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Identification of Cognitive Distraction Using Physiological Features for Adaptive Driving Safety Supporting System

DOI: 10.1155/2013/817179

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Abstract:

It was identified that traffic accidents relate closely to the driver’s mental and physical states immediately before the accident by our questionnaire survey. Distraction is one of the key human factors involved in traffic accidents. We reproduced driver’s cognitive distraction on a driving simulator by means of imposing cognitive loads such as doing arithmetic and having conversation while driving. Visual features such as test subjects’ gaze direction, pupil diameter, and head orientation, together with heart rate from ECG, were used in this study to detect the cognitive distraction. We improved detection accuracy obtained from earlier studies by using the AdaBoost. This paper also suggests a multiclass identification using Error-Correcting Output Coding, which can identify the degree of cognitive load. Finally, we verified the effectiveness of the multiclass identification by conducting a series of experiments. All these aimed at developing a constituent technology of a driver monitoring system that is expected to create adaptive driving safety supporting system to lower the number of traffic accidents. 1. Introduction The number of traffic accidents in Japan are on a declining trend. Fatalities caused by traffic accident in Japan have also been gradually declining for the last 12 years, to reach 4,411 at the end of 2012 as shown in Figure 1. The major factor in this decline seems to come from use of devices as standard or optional equipment in vehicles for enhanced crashworthiness (e.g., airbag systems, seatbelts), intensive enforcement of the Road Traffic Law (e.g., forbidding drunk driving), and improving education of road traffic safety. Meanwhile, the number of nonfatal injuries in Japan caused from traffic accidents, though still in a decreasing trend, reached 824,539 at the end of 2012. Therefore establishing technologies which may prevent traffic accidents remains an important issue for the creation of a sustainable mobile society. Figure 1: Number of road traffic accidents, fatalities, and injuries during 1946–2012 in Japan. Accidents and injuries were divided by 100 to put them all in the same scale. The driver support systems such as Electronic Stability Control (ESC), Lane Departure Warning, and Precrash Safety System have been installed into commercial vehicles to prevent from road traffic accidents. Several other safety systems to lower traffic accidents have also been developed and installed in vehicles. One remarkable Precrash Safety System has a feature that can detect the direction of a driver’s face or eyes. But, it is necessary

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