Models For Urban Transportation Infrastructure Investment And Congestion Pricing Decisions

In recent years, the rapid socio-economic development and transportation demand growth have brought tremendous pressure to the existing transportation infrastructure. The relatively lagging growth in the number of road kilometers cannot catch up with the increase in traffic demand, and the imbalance of transport supply and demand becomes increasingly acute. In order to alleviate the current situation of urban traffic congestion, the paper focuses on the issues of urban transportation infrastructure investment and congestion toll pricing. It is expected that the models presented in this thesis can provide the theoretical and scientific basis for urban traffic planning and management, transport policy analysis and sustainable urban development.Firstly, we address the transit technology investment issues under urban population volatility using a real option approach. Two important problems involved are which transit technology should be introduced and when to introduce it. A real option model is proposed to incorporate explicitly the effects of transit technology investment on urban spatial structure in terms of households’ residential location choices and housing market. The trigger population thresholds for investing in a transit technology project and for switching from a transit technology to another are explored analytically, and comparative static analyses of the urban system and transit technology investment are conducted. The proposed methodology is validated using two candidate Chinese cities and the solutions of the models with and without urban spatial/land use equilibrium consideration are compared. Insightful findings on the relationship between transit technology investment and urban development are reported.Secondly, we propose an analytical model to address the timing issue of cordon toll pricing in a monocentric city. The proposed model allows an explicit consideration of the interactions among three types of agents in the urban system:(1) the local authority who aims to jointly determine the optimal time for introducing cordon toll pricing scheme, cordon toll location and toll level to maximize social welfare of the urban system;(2) property developers who seek to determine the intensity of their capital investment in the land market to maximize their own net profit generated from the housing supply; and (3) households who choose residential locations that maximize their own utility within a budget constraint. The effects of the cordon toll pricing scheme on household’s residential location choice and housing market structure in terms of housing price and space are explicitly considered. A comparison of the toll pricing schemes with a fixed and a mobile cordon location over time and the no-toll case is carried out. The proposed model is also illustrated with several Chinese cities as examples. Insightful findings are reported on the interactions among cordon toll pricing scheme, urban population size, household income level, toll collection cost, and urban development.Thirdly, we address the optimal design of cordon toll pricing schemes, accounting for the health effects of traffic emissions. We propose a model that aims to maximize the overall social welfare by simultaneously determining the optimal road capacity, cordon toll location, and toll level in a linear monocentric city with variable road capacity. Considering health effects of traffic emissions explicitly, the model can be used to explore and compare such equilibrium solution properties as road infrastructure investment (road capacity) and emission costs. These findings have important policy implications for the designs of the optimal cordon location, optimal toll level, and road capacity. Further, with the additional focus of the model on reducing the adverse health impacts of traffic emissions through the adjustment of variable road capacity, our modeling framework offers an alternative approach to assisting transportation planners and policy makers in their search for green infrastructure investment strategies.