Abstract: Real state information, which influences the switching times of a light signal system, is supplied as input signals to a first neural network in a fixed time cycle. The first neural network calculates estimated state information as a replacement for real state information or parts of the real state information which are not received in good time or are received incorrectly in the fixed time cycle. This estimated state information is output to artificial intelligence which predicts the switching times. The first neural network allows the artificial intelligence to also make good predictions for the switching times of signal groups when one of the many communication paths involved fails or is overloaded. It is therefore possible to predict signal group states in the fixed time cycle in real time with a high degree of robustness and tolerance with respect to gaps in the time cycle of the real state information provided.

Abstract: A method for predicting a remaining time of a signal phase includes capturing traffic data and a signal phase specification distinguishing different signal phases of a traffic signal generator. The traffic data is fed as input data to an artificial neural network including first and second sub-networks and a combination network for combining output data of the two sub-networks. The artificial neural network is trained to reproduce a time still remaining until a phase change of the traffic signal generator based on the traffic data. Outputting of the output data of the first and second sub-networks is controlled in a manner complementary to one another according to the signal phase specification. Lastly, the output data of the combination network or the prediction data derived therefrom are transmitted to a transport device or to a road user as a prediction of the time remaining for influencing traffic.

Abstract: In a toll system for paying a fee for allowing a vehicle to use a road network, a random generator generates a random character string and transmits it to an electronic payment system and to a monitoring device for an on-road check on a usage authorization of vehicles using the road network. A user registers with the payment system in order to acquire a usage authorization and inputs a registration number of the vehicle intended for use. The payment system generates a hash value and transmits it to an electronic operator system of a toll operator. The monitoring device records a registration number of the vehicle and generates the hash value from the registration number and the currently valid character string. The operator system checks whether the hash value from the monitoring device matches a hash value from the payment system.

Abstract: A method predicts a switch state and/or a switch time point of a signaling system. The method includes collecting first and second state data, the first and second state data influencing the switch state and/or switch time point. The collection of the first state data includes reading of state data from a signaling system control device of the signaling system by a signaling system interface. The collection of the second state data includes reading in of the state data. A prediction model is provided and configured to make a prediction of the switch time point and/or the switch state of the signaling system based on first and second state data. The switch state and/or the switch time point of the signaling system is predicted via the prediction model using the first and second state data. The predicted switch state and/or switch time point of the signaling system is outputted.

Abstract: A computer-implemented method for determining at least one remaining time value, to be determined, for a system is provided, having the following steps: a. providing at least one known input data record containing a multiplicity of input elements for at least one determined time; b. providing at least one associated known remaining time value for the at least one input data record; c. determining the at least one remaining time value to be determined by applying an error function to the at least one input data record and the at least one associated remaining time value; and d. providing an output data record containing the at least one determined remaining time value and an associated reliability value. The invention furthermore targets a corresponding determination unit and computer program product.

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.