A computer implemented method of creating data for a host vehicle simulation for training an autonomous driving system, comprising: in each of a plurality of iterations of a host vehicle simulation engine , using at least one processor for: obtaining from an environment simulation engine a semantic-data dataset representing a plurality of scene objects in a geographical area, each of said plurality of scene objects comprising at least object location coordinates and a plurality of values of semantically described parameters for each of said plurality of scene objects; placing said plurality of scene objects in a virtual three dimensional visual realistic scene created for emulating said plurality of scene objects in said geographical area according to said semantic-data dataset and based on synthetic 3D imaging data generated from a virtual realistic model created using visual imagery data of said geographical area; creating sensory ranging data simulation for said geographical area by applying to the virtual 3D visual realistic scene at least one noise pattern including at least one noise effect induced by at least one of said plurality of scene objects, said at least one noise pattern is associated with at least one sensor of a vehicle simulated in said virtual 3D visual realistic scene by said host vehicle simulation engine ; converting said sensory ranging data simulation to an enhanced semantic-data dataset emulating said geographical area, said enhanced semantic-data dataset comprising a plurality of enhanced scene objects having object location coordinates adjusted when said at least one noise pattern has been applied and a plurality of values of respective said semantically described parameters adapted when said at least one noise pattern has been applied; and providing said enhanced semantic-data dataset to said host vehicle simulation engine which updates said simulation of said vehicle in said virtual 3D visual realistic scene of said geographical area. obtaining from an environment simulation engine a semantic-data dataset representing a plurality of scene objects in a geographical area, each of said plurality of scene objects comprising at least object location coordinates and a plurality of values of semantically described parameters for each of said plurality of scene objects; placing said plurality of scene objects in a virtual three dimensional visual realistic scene created for emulating said plurality of scene objects in said geographical area according to said semantic-data dataset and based on synthetic 3D imaging data generated from a virtual realistic model created using visual imagery data of said geographical area; creating sensory ranging data simulation for said geographical area by applying to the virtual 3D visual realistic scene at least one noise pattern including at least one noise effect induced by at least one of said plurality of scene objects, said at least one noise pattern is associated with at least one sensor of a vehicle simulated in said virtual 3D visual realistic scene by said host vehicle simulation engine ; converting said sensory ranging data simulation to an enhanced semantic-data dataset emulating said geographical area, said enhanced semantic-data dataset comprising a plurality of enhanced scene objects having object location coordinates adjusted when said at least one noise pattern has been applied and a plurality of values of respective said semantically described parameters adapted when said at least one noise pattern has been applied; and providing said enhanced semantic-data dataset to said host vehicle simulation engine which updates said simulation of said vehicle in said virtual 3D visual realistic scene of said geographical area. <EOS>