Ford Global Technolgoies, LLC

Eduardo Perez Guzman

Daniel Roettger

Christian Winge Vigild

Frederik De Smet

Turgay Isik Aslandere

A simulation includes loading a first generator of a Cycle Generative Adversarial Network (CycleGAN) with a model dataset during a training phase in order to train the first generator in cooperation with a first discriminator of the CycleGAN assigned to the first generator, and loading a second generator of the CycleGAN with a hardware dataset in order to train the second generator in cooperation with a second discriminator of the CycleGAN assigned to the second generator, and loading the first generator with an input dataset during an operational phase in order to provide an output dataset.

Method and system for carrying out a simulation

A method for predicting travel of a vehicle includes determining a prediction starting location and a plurality of prediction destinations including a plurality of possible intersections within a boundary at a predefined distance from the starting location. The method also includes determining, for each destination, at least one route to the destination, resulting in a plurality of routes at least one of which corresponds to each destination, including determining a statistical likelihood of the vehicle remaining on an intersection-exit that is along a potential route and selecting at least one route to each destination with the highest statistical likelihood. Responsive to the vehicle no longer being on a selected route, selecting at least one new route to the at least one destination.

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Aachen, Germany

Eduardo Perez Guzman