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Estimation/updating of origin-destination (OD) flows and other traffic state parameters is a classical, widely adopted procedure in transport engineering, both in off-line and in online contexts. Notwithstanding numerous approaches proposed in the literature, there is still room for considerable improvements, also leveraging the unprecedented opportunity offered by information and communication technologies and big data. A key issue relates to the unobservability of OD flows in real networks-except from closed highway systems-thus leading to inherent difficulties in measuring performance of OD flows estimation/updating methods and algorithms. Starting from these premises, the paper proposes a common evaluation and benchmarking framework, providing a synthetic test bed, which enables implementation and comparison of OD estimation/updating algorithms and methodologies under "standardized" conditions. The framework, implemented in a platform available to interested parties upon request, has been flexibly designed and allows comparing a variety of approaches under various settings and conditions. Specifically, the structure and the key features of the framework are presented, along with a detailed experimental design for the application of different dynamic OD flow estimation algorithms. By way of example, applications to both offline/planning and on-line algorithms are presented, together with a demonstration of the extensibility of the presented framework to accommodate additional data sources. Keywords Traffic modelling, origin-destination (OD) estimation/updating, benchmarking platform. 1. Background and motivation Traffic congestion has been plaguing urban and interurban transportation systems everywhere for *Manuscript Click here to view linked References 1. TRUE CASE STUDY SETUP (FORWARD PROBLEM) 2. DESIGN OF EXPERIMENTAL SETUP

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