Title page for ETD etd-06102012-040235


Type of Document Master's Thesis
Author McCullough, Bernard Curtis
URN etd-06102012-040235
Title A two-point vehicle classification system
Degree Master of Science
Department Civil Engineering
Advisory Committee
Advisor Name Title
Ardekani, Siamak A. Committee Chair
Drew, Donald R. Committee Member
Hobeika, Antoine G. Committee Member
Keywords
  • Vehicles
Date of Defense 1988-02-22
Availability restricted
Abstract
The counting and classification of vehicles is an important part of transportation engineering.

In the past twenty years many automated systems have been developed to accomplish

that labor-intensive task. Unfortunately most of those systems are characterized by

inaccurate detection systems and/or classification method's which result in many classification

errors, thus limiting the accuracy of the system.

This report describes the development of a new vehicle classification program, originally

designed for use in the Two-Point-Time-Ratio method of vehicle classification, which could

greatly improve the accuracy of automated classification systems. The program utilizes data

provided by either vehicle detection sensors, or the program user, to determine the velocity,

number of axles, and axle spacings of a passing vehicle. It then matches the axle numbers

and spacings with one of forty-one possible vehicle classifications and prints the vehicle class,

speed, and wheelbase lengths. It also tabulates and prints totals and average speeds for each

vehicle type.

This report then describes a roadside experiment conducted to test the accuracy of the

program, and the results of that experiment, which show the program classifications to be

highly accurate.

The report then describes the options available within the program, and provides instructions

and an example on the use of the program. Possible future expansions of the system

are also cited.

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