Mesoscopic simulator data to perform dynamic origin- destination matrices estimation in urban context
The aim of this paper is to explore a new approach to obtain better traffic demand (Origin-Destination, OD matrices) for dense urban networks using traffic simulation data. From reviewing existing methods, from static to dynamic OD matrix evaluation, possible deficiencies in the approach could be identified. To improve the global process of traffic demand estimation, this paper is focusing 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 used to perform the OD estimation. The Lower Level (traffic assignment) problem will determine, dynamically, the utilization of the network by vehicles using heuristic data from mesoscopic traffic simulator particularly adapted for urban context. The Upper Level (matrix adjustment) problem will proceed to an OD estimation using optimization least square techniques. In this way, a full dynamic and continuous estimation of the final OD matrix could be obtained. First evaluation of the proposed approach and conclusions are presented.