| This dissertation investigates traveler heterogeneity for dynamic traffic assignment (DTA) in the following four dimensions: travelers' attributes (in the value of time and the value of schedule delay), modal choice, parking choice and route choice. The main focus is on obtaining analytical DTA solutions in simplified networks, particularly in the context of the morning commute problem, with precise sensitivity analysis to derive effective traffic congestion management policies.;First, we solve the morning commute problem with a heterogeneous traveling population whose early/late arrival penalty are continuously distributed. The distribution of the value of schedule delay on each route, freeway or the arterial road, is discussed. It is found that the assumption of homogeneity population overestimates the queuing delay and the total travel time. Every commuter is better off if the freeway capacity or arterial capacity is enlarged, but commuters with high values of early/late arrival penalty generally benefit more than those with low values unless they switch to other routes. We further study the multi-modal morning commute problem with three modes, transit, solo-driving and carpool. Enlarging HOV facilities may reduce transit ridership and increase auto travel, and it does not necessarily reduce the total travel cost when the network is highly congested. The rise of gas price may first entice auto travelers to carpool. However, as the gas price increases further, both carpoolers and solo-drivers will eventually switch to use the transit. In addition, a flat freeway tool can also reduce the total network travel cost.;In addition to the intrinsic distinction among travelers, we also discuss the management measures that can distinguish travelers externally, using parking as an example. The parking fee, parking capacity allocation and accessibility altogether can effectively reduce both the system cost and the queuing delay. If parking lots are owned publicly, then all travelers are better off under the optimal parking setting. This is an advantage that cannot be realized by the system-optimum dynamic toll scheme. If they are owned privately, then market regulations, such as price-ceiling and quantity tax/subsidy, are suggested to improve the network performance and reduce the congestion.;We finally extend our research to the DTA problem in general networks. We propose a hybrid route choice model for studying non-equilibrium traffic where travelers have different preferences in choosing travel routes. It combines pre-trip route choice and en-route route choice to solve dynamic traffic assignment (DTA) in large-scale networks. We apply the hybrid route choice model in a synthetic medium-scale network and a large- scale real network to assess its effect on the flow patterns and network performances, and compare them with those obtained from Predictive User Equilibrium (PUE) DTA. The proposed route choice model incorporating route choice heterogeneity is capable of solving DTA efficiently in a realistic size network with satisfactory results. Finally, some suggestions are given on how to calibrate the hybrid route choice model in practice. |
