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Truck identification using New Jersey weigh in motion data
Descriptive
TitleInfo
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Title
Truck identification using New Jersey weigh in motion data
Name
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Donaiah
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Amrutha
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Amrutha Donaiah
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author
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Hani
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Advisory Committee
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Hani H Nassif
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chair
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Husam
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Advisory Committee
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Husam S Najm
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internal member
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Ozbay
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Kaan
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Advisory Committee
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Kaan Ozbay
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internal member
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Rutgers University
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degree grantor
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Graduate School - New Brunswick
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school
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Text
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theses
OriginInfo
DateCreated
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2008
DateOther
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2008-05
Language
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English
PhysicalDescription
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electronic
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application/pdf
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text/xml
Extent
xiii, 135 pages
Abstract
An algorithm for truck identification based on the truck's axle configuration, arrival time, and gross vehicle weight is proposed. The algorithm is applied between WIM Stations and can further be modified for use in Origin-Destination (O-D) studies for New Jersey State. Truck Origin-Destination study is necessary in order to find out if the roads are being used by local state trucks, or by trucks traveling from out of the state. Truck volumes have incomparably increased since past years in the State of NJ reducing the level of safety of pavement structures and highway bridges.
An extensive database of WIM data was collected from more than 50 fixed stations throughout the State of NJ. The WIM data collected includes gross weight, axle weights, axle spacings, number of axles, speed, length of the vehicle, vehicle classification and counts, lane, date and time of passage and ESAL's to evaluate truck loading. Truck volumes are highly site specific, depending upon the type of highway and its functionality. Based on the truck's axle spacings, arrival time, and gross vehicle weight, an algorithm is written for monitoring its presence at various WIM Stations. The effect of Weight calibration and other factors on WIM accuracy, and thus on truck identification, are studied. The algorithm was further validated by Spot checking WIM data for the truck presence between stations. Based on the results of this study, it can be concluded that the method followed for truck identification is reliable when applied to stations having accuracy in terms of installation and calibration.
However, a rational approach to the whole process of truck identification between WIM stations and O-D study is provided if visual identification systems, like license plate readers, are also adopted as a supplement with WIM data.
An extensive database of WIM data was collected from more than 50 fixed stations throughout the State of NJ. The WIM data collected includes gross weight, axle weights, axle spacings, number of axles, speed, length of the vehicle, vehicle classification and counts, lane, date and time of passage and ESAL's to evaluate truck loading. Truck volumes are highly site specific, depending upon the type of highway and its functionality. Based on the truck's axle spacings, arrival time, and gross vehicle weight, an algorithm is written for monitoring its presence at various WIM Stations. The effect of Weight calibration and other factors on WIM accuracy, and thus on truck identification, are studied. The algorithm was further validated by Spot checking WIM data for the truck presence between stations. Based on the results of this study, it can be concluded that the method followed for truck identification is reliable when applied to stations having accuracy in terms of installation and calibration.
However, a rational approach to the whole process of truck identification between WIM stations and O-D study is provided if visual identification systems, like license plate readers, are also adopted as a supplement with WIM data.
Note
(type = degree)
M.S.
Note
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Includes bibliographical references (p. 103-104).
Subject
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Topic
Civil and Environmental Engineering
Subject
(authority = ETD-LCSH)
Topic
Trucking--New Jersey
Subject
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Topic
Trucks--Identification
Subject
(authority = ETD-LCSH)
Topic
Traffic surveys--New Jersey--Data processing
Subject
HierarchicalGeographic
Country
UNITED STATES
State
New Jersey
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Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Identifier
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http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17302
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ETD_983
Identifier
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doi:10.7282/T39G5N5Q
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NjNbRU
Subject
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Geographic
New Jersey
Genre
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ETD graduate
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Rights
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The author owns the copyright to this work.
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Copyright protected
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Open
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Name
Amrutha Donaiah
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Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
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Non-exclusive ETD license
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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