The paper 'Estimation of the Driving Style Based on the Users’ Activity and Environment Influence’, published in Sensors journal, describes an experiment which includes the evaluation of a self-assessment of the driving style, and a prediction of aggressive driving style based on drivers’ activity and environment parameters.
Sixty seven hours of driving data from 10 drivers were collected for analysis in this study. The new parameters used in the experiment are the car door opening and closing manner, which were applied to improve the prediction accuracy. An Android application called Sensoric was developed to collect low-level smartphone data about the users’ activity. The driving style was predicted from the user’s environment and activity data collected before driving. The prediction was tested against the actual driving style, calculated from objective driving data. The prediction has shown encouraging results, with precision values ranging from 0.727 up to 0.909 for aggressive driving recognition rate. The obtained results lend support to the hypothesis that user’s environment and activity data could be used for the prediction of the aggressive driving style in advance, before the driving starts.
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