Method for determining a friction value (μ) of a roadway by means of a data processing device , the method comprising the following steps: providing a data set of friction measurement values (μ) of the roadway, wherein each of the friction measurement values (μ) indicates a coefficient of friction of the roadway at a measurement position (s i ) at a measurement time (t i ); wherein the method furthermore comprises the following steps: modelling a spatial and/or temporal trend of at least one subset of the friction measurement values (μ) with decomposition of each friction measurement value (μ) of the subset into a first component for describing the trend and a second component for describing statistical fluctuations of the friction measurement values (μ); characterized in that the method comprises the following steps: modelling a spatial and temporal relationship between the friction measurement values (μ) of the subset on the basis of a semivariogram, determining a weighting factor (w i ) for each friction measurement value (μ) of the subset of friction measurement values (μ) on the basis of the semivariogram and the spatial and/or temporal trend; wherein each of the weighting factors (w i ) indicates a spatial and/or temporal relationship between the associated friction measurement value (μ) and the friction value (μ); and determining a friction value (μ) for a roadway position (s 0 ) and for a time (t 0 ) with formation of a weighted average value, wherein the weighted average value correlates with a sum of the friction measurement values (μ) - weighted with the respective weighting factors (w i ) - of the subset of friction measurement values (μ). modelling a spatial and/or temporal trend of at least one subset of the friction measurement values (μ) with decomposition of each friction measurement value (μ) of the subset into a first component for describing the trend and a second component for describing statistical fluctuations of the friction measurement values (μ); characterized in that the method comprises the following steps: modelling a spatial and temporal relationship between the friction measurement values (μ) of the subset on the basis of a semivariogram, determining a weighting factor (w i ) for each friction measurement value (μ) of the subset of friction measurement values (μ) on the basis of the semivariogram and the spatial and/or temporal trend; wherein each of the weighting factors (w i ) indicates a spatial and/or temporal relationship between the associated friction measurement value (μ) and the friction value (μ); and determining a friction value (μ) for a roadway position (s 0 ) and for a time (t 0 ) with formation of a weighted average value, wherein the weighted average value correlates with a sum of the friction measurement values (μ) - weighted with the respective weighting factors (w i ) - of the subset of friction measurement values (μ). modelling a spatial and temporal relationship between the friction measurement values (μ) of the subset on the basis of a semivariogram, determining a weighting factor (w i ) for each friction measurement value (μ) of the subset of friction measurement values (μ) on the basis of the semivariogram and the spatial and/or temporal trend; wherein each of the weighting factors (w i ) indicates a spatial and/or temporal relationship between the associated friction measurement value (μ) and the friction value (μ); and determining a friction value (μ) for a roadway position (s 0 ) and for a time (t 0 ) with formation of a weighted average value, wherein the weighted average value correlates with a sum of the friction measurement values (μ) - weighted with the respective weighting factors (w i ) - of the subset of friction measurement values (μ). <EOS>