A model for integrated analysis of household location and travel choices |
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| Institution: | 1. School of Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China;2. School of Science, Wuhan University of Technology, Wuhan 430063, China;;1. Department of Electrical and Computer Engineering, George Washington University, Washington, DC 20052 USA;2. Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada;1. Department of Civil Engineering, Taibah University, 42353 Medina, Saudi Arabia;2. LESTE Laboratory, ENIM, Monastir University, 12, Ibn El Jazzar Avenue, 5019 Monastir, Tunisia;1. Institute for Transport Studies, Universität für Bodenkultur Wien, Austria;2. Institute for Transport Studies and Choice Modelling Centre, University of Leeds, UK;3. School of Psychology and Centre for Immersive Technologies, University of Leeds, UK;4. Edge Hill University, UK;5. Future Cities Laboratory Singapore-ETH Centre Zurich, Singapore;6. University of Applied Sciences and Arts Northwestern Switzerland, Switzerland |
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| Abstract: | We develop a model for integrated analysis of household location and travel choices and investigate it from a theoretical point of view.Each household makes a joint choice of location (zone and house type) and a travel pattern that maximizes utility subject to budget and time constraints. Prices for housing are calculated so that demand equals supply in each submarket. The travel pattern consists of a set of expected trip frequencies to different destinations with different modes. The joint time and budget constraints ensure that time and cost sensitivities are consistent throughout the model. Choosing the entire travel pattern at once, as opposed to treating travel decisions as a series of isolated choices, allows the marginal utilities of trips to depend on which other trips are made.When choosing trip frequencies to destinations, households are assumed to prefer variation to an extent varying with the purpose of the trip. The travel pattern will tend to be more evenly distributed across trip ends the less similar destinations and individual preferences are. These heterogeneities of destinations and individual preferences, respectively, are expressed in terms of a set of parameters to be estimated. |
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