I finished my M.A.Sc. degree at the University of Toronto in August. In a past post, I discussed some of the coursework that made up the first year of the degree, but I haven’t really discussed the core research here before. I did win an award for some interim results presented at a local conference, but I wanted to hold back on too much public detail until some of my results were ready for publication. My paper submission to the Transportation Research Board was accepted this week, and my thesis will be formally published by the university next month, so there’s no need to hold back any further.
My research is a small piece of a larger research effort: trying to build integrated land use / transportation models that go beyond traditional transportation models. In classic four-stage models for forecasting travel demand, both the transportation network and the shape of the city (land use) is treated as an input to the model, and the travel patterns that would emerge from such a city are estimated. Typically, the goal is to see how changes to the transportation network would impact travel patterns – for example, building a new freeway or subway route. In reality, however, it is not valid to hold land use constant while changing the transportation network – land use reacts to the presence of transportation infrastructure.
Models of this type have been under development for a long time, and my thesis is part of the ILUTE modelling effort at the University of Toronto. The figure below shows the ILUTE model structure, with land development, household location choice and automobile ownership as integral components of the model, not inputs to the model.
My particular contribution is in the population synthesis part of the model, where I developed a faster and more capable method for synthesizing person, family, household and dwelling agents/objects; and a more robust method for creating the initial relationships between these agents.