TxDOT Research Library - Publication Details

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Title:

Boundary Conditions Estimation on a Road Network Using Compressed Sensing

Report No.:

SWUTC/16/600451-00090-1

Authors:

by Michele Simoni [and three others]

Published:

2016

College Station, Texas

Southwest Region University Transportation Center (U.S.)

Type:

Online document

1 PDF (29 pages)

Online Access:

https://swutc.tamu.edu/publications/technicalrepor...

Access Note:

530 KB

Summary

This report presents a new boundary condition estimation framework for transportation networks in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on Hamilton-Jacobi equation, we pose the problem of estimating the boundary conditions of the system on a network, as a Mixed Integer Linear Program (MILP). We show that this framework can handle various types of traffic flow measurements, including floating car data or flow measurements. To regularize the solutions, we propose a compressed sensing approach in which the objective is to minimize the variations over time (in the L1 norm sense) of the boundary flows of the network. We show that this additional requirement can be integrated in the original MILP formulation, and can be solved efficiently for small to medium scale problems.

Publ. Place

College Station, Texas

Contents

Introduction --
Model Definition --
Affine Initial, Boundary and Internal Conditions --
Constraints Arising From Model and Measurement Data --
Boundary Flow Estimation on a Single Highway Link --
Generalization to Highway Networks --
Application of the Boundary Estimation Framework on Highway Networks --
Conclusion

Notes

"February 2016"

Study Sponsor

Print Copy

Collection:

UTC Online Only

Call Number:

SWUTC 2016-600451-00090-1 CTR

More Like This

Topics

Floating car data
Mixed integer programming
Networks
Optimization
Partial differential equations
Traffic control
Traffic density
Traffic flow
Traffic flow theory
Travel time

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