The problem of dynamic origin–destination (O-D) demand estimation aims at estimating the unknown demand values for all O-D pairs and departure times with the use of available time-varying link flow observations. This paper presents a distributed algorithm for estimating the dynamic O-D tables for urban transportation networks. The new algorithm supports the deployment of systems for real-time traffic network management that adopt dynamic traffic assignment methodology for network state estimation and prediction. It encapsulates available link information and reduces the data size required by conventional algorithms for O-D demand estimation. The algorithm adopts a two-stage approach. In the first stage, the study area under consideration is divided into a number of subareas, and an O-D demand table is estimated independently for each subarea. These local O-D tables are then integrated to construct an O-D table for the entire study area. An application of the new algorithm for a typical freeway network is presented as an example.