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Title:

Identification of Network Sensor Locations for Estimation of Traffic Flow

Accession Number:

01517525

Record Type:

Component

Availability:

Transportation Research Board Business Office

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Washington, DC 20001 United States

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Order URL: http://worldcat.org/isbn/9780309295314

Abstract:

This paper addresses the network sensor location problem (NSLP) for identifying the set of sensor locations that minimizes the variability in estimation of traffic flow given budget constraints. The trace of the covariance matrix is adopted as a measure of variability in traffic flow. On the basis of the trace of the covariance matrix in the posterior estimation of traffic flow conditional on a given set of sensor locations, the general form of the NSLP is derived. As an illustration, the multivariate normal distribution for the prior estimation of traffic flow is assumed. In this case, the actual value of the counted flows is not required. Furthermore, an incremental method that can avoid matrix inversion and give priorities of the identified sensor locations is presented to solve the NSLP. Finally, a numerical example based on the Nguyen–Dupuis network illustrates the NSLP approach and clarifies some of its implementation details.

Monograph Accession #:

01548337

Report/Paper Numbers:

14-2013

Language:

English

Authors:

Zhu, Senlai
Cheng, Lin
Chu, Zhaoming
Chen, Anthony
Chen, Jingxu

Pagination:

pp 32–39

Publication Date:

2014

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2443
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309295314

Media Type:

Print

Features:

Figures (2) ; References (37) ; Tables (6)

Subject Areas:

Data and Information Technology; Highways; Operations and Traffic Management; I71: Traffic Theory; I72: Traffic and Transport Planning

Files:

TRIS, TRB, ATRI

Created Date:

Jan 27 2014 2:42PM

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