A hybrid optimization-mesoscopic simulation dynamic traffic assignment model

The evaluation of ITS measures, such as advanced traveler information systems and advanced traffic management systems depend heavily on the use of faster than real time traffic simulation methods. Although many micro-simulation traffic models have already been developed, their execution times are still too slow for large-scale ITS applications. This has lead to the development of mesoscopic simulation and traffic assignment methods. These are simpler traffic models, which trade off some of the fidelity of the results for significant gains in computation time. This paper presents a new dynamic traffic assignment model that is based on the mesoscopic space-time queue network loading method developed by Mahut (2000). This hybrid optimization simulation method was applied to a portion of the Stockholm road network, which consists of 220 zones, 2080 links and 5000 turns.