Advanced Models For Urban Transportation Infrastructure Investment And Congestion Externality Management

With the rapid growth of social economic and urbanization process, traffic congestion has become an increasing serious problem and a bottleneck to restrict the development of urban economic. The essential cause of traffic congestion stems from the imbalance of traffic supply and demand. Thus, the alleviation of urban traffic congestion calls for both increase of transportation infrastructure investment and enhancement of traffic demand management. In this dissertation research, we deal with the meansures on traffic supply and demand, such as investment of transportation infrastructure and urban major roads, and management of congestion externalities. It is expected that the study in this thesis can enrich and improve the current urban transport planning and management theory, provide fundamentals and tools for urban sustainable development.Firstly, we propose a technoloty investment decisionmodel for investigating transit technology investment problem from a perspective of transit authority. Given a transit technology alternative (e.g. metro, light rail transit or bus rapid transit), the proposed model aims to maximize the social welfare of the transit system by determining the optimal combination of transit line length, number of stations, station location (or spacing), headway and fare. In the proposed model, the effects of passenger demand elasticity and capacity constraint are explicitly considered. The properties of the model are examined analytically and a heuristic solution procedure for determining the model solution is presented. By comparing the optimized social welfare for different transit technology alternatives, the optimal transit technology investment solution can be obtained together with critical population density. On the basis of a simple population growth rate formula, optimal investment timing of a new transit technology can be estimated. The proposed methodology is illustrated in several Chinese cities. Insightful findings are reported on the interrelation among transit technology investment, population density, and transit line parameter design as well as the comparison between social welfare maximization and profit maximization regimes.Secondly, we propose an analytical urban system equilibrium model for optimizing the density of radial major roads in a two-dimensional monocentric city. The proposed model involves four types of agents:local authorities, property developers, households and household workers (i.e. commuters). The local authorities aim to maximize the total social welfare of the urban system by determining the optimal density of radial major roads in the city. The property developers seek to determine the intensity of their capital investment in the land market to maximize the net profit generated from the housing supply. The households choose residential locations that maximize their utility within a budget constraint, and the commuters choose the radial major roads that minimize their individual costs of travel between home and workplace. A heuristic solution procedure is developed to find the urban system equilibrium solution. A system optimum model is also proposed to optimize the density of radial major roads that maximizes the social welfare of the urban system. The proposed model can endogenously determine household residential distribution and land values across the city, along with the housing market structure in terms of housing prices and space. Furthermore, numerical comparative static analyses of congestion pricing and road infrastructure investment (adding a new radial major road) are carried out together with evaluation of the effects of the service level of radial major roads, urban population size, and household income level on the urban economy.Thirdly, we propose an analytical model for the design of a tradable property tax credit scheme so as to manage housing crowding externalities and traffic congestion externalities. The proposed scheme helps to rationalize the urban spcace structure and residential distribution, and further alleviate urban traffic congestion. In the proposed model, the interaction between the property tax credit scheme and households’residential location choices is explicitly considered. It is assumed that the authority initially allocates the property tax credits to all households in a uniform way, and the households pay a certain amount of credits for their housing consumptions and traffic commuting, which depend on the total externality that they cause. The property tax credits can be traded among households through a free market at a certain price that is set by the authority. For a given credit price, households’ residential location choices and housing market structure in terms of housing prices and space can be determined by solving the urban system equilibrium problem. A social welfare maximization model is presented to determine the optimal price of unit credit. Numerical results show that implementation of the property tax credit scheme can rationalize the households’ residential location choices and promote the efficiency of the urban system in terms of social surplus.