1 research outputs found
Compressive Origin-Destination Matrix Estimation
The paper presents an approach to estimate Origin-Destination (OD) flows and
their path splits, based on traffic counts on links in the network. The
approach called Compressive Origin-Destination Estimation (CODE) is inspired by
Compressive Sensing (CS) techniques. Even though the estimation problem is
underdetermined, CODE recovers the unknown variables exactly when the number of
alternative paths for each OD pair is small. Noiseless, noisy, and weighted
versions of CODE are illustrated for synthetic networks, and with real data for
a small region in East Providence. CODE's versatility is suggested by its use
to estimate the number of vehicles and the Vehicle-Miles Traveled (VMT) using
link counts