A method of generating and updating a precision road property database comprising driving-relevant objects by a two-step object data processing comprising a first step of object data processing by one or more vehicles and a second step of object data processing by a server database, the server database storing fourth data sets comprising driving-relevant object data, the driving-relevant object data further comprising at least location information and detailed object-based information about at least one of a road object (310, 311), a road furniture object (370, 371, 372), a geographic object or a further object related to driving, the server data base collecting third data sets from the one or more vehicles and evaluating the third data sets to generate fourth data sets in order to build up confidence in the fourth data sets, the method comprising: for each of the one or more vehicles performing the steps of: a) a vehicle requesting information about an area of interest or an area from the server database, or the server database triggering a data transfer, b) the server database generating at least one first data set related to the request or trigger from fourth data sets stored in the server database, each first data set comprising driving-relevant object data, c) the server database forwarding the at least one first data set to the vehicle which stores the first data sets in a vehicle database, wherein the at least one first data set further comprises auxiliary data comprising at least one of a confidence level or a standard deviation parameter of the at least one first data set, d) the vehicle collecting at least one ambient data set along at least a specific section of its path, the ambient data sets relating to at least one of driving-relevant objects, road furniture and geographic objects, wherein the vehicle selects the at least one specific section of the path based on the auxiliary data to cover sections of the path having data with at least one of a low confidence level, a large standard deviation or no data, e) the vehicle performing the first step of object data processing by evaluating the at least one ambient data sets and generating at least one second data set based on the evaluation result, each second data set comprising driving-relevant object data, f) the vehicle generating third data sets containing differences between the object-based information of the second data sets and the object-based information of the first data sets, g) the vehicle forwarding the third data sets to the server database, h) the server database storing a selection of the third data sets, i) the server database performing the second step of object data processing comprising at least statistical evaluation and post processing of the selected third data sets and the fourth data sets by the server database to determine the confidence level or the standard deviation parameter of the fourth data sets, and j) the server database updating of the fourth data sets in the server database based on the third data sets. a) a vehicle requesting information about an area of interest or an area from the server database, or the server database triggering a data transfer, b) the server database generating at least one first data set related to the request or trigger from fourth data sets stored in the server database, each first data set comprising driving-relevant object data, c) the server database forwarding the at least one first data set to the vehicle which stores the first data sets in a vehicle database, wherein the at least one first data set further comprises auxiliary data comprising at least one of a confidence level or a standard deviation parameter of the at least one first data set, d) the vehicle collecting at least one ambient data set along at least a specific section of its path, the ambient data sets relating to at least one of driving-relevant objects, road furniture and geographic objects, wherein the vehicle selects the at least one specific section of the path based on the auxiliary data to cover sections of the path having data with at least one of a low confidence level, a large standard deviation or no data, e) the vehicle performing the first step of object data processing by evaluating the at least one ambient data sets and generating at least one second data set based on the evaluation result, each second data set comprising driving-relevant object data, f) the vehicle generating third data sets containing differences between the object-based information of the second data sets and the object-based information of the first data sets, g) the vehicle forwarding the third data sets to the server database, h) the server database storing a selection of the third data sets, i) the server database performing the second step of object data processing comprising at least statistical evaluation and post processing of the selected third data sets and the fourth data sets by the server database to determine the confidence level or the standard deviation parameter of the fourth data sets, and j) the server database updating of the fourth data sets in the server database based on the third data sets.