Method for determining a road model for the surroundings of a vehicle by means of recursive estimation, each recursion comprising the following steps: using sensors to acquire observation data that characterize the surroundings of the vehicle or the movement thereof; acquiring map data that cartographically characterize the surroundings of the vehicle ; generating a plurality of different suppositions (9-11) for the road model that is to be determined, using a parameterized state function, each of the suppositions (9-11) representing a possible road model for the current recursion step and being characterized by a different association , produced by means of an appropriate parameterization, between the observation data , which are each used as input variables for the state function, and map data ; estimating a confidence value in regard to a predetermined measure of confidence for each of the suppositions (9-11) of the current recursion step by means of a recursive estimation method taking into account at least one supposition from the preceding recursion step as an input variable; selecting , on the basis of the estimated confidence values, one of the suppositions (9-11) as the road model for the surroundings of a vehicle for the current recursion step; characterized by detecting, on the basis of the confidence value distribution, whether, for multiple successive recursion steps, the suppositions with the best confidence values are regularly significantly different from the map data ; and if this is the case, correcting the map data on the basis of the selected road model for this recursion step and/or reporting the obsolescence of the map data to a central infrastructure for providing the map data. using sensors to acquire observation data that characterize the surroundings of the vehicle or the movement thereof; acquiring map data that cartographically characterize the surroundings of the vehicle ; generating a plurality of different suppositions (9-11) for the road model that is to be determined, using a parameterized state function, each of the suppositions (9-11) representing a possible road model for the current recursion step and being characterized by a different association , produced by means of an appropriate parameterization, between the observation data , which are each used as input variables for the state function, and map data ; estimating a confidence value in regard to a predetermined measure of confidence for each of the suppositions (9-11) of the current recursion step by means of a recursive estimation method taking into account at least one supposition from the preceding recursion step as an input variable; selecting , on the basis of the estimated confidence values, one of the suppositions (9-11) as the road model for the surroundings of a vehicle for the current recursion step; characterized by detecting, on the basis of the confidence value distribution, whether, for multiple successive recursion steps, the suppositions with the best confidence values are regularly significantly different from the map data ; and if this is the case, correcting the map data on the basis of the selected road model for this recursion step and/or reporting the obsolescence of the map data to a central infrastructure for providing the map data. <EOS>