This paper presents an application of diagnosis methods to the driver-vehicle-environment system. The study aims at characterizing the driving environment on the basis of data collected on the vehicle. 14 candidates drove on a driving simulator through 4 different driving situations: driving on a motorway with a dense traffic, driving on an A road with a dense traffic, driving on a motorway with a light traffic and driving on an A road with a light traffic. Multiple correspondence analysis (MCA) was used because it could provide a diagnosis without requiring a model of the studied system. Because MCA doesn't allow automated data classification, this first analysis is followed by a discriminant analysis, which provides 97% of well diagnosed driving situations. Finally, prospects that could enhance the diagnosis reliability are exposed.
Driver's environment identification using automatic classification methods. Active safety application
Intelligent Vehicle Symposium, 2002. IEEE ; 2 ; 292-297 vol.2
2002-01-01
383648 byte
Conference paper
Electronic Resource
English
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