suitable algorithms. Some commercial products use the history of steering wheel torque

and position variables to identify the driver distraction. With continually improving technology, sensors are evolving

both in terms of precision and price. An example is the torque sensor which started to be used to measure the torque

applied by the driver in order to determine the level of assistance of the steering system. However, 6 axes torque/force

sensors are highly expensive to be used in the market. On the other hand, once they become cheap and easily available,

they can be used to interpret both the driver posture and the state of mind as the steering wheel is one of the most

critical parts of the car where the driver interacts with. For instance, if the driver is maneuvering with single hand, the

position of the driver hand can be determined analytically from the torques and forces that the driver exerts to the

steering wheel. Hence, interpreting the driver’s posture as well as state of mind may become possible using the hand

position and the torques and forces that the driver exerts. In this study, a steering wheel jig is designed and produced

equipped with a 6 axes torque/force sensor and an encoder in order to develop algorithms to determine the driver’s