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Accession Number
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PB2013-104738
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Title
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Monitoring the Use of HOV and HOT Lanes.
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Publication Date
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Jan 2013
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Media Count
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26p
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Personal Author
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E. Holec G. Somasundaram N. Papanikolopoulos V. Morellas
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Abstract
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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.
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Keywords
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High occupancy vehicle lanes
High occupancy vehicles
High-occupany toll lanes
Infrared detectors
Monitoring
Traffic counting
Vehicle occupants
Vehicles
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Source Agency
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Department of Transportation Office of University Research
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NTIS Subject Category
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85H - Road Transportation
91B - Transportation & Traffic Planning
43G - Transportation
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Corporate Author
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Minnesota Univ., Minneapolis. Dept. of Mechanical Engineering.
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Document Type
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Technical report
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Title Note
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N/A
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NTIS Issue Number
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1310
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Contract Number
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N/A
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