DocumentCode :
2641471
Title :
Sensor selection for maneuver classification
Author :
Torkkola, Kari ; Venkatesan, Srihari ; Liu, Huan
Author_Institution :
Motorola Labs., Tempe, AZ, USA
fYear :
2004
fDate :
3-6 Oct. 2004
Firstpage :
636
Lastpage :
641
Abstract :
To determine when to present information from various devices or services to the driver of an automobile, it is necessary to determine whether a driver is engaged in a difficult driving situation that requires extensive attention. We present simulator experiments in determining which sensors make the classification of driving states into such maneuvers possible, using various machine learning techniques. Our findings indicate that a small number of derived sensor signals can accomplish the task.
Keywords :
automobiles; driver information systems; feature extraction; learning (artificial intelligence); pattern classification; sensors; automobile drivers; difficult driving situation; driving state classification; feature extraction; machine learning techniques; maneuver classification; sensor selection; sensor signals; Automobiles; Cellular phones; Computer displays; Delay; Machine learning; Page description languages; Timing; Two dimensional displays; Vehicle driving; Voice mail;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems, 2004. Proceedings. The 7th International IEEE Conference on
Print_ISBN :
0-7803-8500-4
Type :
conf
DOI :
10.1109/ITSC.2004.1398975
Filename :
1398975
Link To Document :
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