Networked traffic state estimation involving mixed fixed-mobile sensor data using Hamilton-Jacobi equations

Handle URI:
http://hdl.handle.net/10754/625618
Title:
Networked traffic state estimation involving mixed fixed-mobile sensor data using Hamilton-Jacobi equations
Authors:
Canepa, Edward S. ( 0000-0002-5779-2059 ) ; Claudel, Christian G.
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.
KAUST Department:
Electrical Engineering Program
Citation:
Canepa ES, Claudel CG (2017) Networked traffic state estimation involving mixed fixed-mobile sensor data using Hamilton-Jacobi equations. Transportation Research Part B: Methodological 104: 686–709. Available: http://dx.doi.org/10.1016/j.trb.2017.05.016.
Publisher:
Elsevier BV
Journal:
Transportation Research Part B: Methodological
Issue Date:
19-Jun-2017
DOI:
10.1016/j.trb.2017.05.016
Type:
Article
ISSN:
0191-2615
Additional Links:
http://www.sciencedirect.com/science/article/pii/S0191261516302983
Appears in Collections:
Articles; Electrical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorCanepa, Edward S.en
dc.contributor.authorClaudel, Christian G.en
dc.date.accessioned2017-10-03T12:49:29Z-
dc.date.available2017-10-03T12:49:29Z-
dc.date.issued2017-06-19en
dc.identifier.citationCanepa ES, Claudel CG (2017) Networked traffic state estimation involving mixed fixed-mobile sensor data using Hamilton-Jacobi equations. Transportation Research Part B: Methodological 104: 686–709. Available: http://dx.doi.org/10.1016/j.trb.2017.05.016.en
dc.identifier.issn0191-2615en
dc.identifier.doi10.1016/j.trb.2017.05.016en
dc.identifier.urihttp://hdl.handle.net/10754/625618-
dc.description.abstractNowadays, 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.en
dc.publisherElsevier BVen
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S0191261516302983en
dc.subjectTraffic estimationen
dc.subjectMixed integer linear programmingen
dc.subjectOptimizationen
dc.titleNetworked traffic state estimation involving mixed fixed-mobile sensor data using Hamilton-Jacobi equationsen
dc.typeArticleen
dc.contributor.departmentElectrical Engineering Programen
dc.identifier.journalTransportation Research Part B: Methodologicalen
dc.contributor.institutionDepartment of Civil, Architectural and Environmental Engineering, University of Texas Austin, USAen
kaust.authorCanepa, Edward S.en
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.