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In Japan, the number of occupant fatalities has decreased at high ratio due to the development of passive and active safety technology in recent years. However, the pedestrian fatality is still the major proportion of fatalities according to the statistics of traffic accident. Therefore, it is important to study and develop active safety technologies which target to pedestrian. By analyzing the traffic accident statistics, narrow road in urban area is one of the dangerous parts for pedestrian. And the dangerous case that pedestrian often gets into an accident is while crossing road outside of crosswalk. This study focuses on accidents which are caused by pedestrians suddenly crossing narrow urban roads. In such cases, drivers need to drive carefully, preparing for sudden crossing or unexpected dangerous behavior of pedestrians. Therefore, it is important for drivers to predict the accident risk due to the crossing pedestrian behavior in such narrow roads.

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.