Given the growing popularity of wearable smart watch with the capability to detect human hand movements, this paper studies the potential to recognize fatigue driving based on steering operation by using a wearable smart watch. The sensor data used includes acceleration and angular velocity data related to drivers’ operation behavior. We analyze the sensors’ data features of smart watch under drivers’ fatigue and normal states, and select 13 principal characteristic parameters by using the method of principal component analysis (PCA). Then the recognition model of fatigue driving based on support vector machine (SVM) is established. The results show that the proposed method recognizes the drivers’ fatigue or normal state more effectively than other methods and its accuracy can reach 83.29%.
Fatigue driving Operation behavior Smart watch Support vector machine
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This work was supported by the National Natural Science Foundation of China (Grant No. 61573075), the National Key R&D Program (Grant No. 2016YFB0100904), the Natural Science Foundation of Chongqing (Grant No. cstc2017jcyjBX0001).
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