System for locating the position of at least one road object associated with a portion of a road network, the system comprising a road information receiving unit, a road information processing unit and a computing unit: • the road information receiving unit is configured to receive a plurality of geolocated road information items which relate to the road object, the plurality of road information items being obtained from at least one sensor associated with each one of a plurality of road vehicles, • the road information processing unit is configured to identify the type of the road object from the plurality of road information items and to calculate a plurality of geographic coordinates associated with the road object, each geographic coordinate being calculated from the plurality of road information items associated with one of the plurality of road vehicles, • the computing unit characterized by being configured to: - create, in a first creation step, for each type of road object, a first characteristic vector comprising the type of the road object and the associated plurality of geographic coordinates, - partition, in a first partitioning step, on the basis of an unsupervised classification algorithm based on distribution density, at least a portion of the set of first characteristic vectors into a plurality of classes, and the computing unit being further configured, for each class determined in the partitioning step, to: • create, in a second creation step, a second characteristic vector comprising at least one component for each geographic coordinate of the class, each component being representative of an azimuth angle of a direction of observation of the road object associated with the corresponding geographic coordinate, • partition, in a second partitioning step, on the basis of the unsupervised classification algorithm based on distribution density, at least a portion of the set of second characteristic vectors into a plurality of subclasses, and • calculate, in the calculating step, for each subclass, at least one measure of central tendency from the geographic coordinates associated with the subclass, the measure of central tendency being representative of the position of the road object in a direction of observation of the road object. • the road information receiving unit is configured to receive a plurality of geolocated road information items which relate to the road object, the plurality of road information items being obtained from at least one sensor associated with each one of a plurality of road vehicles, • the road information processing unit is configured to identify the type of the road object from the plurality of road information items and to calculate a plurality of geographic coordinates associated with the road object, each geographic coordinate being calculated from the plurality of road information items associated with one of the plurality of road vehicles, • the computing unit characterized by being configured to: - create, in a first creation step, for each type of road object, a first characteristic vector comprising the type of the road object and the associated plurality of geographic coordinates, - partition, in a first partitioning step, on the basis of an unsupervised classification algorithm based on distribution density, at least a portion of the set of first characteristic vectors into a plurality of classes, and - create, in a first creation step, for each type of road object, a first characteristic vector comprising the type of the road object and the associated plurality of geographic coordinates, - partition, in a first partitioning step, on the basis of an unsupervised classification algorithm based on distribution density, at least a portion of the set of first characteristic vectors into a plurality of classes, and • create, in a second creation step, a second characteristic vector comprising at least one component for each geographic coordinate of the class, each component being representative of an azimuth angle of a direction of observation of the road object associated with the corresponding geographic coordinate, • partition, in a second partitioning step, on the basis of the unsupervised classification algorithm based on distribution density, at least a portion of the set of second characteristic vectors into a plurality of subclasses, and • calculate, in the calculating step, for each subclass, at least one measure of central tendency from the geographic coordinates associated with the subclass, the measure of central tendency being representative of the position of the road object in a direction of observation of the road object.