Events Calendar

Variable origin-destination trip matrix estimation: A maximum entropy-least squares estimator

Speaker: Chi Xie, The University of Texas at Austin

Talk Title: Variable origin-destination trip matrix estimation: A maximum entropy-least squares estimator

Abstract: In transportation subnetwork-supernetwork analysis, it is well known that the origin-destination (O-D) flow table of a subnetwork is not only determined by trip generation and distribution, but also by traffic routing and diversion, due to the existence of internal-external, external-internal and external-external flows. This result indicates the variable nature of subnetwork O-D flows. This talk presents a variable O-D flow table estimation problem for subnetwork analysis. The underlying assumption is that each cell of the subnetwork O-D flow table contains an elastic demand function rather than a fixed demand rate and the demand function can properly capture traffic diversion effects under various network changes.
An integrated maximum entropy-least squares (ME-LS) estimator is proposed, by which O-D flows are distributed over the subnetwork so as to maximize the trip distribution entropy, while demand function parameters are estimated for achieving the least sum of squared estimation errors. While the estimator is powered by the classic convex combination algorithm, computational difficulties emerge within the algorithm implementation until partial optimality conditions and a column generation procedure are incorporated into the algorithmic framework. Numerical results from applying the integrated estimator to a couple of subnetwork examples show that a variable O-D flow table, when used as input for subnetwork flow evaluations, reflects network flow changes significantly better than its fixed counterpart.


Host: Sonny Astani Dept. of Civil and Environmental Engineering

Location: Kaprielian Hall (KAP) - 209

Audiences: Everyone Is Invited

Contact: Erin Sigman