Antoniou, Constantinos, Barceló, Jaume, Breen, Martijn, Bullejos, Manuel, Casas, Jordi, Cipriani, Ernesto, Ciuffo, Biagio, Djukic, Tamara, Hoogendoorn, Serge, Marzano, Vittorio, Montero, Lídia, Nigro, Marialisa, Perarnau, Josep, Punzo, Vincenzo, Toledo, Tomer, and van Lint, Hans
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 on-line 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 off-line/planning and on-line algorithms are presented, together with a demonstration of the extensibility of the presented framework to accommodate additional data sources. [ABSTRACT FROM AUTHOR]