| 摘要 |
PURPOSE:To estimate the road surface frictional. coefficient which can not be measured directly, with high precision, by detecting the vehicle traveling state and inputting the state to a neural network, as for a road surface frictional coefficient estimating device during the traveling of a vehicle. CONSTITUTION:Into a controller 2, each information representing the traveling state is supplied from a steering angle sensor 21, car speed sensor 22, yaw rate sensor 23, lateral slip angle sensor 24, and a rear wheel steering angle sensor 25. The controller reads these information in each prescribed interruption timing by using a microcomputer and executes the calculation processing based on the neural network, and calculates the road surface frictional efficient. The neural network allows plural numerical values to be outputted in parallel, and consists of the equal number of elements to a plurality of outputs, and learning is carried out, having the numerical series set in the pattern corresponding to the well-know road surface frictional coefficient, as learning signal, and calculation processing is carried out. |
