Abstract
In this paper we present the usage of neural networks and hidden markov models for learning driving patterns. We used neural networks for short-term prediction of lateral and longitudinal vehicle acceleration. For long- time prediction, hidden markov models provide recognition of individual driving events. The experiments performed showed that both techniques are very reliable. Recognition rate for driving events is above 98% and prediction error for events in the near future is very low. Predicted events will be used to support drivers in solving guidance navigation tasks.
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© 2001 Springer-Verlag Berlin Heidelberg
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Mitrovic, D. (2001). Machine Learning for Car Navigation. In: Monostori, L., Váncza, J., Ali, M. (eds) Engineering of Intelligent Systems. IEA/AIE 2001. Lecture Notes in Computer Science(), vol 2070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45517-5_74
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DOI: https://doi.org/10.1007/3-540-45517-5_74
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Online ISBN: 978-3-540-45517-2
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