| 摘要 |
PROBLEM TO BE SOLVED: To support safe driving by adaptively learning relevance between driving operation of a driver and an external environment corresponding to various state changes in cycle and speed generated to the driver during driving, and by recognizing deviation from an ordinary internal state of the driver. SOLUTION: A correspondence between risk of travel environment recognized in an environment risk recognition part 2 and a characteristic amount of driving operation data quantized by an operation characteristic amount discretization part 5 is learned in a model learning part 6 to obtain a model parameter according to the cycle set by a schedule control part 9. A state estimation part 7 estimates an internal state of the driver from the relevance between the operation characteristic amount and an environment risk level by use of the already learned model parameter by the estimated cycle set by the schedule control part 9. An alarm-support part 8 compares the internal state of the driver and the environment risk level, evaluates whether a vehicle is in an essentially safe or dangerous state, and performs an alarm, the operation support, and the like. COPYRIGHT: (C)2010,JPO&INPIT
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