Autonomous vehicles (AVs) and shared mobility constitute two of the “Three Revolutions” that portend major changes to surface transportation. AVs promise to reduce accidents, expand accessibility, and decrease congestion, while shared mobility provides the benefits of automotive transportation without requiring the purchase of a vehicle or the ability to drive it. Despite great promise to alleviate the negative externalities imposed by transportation, there remains much to be understood about the combined diffusion and impact of AVs and shared mobility. There is little demonstrated experience and application of AVs to the public, and how and where people would use automated shared mobility relative to their current travel is largely unknown. This study advances our understanding by utilizing an intercept survey of 232 respondents in Ann Arbor, Michigan who had made a discretionary trip to one of two central and two suburban locations. The novel approach of using intercept surveys allows us to gather more valid data about the willingness of respondents to replace the mode they just used for either a privately owned or a shared AV and do so for the trip purpose most conducive to using such a vehicle. We incorporate descriptive and spatial analyses and then utilize multinomial logit models to predict the factors influencing the encouragement or discouragement of substituting a private and a shared AV for their previous trip. We found that active mobility and transit trips work in competition with private AVs, while youth encourages interest. Meanwhile, active mobility, increasing age, and one of our measures of density discourage interest, while female respondents and the same measure of density increase interest. The results suggest that future efforts to facilitate the adoption of shared AVs target areas of the city that are relatively dense and residents in these areas where a shared AV would enhance individuals’ mobility.
Modeling Determinants of Autonomous Vehicle Utilization in Private and Shared Ownership Models
2025
Article (Journal)
Electronic Resource
Unknown
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