The dynamic traffic assignment models with real-time information

This thesis develops a series of novel analytical traffic assignment frameworks to study the adaptive routing in the transportation network for a given real-time information. The analytical study shows the relation between two typical principles of route choice, i.e., user equilibria and system optimality, and the role of First-In-First-Out conditions in these principles. This relation enables the development of incremental loading method to obtain the solutions efficiently by solving a sequence of linear programs. The proposed frameworks have a wide range of applications in reality, including the congestion management and the forecast of road traffic in the network.