Feature analysis of acceleration and deceleration behavior during hurry driving using driving behavior model based on hierarchical Bayesian approach

Existing driver assistance systems are based on averaged characteristics of drivers so the systems may cause a 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 longitudinal hurry driving using hierarchical Bayesian model. Urban driving data are collected by a continuous-logging drive recorder (DR). The system using Hierarchical Bayesian method has extracted feature of hurry driving behavior appropriately. These features were different of individual drivers. The probability of hurry driving state is detected by using this hierarchical Bayesian model.