Urban Transportation Network Equilibrium And Congestion Pricing With Bounded Rationality

Traffic congestion is a special kind of flow pattern in a certain time-space context. This dissertation analyzed both the behavioral and psychological process of tripmakings, refined the factors contributing to travelers' bounded rationality and established a Prospect Theory-based route choice decision-making framework. Models were established to describe the network equilibrium flow patterns and system dynamics with consideration to travelers' bounded rationality. And various strategies were represented to help relieve traffic congestion through guiding travelers'choices. More details are listed bellow.Firstly, the behavioral process of urban trips was analyzed in stages under the concept of consumer behavior theory. The Individual Behavior Model (IBM) was used to analyze commuters' decision-making mechanism. An IBM-based structure model was advanced to systemically describe traveler's psychological process, which represents the relationship among objective factors, subjective factors, commuter's decision-making and activity. The first part of the dissertation also concluded the key problems to be solved in the bounded-rationality-based transportation research.Secondly, this dissertation developed a general route choice decision-making rule with the choice concept of cumulative prospect theory. After an analysis about the relationship between the reference points and travelers'risk preferences, a method was proposed to determine the values of endogenous reference points. A questionnaire survey was conducted to capture the distribution of reference point parameters in the context of route choice. Together with the questionnaire survey, the method of numerical fitting was used to re-estimate the parameter values. In conclusion, a travel utility measure system was established, which was illustrated by numerical examples.Thirdly, a fixed-demand stochastic network user equilibrium model was established on the basis of prospect theory. The proposed prospect-based user equilibrium model is flexible and general. It incorporated some user equilibrium models in the literatures as special cases. It was assumed that travelers had different views on the values of reference points. A multi-class elastic demand user equilibrium model was established. We further established a CPT-based dynamic system that incorporated travelers'learning and renewal procedure and dynamic route choices. The proposed system is expected to capture the day-to-day dynamic traffic flow patterns.Finally, attention was paid to the congestion relief strategies. The IBM showed that travelers'abilities played an important role in their decision-making. This research established an ability-based pricing model that determined an optimal pricing scheme for stochastic networks to minimize the total (expected) travel times. On the basis of the conclusions about travelers' behavior with bounded rationality, this dissertation also suggested a strategy frame about traffic demand management and several principles that should be followed by transportation policy makers.