Driver Distraction Detection with a Camera Vision System

• Published in: 2007 IEEE International Conference on Image Processing Vol. 6; pp. VI - 201 - VI - 204
• Main Authors: Kutila, M., Jokela, M., Markkula, G., Rue, M.R.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-09-2007
• Subjects: camera; Cameras; Cellular phones; classification; distraction detection; Driver circuits; Intelligent vehicles; Job shop scheduling; Machine vision; Man machine systems; Monitoring; Navigation; Stereo vision; vehicle; Vehicle driving
• DOI: 10.1109/ICIP.2007.4379556
• EISSN: 2381-8549
• ISBN: 9781424414369; 1424414369
• ISSN: 1522-4880

Driver assistance systems and electronics (e.g. navigators, cell phones, etc.) steal increasing amounts of driver attention. Therefore, the vehicle industry is striving to build a driving environment where input-output devices are smartly scheduled, allowing sufficient time for the driver to focus attention on the surrounding traffic. To enable a smart human-machine interface (HMI), the driver's momentary state needs to be measured. This paper describes a facility for monitoring the distraction of a driver and presents some early evaluation results. The module is able to detect the driver's visual and cognitive workload by fusing stereo vision and lane tracking data, running both rule-based and support-vector machine (SVM) classification methods. The module has been tested with data from a truck and a passenger car. The results show over 80% success in detecting visual distraction and a 68-86 % success in detecting cognitive distraction, which are satisfactory results.