Integrated Optimization Models On Urban Land Use And Transportation System

With the rapid growth of social economy and the acceleration of urbanizationprocess, intensity of urban land use dramatically increases, and traffic congestion andenvironmental issues caused by traffic are becoming increasingly serious problems. Inthe previous related studies, it was often suggested to increase a new road or to expandan existing road to alleviate traffic congestion. However, there is a close relationshipbetween land use and transportation, thus it is important to consider the effects of landuse in the transportation network design. In addition, traffic emissions are one of themain contributions to global warming, it is therefore necessary to incorporateenvironmental issues in the transportation network design problems. In view of the above,there is an urgent need to address the integrated design of urban land use andtransportation system so as to reduce urban traffic congestion and create a sustainableurban transportation system.This thesis firstly studies the commuters’ choices of residential and employmentlocations and travel routes, and proposes a network equilibrium model for the integratedresidential/employment location and route choices to predict travel demand distributionon the network. Then, under the condition of environmental sustainability, the integratedoptimization models of urban land use and transportation system under bothdeterministic and stochastic demand scenarios are developed, respectively. Particularly,in the uncertain scenario, the future population size is assumed to be a random variablewith a given probability distribution. This stochastic model is formulated as a two-stagerobust optimization problem with chance constraints, which aims to maximize a robustrisk-averse objective function by determining the capacity increases in the urban land useand road links in the network. Finally, a heuristic solution algorithm is developed to solvethe proposed models. Numerical studies are given to illustrate the application of theproposed models and solution algorithm. Sensitivity analyses to some key modelparameters are also carried out.