Doctor of Philosophy (PhD)
First Committee Member
Number of Pages
Traffic forecasters traditionally rely on stability of populations and land uses to predict future trip data. In a number of rapidly growing cities of the western United States, where the population has been expanding at a pace far greater than the average community in the country, traditional travel demand models using the "Four Step Process" have been found to be not sufficiently accurate. The focus of this dissertation was to examine whether the predictive ability of traditional trip production models could be improved by the incorporation of accessibility and network variables, when applied to a rapidly growing region. The variables examined were developed on a disaggregate, per household basis using geographic information systems. The purpose of this research was to identify the factors which significantly affect trip production for a rapidly growing area, and to develop a regression model that improves upon the accuracy of trip production models that incorporate traditionally used socioeconomic variables; The travel survey data used in the research was taken from two household travel surveys, from the years 1996 and 2005. The dependent variables in the trip production equations---total number of non-work trips and total number of home-based shopping trips per household---were recorded from the household travel surveys. The three traditionally-used independent variables input into trip production regression equations---the number of persons in each household, the number of vehicles available for use by each household, and the household income---were also taken from the household travel surveys. Data were obtained from Clark County and used to develop additional independent variables. Once the development of variables was completed, regression equations were calibrated. The trip production models were then evaluated statistically, and observations were made; It was concluded that accessibility and transportation network variables can be developed on a disaggregate, per household basis for inclusion into trip production models. Whether or not such models created with the additional variables predict future trip production more effectively than models containing traditional variables proved inconclusive. However, by including the accessibility and transportation network variables in trip production equations, growth can be included in trip generation models.
Accessibility; Accessibility Measures; Developing; Incorporating; Measures; Models; Production; Rapidly; Region; Travel Demand; Trip; Trip Production
University of Nevada, Las Vegas
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Green, John Gregory, "Development of trip production models incorporating accessibility measures for a rapidly developing region" (2008). UNLV Retrospective Theses & Dissertations. 2788.