Fine-grained OD estimation with automated zoning and sparsity regularisation

Aditya Krishna Menon*, Chen Cai, Weihong Wang, Tao Wen, Fang Chen

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    19 Citations (Scopus)

    Abstract

    Given a road network, a fundamental object of interest is the matrix of origin destination (OD) flows. Estimation of this matrix involves at least three sub-problems: (i) determining a suitable set of traffic analysis zones, (ii) the formulation of an optimisation problem to determine the OD matrix, and (iii) a means of evaluating a candidate estimate of the OD matrix. This paper describes a means of addressing each of these concerns. We propose to automatically uncover a suitable set of traffic analysis zones based on observed link flows. We then employ regularisation to encourage the estimation of a sparse OD matrix. We finally propose to evaluate a candidate OD matrix based on its predictive power on held out link flows. Analysis of our approach on a real-world transport network reveals that it discovers automated zones that accurately capture regions of interest in the network, and a corresponding OD matrix that accurately predicts observed link flows.

    Original languageEnglish
    Pages (from-to)150-172
    Number of pages23
    JournalTransportation Research Part B: Methodological
    Volume80
    DOIs
    Publication statusPublished - 1 Oct 2015

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