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How do college students perceive future shared mobility with autonomous Vehicles? A survey of the University of Alabama students
- Source :
- International Journal of Transportation Science and Technology, Vol 11, Iss 2, Pp 189-204 (2022)
- Publication Year :
- 2022
- Publisher :
- KeAi Communications Co., Ltd., 2022.
-
Abstract
- University students are young, open to new technologies, and their perceptions of the Shared Autonomous Vehicles (SAVs) may indicate their travel behaviors in the future. College towns in small urban or suburban areas offer researchers a unique environment to understand the travel behaviors of future commuters, and test emerging mobility services, such as SAVs. The study performs a survey with the aim of understanding university student perception regarding SAVs. The survey was conducted among the University of Alabama students in Tuscaloosa. The key survey questions include their knowledge and attitudes about AV and shared mobility. The results showed 97% of respondents are aware of AVs, but only 41% know specific automation technologies. As for shared mobility services, 98% of respondents are familiar with Uber and Lyft services. The survey also asked survey participants to indicate their Willingness-To-Pay (WTP) for hypothetical SAV services in three price scenarios. The prices were assumed as relative to the cost of using ride-hailing services with human drivers such as Uber and Lyft. Random parameter ordered logit models were developed to uncover the correlates of the WTP for SAV services. The models identified significant relationships between the WTP and various factors related to respondents’ socio-demographics, awareness of AV companies, and experiences with human-driver ride-hailing services. The awareness of AV companies and ride-hailing services is positively related to the WTP for SAV services. Students who know more AV companies appear to have a greater WTP, and students who are heavy users of Uber or Lyft services are also likely to SAV users in the future. Significant variations were also found in model estimates, indicating that some relationships could vary significantly across observations due to the unobserved heterogeneity. The findings offer insights to decision-makers and investors trying to estimate the market potential of emerging mobility services with AVs.
Details
- Language :
- English
- ISSN :
- 20460430
- Volume :
- 11
- Issue :
- 2
- Database :
- Directory of Open Access Journals
- Journal :
- International Journal of Transportation Science and Technology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.8c2730a8c9524b30913d76a3569778e3
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.ijtst.2021.11.006