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The aim of this paper is to explore a new approach to obtain better traffic demand (Origin-Destination, OD matrices) in dense urban networks. From reviewing actual methods, for static and dynamic OD matrix evaluation, possible deficiencies in the approach could be identified. To improve the global process of traffic demand estimation, this paper is focussing on a new methodology to determine dynamic OD matrices for urban areas characterized by complex route choice situation and high level of traffic controls. An iterative bi- level approach will be use to perform the OD estimation. The Lower level (traffic assignment) problem will determine, dynamically, the utilisation of the network by vehicles using heuristic data from traffic simulator. This simulation will be mesoscopic and a particular calibration will be done, focusing mainly on flow and route choice indicators. The Upper level (matrix adjustment) problem will precede to an OD estimation using dynamic optimization least square techniques. In this way, a full dynamic and continuous estimation of the final OD matrix could be obtained in urban context.
Jeffrey Huang, Simon Elias Bibri