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Uniform TitleTruck identification using New Jersey weigh in motion data
NameDonaiah, Amrutha (author), Nassif, Hani (chair), Najm, Husam (internal member), Ozbay, Kaan (internal member), Rutgers University, Graduate School - New Brunswick,
Degree Date2008-05
Date Created2008
SubjectCivil and Environmental Engineering,
Trucking--New Jersey,
Trucks--Identification,
Traffic surveys--New Jersey--Data processing
DescriptionAn 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.
NoteM.S.
NoteIncludes bibliographical references (p. 103-104).
Genretheses
Persistent URLhttp://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17302
LanguageEnglish
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.