Americans’ plans for acquiring and using electric, shared, and self-driving vehicles and costs and benefits of electrifying and automating U.S. bus fleets

This thesis is divided into three parts. The first part surveys 1,426 Americans to gauge how technology availability and costs influence public opinion, vehicle ownership decisions, travel, and location choices, and then adjusted all results for population weights, to offset any sample biases in U.S. demographics. Example results include average willing to pay (WTP) for full automation (on a newly acquired vehicle) of $3,252 with a very high standard deviation of +/- $3,861 with a human-driven-vehicle (HV) mode option and $2,783 (standard deviation = $3,722) without that option (AV driving only). These averages rise to $3685 and $3112 for AV with and without an HV option, respectively, if responses of zero WTP are removed. Americans’ average WTP for use of shared autonomous vehicles (SAVs) is $0.44 per mile (standard deviation = $0.43). If given the option, Americans expect to set their vehicles in AV (self-driving) mode 36.4% of the time. Respondents believe about 20% of AV miles should be allowed to travel empty, for both privately-owned AVs and shared AV fleets, which would be quite congesting in urban regions at many times of day. Among those likely to move their home in the next few years, 15.5% indicate that availability of AVs and SAVs would shift their new home locations relatively closer to the city center, while 10% indicate further away; the other 74.5% do not expect such technologies to influence their home location choices. The second part develops a simulation-based framework to predict fleet evolution and VMT through year 2050, based upon regression models calibrated with the results of the survey the previous part of this thesis. Multiple scenarios are tested to analyze the effect of the difference in willingness to for AVs when the option to retain human driving capabilities in AVs is available vs. when it is not, as well as the effect of different rates of decline in the AV technology price premium. Both are shown to have a substantial effect on AV adoption rates. Home location is also analyzed, and a slight migration away from city centers is observed. The third part uses Capital Metro’s transit bus fleet in Austin, Texas to analyze the costs and effects of implementing electric and autonomous technologies in transit bus fleets. Qualitative effects are discussed, financial effects are analyzed, and potential adoption schedules are developed. It is found that electric buses will become competitive with diesel in a few years, or immediately with a modest rise in diesel fuel prices within the range of historical levels. Autonomous buses will offer significant costs savings upon availability, and their implementation could ease the near-term cost burden associated with electric bus adoption in the near term before a substantial drop in electric technology price or rise in diesel fuel prices.