On integrating models of household vehicle ownership, composition, and evolution with activity based travel models

dc.contributor.advisorBhat, Chandra R. (Chandrasekhar R.), 1964-en
dc.contributor.committeeMemberAbrevaya, Jasonen
dc.contributor.committeeMemberPendyala, Ramen
dc.contributor.committeeMemberMachemehl, Randyen
dc.contributor.committeeMemberBoyles, Stephenen
dc.creatorPaleti Ravi Venkata Durga, Rajeshen
dc.date.accessioned2013-01-30T16:20:48Zen
dc.date.available2013-01-30T16:20:48Zen
dc.date.issued2012-12en
dc.date.submittedDecember 2012en
dc.date.updated2013-01-30T16:20:58Zen
dc.descriptiontexten
dc.description.abstractActivity-based travel demand model systems are increasingly being deployed to microsimulate daily activity-travel patterns of individuals. However, a critical dimension that is often missed in these models is that of vehicle type choice. The current dissertation addresses this issue head-on and contributes to the field of transportation planning in three major ways. First, this research develops a comprehensive vehicle micro-simulation framework that incorporates state-of-the-art household vehicle type choice, usage, and evolution models. The novelty of the framework developed is that it accommodates all the dimensions characterizing vehicle fleet/usage decisions, as well as accommodates all dimensions of vehicle transactions (i.e., fleet evolution) over time. The models estimated are multiple discrete-continuous models (vehicle type being the discrete component and vehicle mileage being the continuous component) and spatial discrete choice models that explicitly accommodate for multiple vehicle ownership and spatial interactions among households. More importantly, the vehicle fleet simulator developed in this study can be easily integrated within an activity-based microsimulation framework. Second, the vehicle fleet evolution and composition models developed in this dissertation are used to predict the vehicle fleet characteristics, annual mileage, and the associated fuel consumption and green-house gas (GHG) emissions for future years as a function of the built environment, demographics, fuel and related technology, and policy scenarios. This exercise contributes in substantial ways to the identification of promising strategies to increase the penetration of alternative-fuel vehicles and fuel-efficient vehicles, reduce energy consumption, and reduce greenhouse gas emissions. Lastly, this research captures several complex interactions between vehicle ownership, location, and activity-travel decisions of individuals by estimating 1) a joint tour-based model of tour complexity, passenger accompaniment, vehicle type choice, and tour length, and 2) an integrated model of residential location, work location, vehicle ownership, and commute tour characteristics. The methodology used for estimating these models allows the specification and estimation of multi-dimensional choice model systems covering a wide spectrum of dependent variable types (including multinomial, ordinal, count, and continuous) and may be viewed as a major advance with the potential to lead to redefine the way activity-based travel model systems are structured and implemented.en
dc.description.departmentCivil, Architectural, and Environmental Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifier.slug2152/ETD-UT-2012-12-6687en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2012-12-6687en
dc.language.isoengen
dc.subjectActivity-based travel modelsen
dc.subjectVehicle type choiceen
dc.subjectMultidimensional choice modelingen
dc.subjectGreenhouse gas emissionsen
dc.subjectMicrosimulationen
dc.titleOn integrating models of household vehicle ownership, composition, and evolution with activity based travel modelsen
dc.type.genrethesisen
thesis.degree.departmentCivil, Architectural, and Environmental Engineeringen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen
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