Dynamic stochastic user equilibrium: Models and algorithms for multidimensional network choices

This dissertation aims at developing models and algorithms for the dynamic stochastic user equilibrium (DSUE) problem in multidimensional transportation networks. These models form the basis of decision-support tools for the planning and design of advanced operational strategies to reduce traffic congestion and enhance system sustainability. The central contribution is a behaviorally flexible time-dependent stochastic user equilibrium (TDSUE) model, which integrates probit-based discrete choice models of user path decisions in a simulation-based dynamic assignment framework. This fixed-point problem is reformulated as an equivalent gap function-based nonlinear optimization problem, and solved by a column-generation framework with a vehicle-based implementation. The approach incorporates newly developed methods to specify and compute the variance-covariance matrix for stochastic dynamic path choice models, thereby addressing a fundamental challenge in capturing spatial and temporal correlation in path cost perception along with unobserved heterogeneity.;The TDSUE is generalized to represent multidimensional choices in networks with heterogeneous users. The generalization is further developed to evaluate transportation policies for three specific problem instances. The first extends the TDSUE to a simultaneous route and departure time choice stochastic user equilibrium (SRDSUE) problem, which is applied to evaluate the impact of flexible work hour policies. The second is a bi-criterion dynamic stochastic user equilibrium (BDSUE) problem which takes into account both heterogeneous users' response to dynamic pricing and perception errors of travel costs. Finally, the third instance is to determine an optimal freight tariff policy, which is considered in the context of an MPEC (Mathematical Program with Equilibrium Constraints) approach to tariff design for multiproduct multimodal freight transportation networks. The objective is to maximize profit subject to equilibrium constraints that explicitly consider shippers' multidimensional choice behavior.;This dissertation makes important contributions to the transportation network modeling literature in terms of key improvements in theory, formulation, algorithm, and implementation. The proposed DSUE models and algorithms have been demonstrated in applications to practical multidimensional networks to evaluate congestion management strategies and determine optimal transportation policies.