Information metrics for improved traffic model fidelity through sensitivity analysis and data assimilation

A. Sopasakis and M.A. Katsoulakis

Transportation Research Part B: Methodological, 2016, vol. 86, issue C, 1-18

Abstract: We develop theoretical and computational tools which can appraise traffic flow models and optimize their performance against current time-series traffic data and prevailing conditions. The proposed methodology perturbs the parameter space and undertakes path-wise analysis of the resulting time series. Most importantly the approach is valid even under non-equilibrium conditions and is based on procuring path-space (time-series) information. More generally we propose a mathematical methodology which quantifies traffic information loss.

Keywords: Traffic model parametrization; Inverse dynamic Monte Carlo; Stochastic microscopic dynamics; Information theoretic tools; Relative entropy rate; Fisher information matrix; Controlled fidelity (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1016/j.trb.2016.01.003

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