High-dimensional offline origin-destination (OD) demand calibration for stochastic traffic simulators of large-scale road networks

Carolina Osorio

Transportation Research Part B: Methodological, 2019, vol. 124, issue C, 18-43

Abstract: This paper considers high-dimensional offline calibration problems for large-scale simulation-based network models. We propose a metamodel simulation-based optimization (SO) approach. The proposed method is formulated and validated on a simple synthetic toy network. It is then applied to a high-dimensional case study of a large-scale Singapore network. Compared to two benchmark methods, a derivative-free pattern search method and the SPSA method, the proposed method improves the objective function estimates by two orders of magnitude. Moreover, this improvement is achieved after only 2 simulation runs. Hence, the proposed method is computationally efficient.

Date: 2019
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DOI: 10.1016/j.trb.2019.01.005

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