A novel multidisciplinary system for the automatic driving risk level classification is presented. The data considered involves the three basic traffic safety elements (driver, road, and vehicle), as well as knowledge from traffic experts. The driving experiments were conducted in a truck cabin simulator handled by a professional driver, considering the most common real-world enviroments. Each traffic expert evaluate the driving risk on a 0 to 100 visual analogue scale. The driver, road and vehicle information was used to train five different data mining algorithms in order to predict the driving risk level. The benefits of the completeness of the data considered in our system are presented and discussed.
Driving risk classification based on experts evaluation
2010 IEEE Intelligent Vehicles Symposium ; 1098-1103
01.06.2010
1482161 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Driving Risk Classification Based on Experts Evaluation, pp. 1098-1103
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