Abstract: A method for determining a state of a road surface in which, a time-series waveform of tire vibration detected by an acceleration sensor is windowed by a windowing means with a time T and a feature vector Xi in each time window is calculated through the extraction of a time-series waveform of the tire-vibration in each time window. Thereafter, in the calculation of a kernel function KA from the feature vector Xi in each time window and a road surface feature vector YAj that is a feature vector in each time window calculated from a time-series waveform of tire-vibration that has been calculated in advance for each road surface state, the feature vector Xi in each time window and the road-surface feature vector YAj are made to be vibration levels of frequency bands of 500 Hz or greater extracted from the time-series waveform in each time window.

Abstract: A time series waveform of detected vibration of a tire during travel is multiplied by a window function of a prescribed time width and a time series waveform for each time window is extracted to calculate a feature vector from the time series waveform for each time window. Thereafter, when determining the state of the road surface during travel using the feature vector for each time window and road surface models, a plurality of the aforementioned road surface models is constructed depending on the magnitude of a braking/driving force, the braking/driving force acting on the aforementioned tire is estimated, and the state of the road surface is determined using the road surface models, which depend on the aforementioned feature vector and the magnitude of the estimated braking/driving force.

Abstract: In a method for determining a road surface condition, the speed of calculation is improved by applying an appropriate path limitation. To further improve the accuracy of determination, a time-series waveform of tire vibration detected by an acceleration sensor is windowed at time width T by a windowing means, and time-series waveforms of tire vibration in the respective time windows are extracted before feature vectors Xi of the respective time windows are calculated. Then kernel functions KA (X, Y) are calculated from the feature vectors Xi for the respective time windows and road surface feature vectors Yi, which are feature vectors for the respective time windows calculated from time-series waveforms of tire vibration having been determined in advance for distinctive road surface conditions.

Abstract: In order to provide a method for accurately determining the road surface state even when the tire state and external information change, when determining the state of the road surface from the time-varying waveform of vibration of a tire during travel detected by a vibration detection means, in addition to the vibration waveform of the tire, tire state information and external information inputted to the tire are acquired, and a determination parameter for determining the road surface state calculated from the tire vibration waveform is corrected or modified on the basis of the acquired tire state information or external information, and either the road surface state is determined using said corrected or modified determination parameter, or the road surface state is determined from the determination parameter and the state information or external information.