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Accession Number PB2013-104738
Title Monitoring the Use of HOV and HOT Lanes.
Publication Date Jan 2013
Media Count 26p
Personal Author E. Holec G. Somasundaram N. Papanikolopoulos V. Morellas
Abstract This report presents the formulation and implementation of an automated computer vision and machine learning based system for estimation of the occupancy of passenger vehicles in high-occupancy vehicles and highoccupancy toll (HOV/HOT) lanes. We employ a multi-modal approach involving near-infrared images and highresolution color video images in conjunction with strong maximum margin based classifiers such as support vector machines. We attempt to maximize the information that can be extracted from these two types of images by computing different features. Then, we build classifiers for each type of feature which are compared to determine the best feature for each imaging method. Based on the performance of the classifiers we critique the efficacy of the individual approaches as the costs involved are significantly different.
Keywords High occupancy vehicle lanes
High occupancy vehicles
High-occupany toll lanes
Infrared detectors
Traffic counting
Vehicle occupants

Source Agency Department of Transportation Office of University Research
NTIS Subject Category 85H - Road Transportation
91B - Transportation & Traffic Planning
43G - Transportation
Corporate Author Minnesota Univ., Minneapolis. Dept. of Mechanical Engineering.
Document Type Technical report
Title Note N/A
NTIS Issue Number 1310
Contract Number N/A

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