Integration of an Agent-Based Joint Route and Departure Time Choice Model with the Dynamic Traffic Assignment Package

Compared to static traffic assignment models, dynamic traffic assignment (DTA) models consider time variations in the demand and flow behaviors in the traffic network. However, within the current DTA framework, it is difficult to model traveler's characteristics and behaviors such as heterogeneity, information sharing, learning process, and the interactions among the travelers. Agent-based modeling and simulation (ABMS) is specifically developed to address this complexity and support individual agent-based decision making. This paper proposes a framework that integrates an agent-based joint route and departure time choice model with the DynusT traffic simulation. The proposed agent-based joint route and departure time choice model considers learning from previous experiences (e.g., trips), heterogeneity of different travelers, incomplete network information, and information sharing between travelers. An interface is defined between the simulation package and the proposed choice model that supports individual agent to make route and departure time decision jointly.