Abstract
The goal of this paper is to apply some of the best-known machine learning techniques to a practical problem in the automotive field: the identification and classification of the user’s intentions in performing specific driving maneuvers. Data have been collected by a static driving simulator. These models are then analyzed and compared, in order to select the best car-following maneuver classifier.
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Tango, F., Botta, M. (2009). ML Techniques for the Classification of Car-Following Maneuver. In: Serra, R., Cucchiara, R. (eds) AI*IA 2009: Emergent Perspectives in Artificial Intelligence. AI*IA 2009. Lecture Notes in Computer Science(), vol 5883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10291-2_40
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DOI: https://doi.org/10.1007/978-3-642-10291-2_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10290-5
Online ISBN: 978-3-642-10291-2
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