A computer implemented method of creating a virtual three dimensional realistic model of a geographical area for training an autonomous driving system, comprising: obtaining geographic map data of a geographical area; obtaining visual imagery data of the geographical area; classifying a plurality of static objects identified in the visual imagery data to corresponding labels to designate a plurality of labeled objects; superimposing the plurality of labeled objects over the geographic map data; generating a virtual three dimensional realistic model emulating the geographical area by synthesizing a corresponding visual texture for each of the plurality of labeled objects; injecting synthetic 3D imaging feed of the virtual 3D realistic model to an input of at least one imaging sensor of the autonomous driving system, the autonomous driving system controlling movement of an emulated vehicle in the virtual 3D realistic model, the synthetic 3D imaging feed is generated to depict the virtual 3D realistic model from a point of view of at least one emulated imaging sensor mounted on the emulated vehicle; characterized by: inserting at least one simulated ground vehicle into the virtual 3D realistic model; and applying at least one of a plurality of driver behavior classes for controlling a movement of the at least one simulated ground vehicle, the at least one driver behavior class is adapted to the geographical area according to an analysis of typical driver behavior patterns identified in the geographical area, the at least one driver behavior class is selected according to a density function calculated for the geographical area according to recurrence of drivers prototype corresponding to the at least one driver behavior classes in the geographical area. obtaining geographic map data of a geographical area; obtaining visual imagery data of the geographical area; classifying a plurality of static objects identified in the visual imagery data to corresponding labels to designate a plurality of labeled objects; superimposing the plurality of labeled objects over the geographic map data; generating a virtual three dimensional realistic model emulating the geographical area by synthesizing a corresponding visual texture for each of the plurality of labeled objects; injecting synthetic 3D imaging feed of the virtual 3D realistic model to an input of at least one imaging sensor of the autonomous driving system, the autonomous driving system controlling movement of an emulated vehicle in the virtual 3D realistic model, the synthetic 3D imaging feed is generated to depict the virtual 3D realistic model from a point of view of at least one emulated imaging sensor mounted on the emulated vehicle; characterized by: inserting at least one simulated ground vehicle into the virtual 3D realistic model; and applying at least one of a plurality of driver behavior classes for controlling a movement of the at least one simulated ground vehicle, the at least one driver behavior class is adapted to the geographical area according to an analysis of typical driver behavior patterns identified in the geographical area, the at least one driver behavior class is selected according to a density function calculated for the geographical area according to recurrence of drivers prototype corresponding to the at least one driver behavior classes in the geographical area. inserting at least one simulated ground vehicle into the virtual 3D realistic model; and applying at least one of a plurality of driver behavior classes for controlling a movement of the at least one simulated ground vehicle, the at least one driver behavior class is adapted to the geographical area according to an analysis of typical driver behavior patterns identified in the geographical area, the at least one driver behavior class is selected according to a density function calculated for the geographical area according to recurrence of drivers prototype corresponding to the at least one driver behavior classes in the geographical area.