Abstract: Movement data of a plurality of positions on an observation object performing a predetermined movement action is acquired, feature data is generated by performing frequency analysis on the movement data, a transition sequence of a primitive action is extracted by segmenting the feature data, and based on the transition sequence and an action model obtained by learning a transition sequence of a primitive action obtained by segmenting a movement state of a training object performing a movement action, an occurrence rate of the primitive action in the predetermined movement action is analyzed to extract a pattern of the primitive action, thereby predicting an end timing of the predetermined movement action.

Abstract: In an abnormal driving behavior detection system for a vehicle, an obtainer repeatedly obtains an observed value indicative of at least one of a running condition of the vehicle and a driver's driving operation of the vehicle. A mode-probability calculator calculates, each time an observed value is obtained at a given obtaining timing as a target obtained value, a mode probability for each of driving modes as a function of one or more previous observed values. A deviation calculator obtains a predicted observed value for each driving mode using a driver's normal behavior model defined therefor, and calculates a deviation of the target observed value from the predicted observed value for each driving mode. An abnormality determiner determines whether there is at least one driver's abnormal behavior based on the mode probability for each driving mode and the deviation calculated for each driving mode.

Abstract: In an abnormal driving behavior detection system for a vehicle, an obtainer repeatedly obtains an observed value indicative of at least one of a running condition of the vehicle and a driver's driving operation of the vehicle. A mode-probability calculator calculates, each time an observed value is obtained at a given obtaining timing as a target obtained value, a mode probability for each of driving modes as a function of one or more previous observed values. A deviation calculator obtains a predicted observed value for each driving mode using a driver's normal behavior model defined therefor, and calculates a deviation of the target observed value from the predicted observed value for each driving mode. An abnormality determiner determines whether there is at least one driver's abnormal behavior based on the mode probability for each driving mode and the deviation calculated for each driving mode.