Examining the Benefit of Accounting for Traffic Dynamics in Congestion Pricing Applications

There has been rapidly increasing interest in developing congestion pricing models and applications for relieving congestion in transportation networks. However, most of the work in the literature focuses on using static transportation models for analysis. It is still unclear what, if any, benefits are derived by accounting for traffic dynamics in congestion pricing. The main purpose of this paper is to perform a systematic comparison of both the static and dynamic CP results on the Dallas Ft. Worth Network. As part of this analysis we develop a novel demand profiling algorithm based on piecewise linear curves, and provide a method that enables comparison between the results of static traffic assignment, and an approximation to dynamic traffic assignment used in an add-in for certain types of software. The results indicate that traditional static models have the potential to significantly underestimate congestion levels in traffic networks, and the ability of DTA models to account for nonuniform demand and traffic dynamics in congestion pricing should not be neglected.