Efficient methodology for benchmarking dynamic origin-destination demand estimation methods

Tamara Djukic, J. W.C. Van Lint, S. P. Hoogendoorn

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

One of the key traffic variables required for the ex post and ex ante evaluation of traffic management and policy measures is origin-destination (O-D) demand matrices. Without ground truth O-D information, however, it is difficult, if not impossible, to assess the quality of an O-D estimation method because so many unknowns are involved. One indicator of the quality of an O-D estimation method is the sensitivity of the method to, and its robustness against, random and structural perturbations of the input from a few typical test networks (e.g., data from sensors, prior O-D matrices). In this paper, an assessment methodology is proposed on the basis of the Latin hypercube method, which is an efficient alternative to Monte Carlo sampling and particularly suited for high-dimensional estimation problems. The methodology is demonstrated on a real urban corridor network for a well-known O-D estimation method (the minimum information estimation method) to illustrate the results that can be obtained and how these results can be used to benchmark different O-D estimation methods.

Original languageEnglish
Pages (from-to)35-44
Number of pages10
JournalTransportation Research Record
Issue number2263
DOIs
Publication statusPublished - 1 Dec 2011
Externally publishedYes

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