Fundamental Study on Human Model Synthesis Based on Extraction ofAccident Risk Variable and Its State Transition Probability

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This research proposes a theoretical method of by driver-vehicle system model parameter analysis and driving operational behavior analysis especially in drowsiness driving state and inattention states. This research potentially contributes to the further reduction of rear-end collision accidents which accounts for 30% of all accidents in Japan. The following research issues were conducted during the research term:(1) The method to extract driving behavior parameters which relate to the velocity control based on experiments using Driving Simulator and a test car.(2) Public expressway driving data collection between Chofu city and Kawaguchiko town using a number of subject drivers.(3) Drowsiness driving behavior analysis by comparing the driving data with the driver model.(4) Verification of the effectiveness of the drowsiness detection method by comparing with the subjective evaluation results using driver face camera image.The velocity-control driver model used in this study is expressed as a spring-mass-damper system based on risk potential theory.Furthermore, by including the lateral-control driver model, the higher accuracy of drowsiness driving detection can be obtained. The achievement from this researchis expected to be applied to active safety systems to prevent accidents.