A train control system (100) uses machine learning for implementing handovers between centralized and distributed train control models. A machine learning engine receives training data from a data acquisition hub (312), receives a centralized train control model from a centralized virtual system modeling engine, and receives an edge-based train control model from an edge-based virtual system modeling engine (324). The machine learning engine trains a learning system using the training data to enable the machine learning engine to predict when a locomotive (108, 110) of the train (102) will enter a geo-fence where communication between the edge-based computer processing system and the centralized computer processing system will be inhibited.
Train control with centralized and edge processing handovers
15.09.2022
Patent
Elektronische Ressource
Englisch
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