Abstract: To track the path of moving objects without using object-identifying information, e.g. GPS information of the object or other individual identifiers by means which an object can be basically identified, or if the objects continue to change their respective identity, it is proposed how a statement can be made about the successful tracking with respect to at least some of the object group along the tracking route on the basis of the acquisition of information, taking place along a tracking route repeatedly with non-object-identifying parameter data which is emitted by the moving objects, at regular time intervals, by object-group-specific considerations of the acquired parameter data, of group-specific data profiles, acquired from these considerations, and a data profile similarity comparison, and tracking information is generated, and otherwise no such statement is possible and the generation of the tracking information does not occur.

Abstract: A system and method are for determining a vehicle speed. In an embodiment, the system includes a first collecting module, adapted to collect traffic information; and a deep learning module, including a control model and a neural network. The control model is generated after the neural network autonomously deeply learns based on inputted traffic information. The control model is adapted to receive current traffic information including a speed and a location of a vehicle, traffic light status at a junction ahead, and traffic condition information in a road segment ahead currently collected by the first collecting module; to compute a recommended vehicle speed for the vehicle based on the current traffic information; and to output the recommended vehicle speed. Such a system may reduce the stopping times at the intersection.

Abstract: A system supports a traffic participant while predicting a future signaling of a traffic infrastructure element. The system contains a storage device in which artificial intelligence is stored, wherein the artificial intelligence includes a predictive model for predicting a future signaling of the traffic infrastructure element, and a communication device for transmitting the artificial intelligence to a traffic participant via a communication network.