DocumentCode
2778249
Title
Sensor Selection for Driving State Recognition
Author
Torkkola, Kari ; Gardner, Mike ; Schreiner, Chris ; Zhang, Keshu ; Leivian, Bob ; Summers, John
Author_Institution
Motorola, Tempe
fYear
0
fDate
0-0 0
Firstpage
4734
Lastpage
4739
Abstract
Driver activity recognition in the car cockpit is a necessary component for intelligent driver assistance systems. Since this has to be based on the sensor data stream available from the vehicle, an important question is what sensors are necessary and for which driver activities. We present results of a large-scale sensor selection study with naturalistic driving data looking at driving maneuver classification using ensemble methods.
Keywords
distributed sensors; driver information systems; pattern classification; car cockpit; driver activity recognition; driving maneuver classification; driving state recognition; ensemble methods; intelligent driver assistance systems; large-scale sensor selection; Alarm systems; Context awareness; Context modeling; Intelligent sensors; Intelligent systems; Large-scale systems; Machine learning; Sensor systems; Speech; Vehicle driving;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9490-9
Type
conf
DOI
10.1109/IJCNN.2006.247128
Filename
1716757
Link To Document