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.
Description
[1606.03332] Networked Traffic State Estimation Involving Mixed Fixed-mobile Sensor Data Using Hamilton-Jacobi equations
%0 Generic
%1 canepa2016networked
%A Canepa, Edward S.
%A Claudel, Christian G.
%D 2016
%K transportation
%T Networked Traffic State Estimation Involving Mixed Fixed-mobile Sensor
Data Using Hamilton-Jacobi equations
%U http://arxiv.org/abs/1606.03332
%X 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.
@misc{canepa2016networked,
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.},
added-at = {2017-10-06T17:47:38.000+0200},
author = {Canepa, Edward S. and Claudel, Christian G.},
biburl = {https://www.bibsonomy.org/bibtex/2050ff6424ae79c7ca3ca412429402117/masslabut},
description = {[1606.03332] Networked Traffic State Estimation Involving Mixed Fixed-mobile Sensor Data Using Hamilton-Jacobi equations},
interhash = {6bd93c135357babf09235c873b7dec58},
intrahash = {050ff6424ae79c7ca3ca412429402117},
keywords = {transportation},
note = {cite arxiv:1606.03332},
timestamp = {2017-10-06T17:47:38.000+0200},
title = {Networked Traffic State Estimation Involving Mixed Fixed-mobile Sensor
Data Using Hamilton-Jacobi equations},
url = {http://arxiv.org/abs/1606.03332},
year = 2016
}