The paper proposes an innovative methodology for addressing the issue of the location of optimal link count sections on the basis of the proposition of a reliability measure in which the prior accuracy of the estimate of the origin-destination (O-D) matrix, that is, its statistical distribution rather than its prior punctual estimate, is explicitly considered, together with its posterior distribution conditioned on a given subset of link count locations. The proposed measure, under the mild assumptions of prior normal distribution and through appropriate algebraic rotations of the reference system, is proved not to depend on the unknown values of the counted flows; this is actually the key point that allows for effective implementation of a fast and operational procedure that is based on this mathematical framework. As an example, toy network and real network applications are presented to show how a heterogeneous level of knowledge across O-D pairs may lead to the choice of counting sections different from those resulting from the commonly adopted procedures. The proposed methodology allows for a more effective theoretical interpretation of the phenomenon and leads to an extremely efficient computational procedure-suitable also in real-size networks-whose results outperform those obtained with the methods currently available in the literature.

Methodology for locating link count sensors that accounts for reliability of prior estimates from origin-destination matrices

SIMONELLI, Fulvio;
2011

Abstract

The paper proposes an innovative methodology for addressing the issue of the location of optimal link count sections on the basis of the proposition of a reliability measure in which the prior accuracy of the estimate of the origin-destination (O-D) matrix, that is, its statistical distribution rather than its prior punctual estimate, is explicitly considered, together with its posterior distribution conditioned on a given subset of link count locations. The proposed measure, under the mild assumptions of prior normal distribution and through appropriate algebraic rotations of the reference system, is proved not to depend on the unknown values of the counted flows; this is actually the key point that allows for effective implementation of a fast and operational procedure that is based on this mathematical framework. As an example, toy network and real network applications are presented to show how a heterogeneous level of knowledge across O-D pairs may lead to the choice of counting sections different from those resulting from the commonly adopted procedures. The proposed methodology allows for a more effective theoretical interpretation of the phenomenon and leads to an extremely efficient computational procedure-suitable also in real-size networks-whose results outperform those obtained with the methods currently available in the literature.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/1097
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? ND
social impact