Abstract
A dynamic traffic assignment (DTA) model has been widely accepted as a standard planning tool for assessing developed transportation policy and forecasting the effect of future travel demand. If excluding a problem originated from the inclusion of time concept in DTA model, the basic framework of DTA model is similar to that of static model. Using given exogenous travel demand, DTA model loads the travel demand on a network and finds an optimal solution satisfying with a pre-defined route choice rule. In standard DTA loading, the departure time pattern of given travel demand is predefined and assumed as fixed values. However, the departure time is variable depending on a network traffic condition in a real travel choice process when drivers have their preferred arrival time for their destinations. Therefore, for commuters in the morning peak, the departure time should be modeled as an endogenous variable. In this paper, the authors criticize the framework of current standard DAT model and propose an alternative approach which could overcome the shortcomings of current DTA model. The authors substitute a traditional definition for time-dependent OD table by a new definition in which the time-dependent OD table is defined as arrival time-based one. In results, we can have a new DTA model which can calculate equilibrium departure pattern without any additional module such as a schedule delay function. Three types of objective function for a new DTA framework are proposed, and the solution algorithms for the three objective functions are also explained.