A computer implemented method is for determining railway vehicle movement profile type of a railway vehicle movement profile. The railway vehicle movement profile includes a sequence of measured transmitted currents of a transceiver of a track circuit with respect to the time. The method includes obtaining a railway vehicle movement profile, normalizing the railway vehicle movement profile, extracting one or more features from the normalized railway vehicle movement profile, determining the distance of the extracted features with respect to each centroid of a railway vehicle movement profile type determined in a classification process, and assigning the railway vehicle movement profile to the railway vehicle movement profile type with the closest centroid

A method is provided for communicating at least one item of information between a first control unit on-board a first vehicle and a public transport network. The information is sent as a command from the first control unit to a first communication unit on board the first vehicle. The first communication unit establishes a transmission link outside the vehicle with a second communication unit connected to a module for executing the command. The second communication unit and the execution module are located on the ground. The first control unit controls the execution module on the ground in a governed slave mode for the command by a master mode of the first control unit.

A method is provided for communicating at least one item of information between a first control unit on-board a first vehicle and a public transport network. The information is sent as a command from the first control unit to a first communication unit on board the first vehicle. The first communication unit establishes a transmission link outside the vehicle with a second communication unit connected to a module for executing the command. The second communication unit and the execution module are located on the ground. The first control unit controls the execution module on the ground in a governed slave mode for the command by a master mode of the first control unit.

An improved safety system used to determine the present position of a car riding on railroad tracks that provides data to control signals, such as flashing lights, and crossing gates at railroad grade crossings in order to prevent accidents with vehicles or persons.

An improved safety system used to determine the present position of a car riding on railroad tracks that provides data to control signals, such as flashing lights, and crossing gates at railroad grade crossings in order to prevent accidents with vehicles or persons.

Examples of techniques for anomaly detection in a grade crossing prediction system are disclosed. Aspects include receiving a training data set comprising a plurality of labelled time series of signal values from a track circuit in a grade crossing predictor system, removing one or more non-unique values from each labelled time series of signal values in the plurality of labelled time series of signal values, extracting a plurality of features from the plurality of labelled time series of signal values, the plurality of features comprising: a number of signal values for each labeled time series of signal values in the plurality of labelled time series of signal values that are larger than a first threshold and a standard deviation for each labelled time series of signal values in the plurality of labelled time series of signal values, and training a machine learning algorithm utilizing the plurality of features.

Examples of techniques for anomaly detection in a grade crossing prediction system are disclosed. Aspects include receiving a training data set comprising a plurality of labelled time series of signal values from a track circuit in a grade crossing predictor system, removing one or more non-unique values from each labelled time series of signal values in the plurality of labelled time series of signal values, extracting a plurality of features from the plurality of labelled time series of signal values, the plurality of features comprising: a number of signal values for each labeled time series of signal values in the plurality of labelled time series of signal values that are larger than a first threshold and a standard deviation for each labelled time series of signal values in the plurality of labelled time series of signal values, and training a machine learning algorithm utilizing the plurality of features.

Examples of techniques for anomaly detection in a grade crossing prediction system are disclosed. Aspects include receiving a training data set comprising a plurality of labelled time series of signal values from a track circuit in a grade crossing predictor system, removing one or more non-unique values from each labelled time series of signal values in the plurality of labelled time series of signal values, extracting a plurality of features from the plurality of labelled time series of signal values, the plurality of features comprising: a number of signal values for each labeled time series of signal values in the plurality of labelled time series of signal values that are larger than a first threshold and a standard deviation for each labelled time series of signal values in the plurality of labelled time series of signal values, and training a machine learning algorithm utilizing the plurality of features.

A safety method for a railway network that is divided into section segments by way of section elements and which can be traveled by vehicles in accordance with data from a section atlas. The vehicles request steps for allocation as a track element from selected section elements. Each of the selected section elements autonomously allocates itself as a track element under specified conditions for each requesting vehicle. In order to be able to inform the vehicle or the vehicle operators thereof about changed section characteristics better and more quickly, for the section elements, the vehicles store manually entered and/or manually released dynamic driving operation data as a dynamic component of the section atlas in parts related to the section elements.

A safety method for a railway network that is divided into section segments by way of section elements and which can be traveled by vehicles in accordance with data from a section atlas. The vehicles request steps for allocation as a track element from selected section elements. Each of the selected section elements autonomously allocates itself as a track element under specified conditions for each requesting vehicle. In order to be able to inform the vehicle or the vehicle operators thereof about changed section characteristics better and more quickly, for the section elements, the vehicles store manually entered and/or manually released dynamic driving operation data as a dynamic component of the section atlas in parts related to the section elements.