Abstract
Over the last fifty years, transportation researchers have sought to develop stable day-to-day dynamical models to capture the convergence process toward a departure time user equilibrium (DTUE). However, most existing models lack mathematically guaranteed stability. There is seminal recent research at UCI that introduced the first provably stable analytical model of day-to-day departure time dynamics, albeit without considering multi-class dynamics, congestion pricing, or network-level traffic dynamics. This dissertation addresses these issues that are important for realism in the analysis, by: (1) developing the first stable multi-class dynamics with heterogeneous travelers; (2) integrating pricing schemes to drive the system from DTUE to system optimum (SO); and (3) scaling departure time modeling to the network level using Vickrey’s bathtub model and dynamic traffic assignment (DTA) simulations. Collectively, these contributions provide a stable modeling framework for analyzing and managing departure time choices at both corridor and network levels, that offers new theoretical insights for designing stable and efficient congestion pricing policies, and helps develop early practical insights on a notably more efficient process for transportation planning at large.
