An Exploration of Short-Term Vehicle Usage Decisions

Vehicle choice decisions are Important to consider because they have implications on fuel consumption and greenhouse gas emissions. Much research has been done in the past regarding the types of vehicles that people own and how much they use each vehicle on annual basis. However, these are all long-term vehicle choice decision, and very little research has been done to explore short-term decisions. Short-term decisions provide information about how much vehicles in the household are being used at a day-level. In addition to the capturing the role of socio-demographics and economic factors on the short-term vehicle choices, the fine scale temporal analysis allows for exploring the relationship between vehicle choices and daily activity-travel engagement decisions which shape the selection and use of different vehicles in the household fleet. In the context of the short-term vehicle choices, there are two important choices to consider: the vehicle chosen from the household fleet to pursue the trip and the distance traveled. Further, there are important interrelationships between these two variables namely, vehicle choice may affect distance or distance may affect vehicle choice. Depending on the directionality of this relationship, there are different policy implications. It is important to understand these short-term decisions and their interrelationships so as to make informed decisions for creating efficient transportation systems, reducing fuel use, and decreasing greenhouse gas emissions. To explore the relationship between distance and vehicle type, data from the 2009 National Household Travel Survey (NHTS) was used. The thesis is divided into two parts. In the first part, findings from the examination of distance and vehicle type choice dimensions are presented. This section also explores the potential interrelationships between the choice dimensions. Further, the section also discusses findings from a comparative analysis of differences in vehicle choice behaviors across three metropolitan areas namely New York, Los Angeles, and Washington. The second part of the thesis explored the possibility that not one but both interdependencies could hold true but each for a different subgroup of the population to explain the short-term vehicle choice and usage behaviors. To this end, a latent segmentation approach was used to model both interdependencies and the corresponding interrelationships between vehicle type choice and distance within the same modeling framework. Both studies provide statistically significant and plausible results. Further, the results provide evidence in support of the importance of short-term vehicle choices and the importance of them in planning and policy analysis