Travel time prediction using machine learning

This paper investigates the application of a Machine Learning technique to predict the time that will be spent by a vehicle between any two points in an approximated area. The prediction is based on a learning process based on historical data about the movements performed by the vehicles taking into account a set of semantic variables to get estimated time accurately. The paper also describes an experiment with real-world data. Although this is preliminary work, the results were satisfactory.

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