Abstract
Nowadays, traffic management has become a challenge for urban areas, which
are covering larger geographic spaces and facing the generation of different
kinds of traffic data. This article presents a robust traffic estimation
framework for highways modeled by a system of Lighthill Whitham Richards
equations that is able to assimilate different sensor data available. We first
present an equivalent formulation of the problem using a Hamilton-Jacobi
equation. Then, using a semi-analytic formula, we show that the model
constraints resulting from the Hamilton-Jacobi equation are linear ones. We
then pose the problem of estimating the traffic density given incomplete and
inaccurate traffic data as a Mixed Integer Program. We then extend the density
estimation framework to highway networks with any available data constraint and
modeling junctions. Finally, we present a travel estimation application for a
small network using real traffic measurements obtained obtained during Mobile
Century traffic experiment, and comparing the results with ground truth data.
Users
Please
log in to take part in the discussion (add own reviews or comments).