The Development of a Household Travel Resource Allocation Model for Kitchener – Waterloo

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Date

2015-09-24

Authors

Yeung, Kevin King Lun

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University of Waterloo

Abstract

Cities are dynamic and complex. Changes within cities are a result of actions of decision makers – governments, businesses, and households – and interactions within urban systems. An integrated land use - transport model is being developed to estimate the change in residential location choice and travel behaviour in the cities of Kitchener and Waterloo, Ontario, Canada. Within this model, there must be a representation of the daily travel decisions made by households to determine when and how people travel to activities. This decision is constrained by the availability of travel resources, such as vehicles or chaperones (for households with members that cannot travel on their own) This research proposes a model for these daily travel decisions that allocates travel resources to household members so that they are able to achieve their desired activities in a day. The output of the model is a set of scheduled tours and activities for each member of the household. The model is informed by a survey of 14 households within the Region of Waterloo, and tested against 9 household schedules that are located within the cities of Kitchener and Waterloo. The result of the model tests show that it performs relatively well in the scheduling of activities and the creation of tours if there is some level of time constraint associated with the discretionary activities. As well, the model is able to predict the mode choice for most tours, but some mode preferences are not entirely captured. Furthermore, this model is able to complete the travel resource allocation in an average time of 36 milliseconds per household. This research serves as the foundation for a model of household transport decisions that may be incorporated into the broader integrated land use - transport model for Kitchener and Waterloo.

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Keywords

activity scheduling, mode choice, transportation, planning, household travel behaviour, modelling, forecasting, agent based model

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