Estimation of Hurry Driving Behavior based on Hierarchical Bayesian Model Using Continuous-Logging Drive Recorder

Existing driver assistance systems are based on averaged characteristics of drivers, so the systems may cause sense of discomfort to some drivers and the effectiveness on accident prevention degrades due to low system acceptance. To deal with this issue, an individual adaptive hurry driving detection system is proposed in this research. We proposed the detection method of hurry driving using hierarchical Bayesian model. Urban driving data are collected by a continuous-logging drive recorder (DR). Features of hurry driving behavior extracted by hierarchical Bayesian method. The probability of hurry driving state is estimated by using this model using this model.