Willingness-to-pay for shared automated mobility using an adaptive choice-based conjoint analysis during the COVID-19 period

Due to recent technological developments, both academia and the market have become interested in utilizing shared autonomous vehicles (SAVs). Gaining insight into preferences and priorities for using the next generation of shared mobility was the primary motivation for this study. The goal is to explore the willingness-to-pay (WTP) for a shared mobility service using a detailed user preference analysis for alternative automation types and incentive and policy options. The data was collected between March to May 2020 during the COVID-19 lock -down period in the United States via an online survey and analyzed by the Adaptive Choice-Based Conjoint Analysis (ACBC) method. The results of this study show that respondents distinctly preferred fully automated vehicles (SAVs) over shared human-driven vehicles (SHVs), tended to use a door-to-door service rather than a pooled service with a short walking distance, and were more interested in using advanced built-in amenities in the vehicle, not inclined to share their travel with others, and likely to pay less money to avoid potential delays. Comparing the results before and during the COVID-19 period showed that respondents afterward have markedly less willingness-to-share their trips with other riders compared to the survey analysis done before the COVID-19 period.