Master of Science / Department of Computer Science / Doina Caragea / The goal of the project is to create a database for storing the National Household Travel Survey (NHTS) data, and a user interface to query the database. Currently, the survey data is stored in excel files in the CSV format, which makes it hard to perform complex analyses over the data. Analyses of interest to transportation community include comparisons of the trips made by urban household to those made by rural household, finding the average trip time spent based on ethnicity, the total travel time of a particular household, the preferred vehicle by a specific household, average time spent per shopping trip, etc. The tool designed for the purpose of querying the NHTS database is a Python-based Web application. Django is used as the Web framework for this project and PostgreSQL is used for the back-end purpose. The user interface consists of various drop-down lists, text-boxes, buttons and other user interface components that facilitate querying the database and presenting the results in formats that allow easy interpretation. FusionCharts Django-Wrapper and FusionCharts Jquery-Plugin are used to visualize the data in the chart form. A Codebook of the NHTS dataset is also linked for the reference purpose at any point for the user. The tool built in the project allows the user to get a deeper understanding of the data, not only by plotting the data in the form of line charts, bar charts, two column graph, but also by providing the results of the queries in the CSV format for further analysis.

Individuals who use wheelchairs or who have other mobility challenges often are unable to access modern mobility systems "“ including application-based ride hailing and on-demand microtransit. Even designing a system targeted at these users is challenging, given the limited prior analysis of their travel behavior and activity patterns. Simulation tools are used by cities around the world to understand novel and complex transportation systems, yet few are including the needs of users with disabilities in these simulation studies. This thesis examines the travel patterns of wheelchair users from the 2017 National Household Travel Survey and presents a model of daily activity pattern choice of respondents who self-identify as using a wheelchair. This thesis discusses the application of a wheelchair status variable in the activity-based travel demand model ActivitySim and measures its effect on individual and household daily activity pattern choice. Wheelchair use is estimated to reduce the utility of a work daily activity pattern by 1.9 points relative to a home pattern for full time workers and 3.4 for part time workers. Including the effect of wheelchair use in a regional daily activity pattern model resulted in 21.9 percent of wheelchair users changing to a home activity pattern relative to a base scenario not including wheelchair use. Lastly, the thesis evaluates the performance of an on-demand, accessible mode for users with wheelchairs in the agent-based microsimulation BEAM. This simulation showed that demand for such a service increases linearly with fleet size and wait time remains constant, though further scenario refinement and research is necessary.

Literature on transportation planning and modeling is replete with the concept of a travel time budget. According to this concept, average daily travel times tend to be relatively constant. However, evidence from the 1983 Nationwide Personal Transportation Survey and the 2001 National Household Travel Survey suggest that the average daily travel time has increased by 1.9 minutes per year. Understanding travel time expenditures is important for forecasting travel demand, especially future vehicle miles of travel. Historically, travel demand models considered vehicle availability and income as limiting factors for travel, but going forward time may be the constraint. As individuals spend more time devoted to travel, less time will be available for other activities. Therefore, future travel demand is dependent on people's willingness to spend time traveling. Growth of travel demand has been per capita based not just population based. This has been enabled by several cultural trends, including fewer children to care for; specialization of activities; multitasking during travel, for example, cell phone use can add value to travel time; seeking socialization away from home; and increases in real income enabling more activity participation. This study will report the increase in average daily travel time expenditures and analyze the increase by various demographic segments of the population. Travel time expenditures are also related to activity participation, the characteristics of the area, and many other interrelated factors at the person level. Aggregate values will be used to investigate the general relationships between daily travel time expenditures and socio-demographic characteristics. Careful consideration of the implications of the increase in travel time, as well as the changes in society that have contributed to these changes will be explored. The increase in travel time expenditures is likely to play a significant role in future travel demand growth in the United States and will impact the performance of the transportation system going forward. If travel time expenditures continue to grow, the hope for slowing VMT growth may not materialize. Understanding the mechanics of why people are traveling more will aid planners and modelers in estimating future travel demand.

The Texas state gas tax has been 20.0 cents per gallon since 1991, and the federal gas tax has been 18.4 cents per gallon since 1993. The gas tax is not only stagnant, but depreciating in value due to inflation. Thus, damage is being done to the infrastructure but the money needed to maintain and improve roadways is not being adequately generated. One proposed alternative to the gas tax is the creation of a vehicle miles traveled (VMT) fee; with equity being a crucial issue to consider. This research used 2009 National Household Travel Survey (NHTS) Texas data to consider the equity impacts surrounding four VMT fee scenarios. Data were filtered and weighted to reflect results representative of Texas vehicle-owning households in 2008. Each scenario was run both statically and dynamically under the assumption that the VMT fee would replace the state gas tax. An assessment of the relative vertical equity of each scenario was made by calculating the Gini Coefficient associated with the proportion of state gas tax or VMT fee revenue generated by each household income level quintile. Results indicate that all VMT fee scenarios are essentially as equally vertically equitable than the current state gas tax system. Scenario 4 was designed to be inherently horizontally equitable because the per mile fee associated with each roadway type (urban or rural) was assessed to all vehicles driven on these roadway types at a rate calculated to generate needed funds to address the mobility and infrastructure needs of that roadway type. Scenario 3, a scenario favoring vehicles with high fuel efficiency, was found to be the least horizontally equitable. Scenarios 2-4 were able to generate additional revenue desired to meet the infrastructure and mobility needs of Texas set forth by the 2030 Texas Transportation Needs Committee. The large fee increase necessary to achieve the desired additional revenue may not be popular or possible. However, an evaluation of the philosophy governing each scenario designed to generate additional revenue is informative when it comes to equity impacts. No one VMT fee scenario affects all household income levels and geographic locations uniformly and it was not the goal of this research to design an equitable VMT fee scenario. Rather, the effect of each scenario on 2008 Texas vehicle-owning households disaggregated by household income level and geographic location are presented and left to the discretion of elected officials to decide which VMT fee, if any, would be best for their constituents.

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