The motivation behind this research is the need for a real-time implementable, yet
accurate, procedure for estimating an origin-destination (O-D) trip-table based on entering
and exiting traffic volume data for a given freeway section. These tables help in on-line
control of traffic facilities, and consequently, are of significant use in alleviating traffic
congestion. The dynamism of the approach captures the variations in the traffic counts
with time which are in tum used to predict user travel patterns.
Two models have been developed for this problem, one based on a least squares
estimation and the other based on an 11 norm approach. Two projected conjugate gradient
schemes are investigated for solving the constrained least squares problem, and an interior
point affine scaling algorithm that is applied to the dual problem is explored for solving the
11 estimation linear programming problem. Computational results are presented on a set
of test problems involving the determination of O-D trip tables for both intersection and freeway scenarios in order to demonstrate the viability of the proposed methods. These
results exhibit that, unlike as reported in the literature based on previous efforts, properly
designed parameter optimization methods can indeed provide accurate estimates in a realtime
implementation. Hence, this research presents a competitive alternative to the
iterative statistical techniques that have been heretofore used because of their real-time
processing capabilities, despite their inherent inaccuracies. We hope that the proposed
technology enhances existing methods for constructing O-D trip-tables from traffic
counts.
next to an author's name indicates that all files or directories associated with their ETD are accessible from the Virginia Tech campus network only.
![[VT]](http://scholar.lib.vt.edu/images/ETD-db/restricted.gif)
