Abstract
This paper uses inductive logic programming (ILP) to identify a driver’s cognitive state in real driving situations to determine whether a driver will be ready to select a suitable operation and recommended service in the next generation car navigation systems. We measure the driver’s eye movement and collect various data such as braking, acceleration and steering angles that are qualitatively interpreted and represented as background knowledge. A set of data about the driver’s degree of tension or relaxation regarded as a training set is obtained from the driver’s mental load based on resource-limited cognitive process analysis. Given such information, our ILP system has successfully produced logic rules that are qualitatively understandable for rule verification and are actively employed for user-oriented interface design. Realistic experiments were conducted to demonstrate the learning performance of this approach. Reasonable accuracy was achieved for an appropriate service providing safe driving.
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Mizoguchi, F., Ohwada, H., Nishiyama, H., Iwasaki, H. (2013). Identifying Driver’s Cognitive Load Using Inductive Logic Programming. In: Riguzzi, F., Železný, F. (eds) Inductive Logic Programming. ILP 2012. Lecture Notes in Computer Science(), vol 7842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38812-5_12
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DOI: https://doi.org/10.1007/978-3-642-38812-5_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38811-8
Online ISBN: 978-3-642-38812-5
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