Integration of Activity-based Modeling and Dynamic Traffic Assignment

The traditional trip based approach to transportation modeling has been employed for the past thirty years. However, due to the limitations of traditional planning for short-term policy analysis, researchers have explored alternative paradigms for incorporating more behavioral realism in planning methodologies. On the demand side, activity-based approaches have evolved as an alternative to traditional trip-based transportation demand forecasting. On the supply side, dynamic traffic assignment models have been developed as an alternative to static assignment procedures. Unfortunately, much of the research efforts in activity-based approaches (the demand side) and dynamic traffic assignment techniques (the supply side) have been undertaken relatively independently. To maximize benefits from these advanced methodologies, it is essential to combine them via a unified framework. The objective of the current paper is to develop a conceptual framework and explore practical integration issues for combining the two streams of research. Technical, computational and practical issues involved in this demand-supply integration problem are discussed. While the framework is general in nature, specific technical details related to the integration are explored by employing CEMDAP for activity-based modeling and VISTA for the dynamic traffic assignment modeling. Solution convergence properties of the integrated system, specifically examining different criteria for convergence, different methods of accommodating time of day and the influence of step size on the convergence are studied. Further, the integrated system developed is empirically applied to two sample networks selected from the Dallas Fort Worth network. Lin, Eluru, Waller and Bhat 3