Toward Modeling And Classification Of Naturalistic Driving

Intelligent systems in automobiles need to be aware of the driving and driver context. Available sensor data streams have to be modeled and monitored in order to do so. We describe a machine learning approach to accomplish this through collecting a large database of naturalistic driving data in a driving simulator. Preliminary experiments with a smaller dataset indicate successful modeling of naturalistic driving with hierarchical sequential models such as Hidden Markov Models.