@article{kaplan2023,
author = {Leah Kaplan and John Paul Helveston},
title ={Undercutting Transit? Exploring Potential Competition Between Automated Vehicles and Public Transportation in the United States},
journal = {Transportation Research Record},
volume = {0},
number = {0},
year = {2023},
doi = {10.1177/03611981231208976},
URL = {https://doi.org/10.1177/03611981231208976},
}Undercutting Transit? Exploring potential competition between autonomous vehicles and public transportation in the U.S.
Kaplan, Leah & Helveston, John P. (2023) “Undercutting Transit? Exploring potential competition between autonomous vehicles and public transportation in the U.S.” Transportation Research Record. DOI: 10.1177/03611981231208976
Abstract:
Automated vehicles (AVs) have the potential to dramatically disrupt current transportation patterns and practices. One particular area of concern is AVs’ impacts on public transit systems. If vehicle automation enables significant price decreases or performance improvements for ride-hailing services, some fear that it could undercut public transit, which could have significant implications for the environment and transportation equity. The extent to which individuals adopt automated transportation modes will drive many system-level outcomes, and research on public preferences for AVs is immature and inconclusive. In this study, we used responses from an online choice-based conjoint survey fielded in the Washington, D.C. metropolitan region (N = 1,694) in October 2021 to estimate discrete choice models of public preferences for different automated (ride-hailing, shared ride-hailing, bus) and nonautomated (ride-hailing, shared ride-hailing, bus, rail) modes. We used the estimated models to simulate future marketplace competition across a range of trip scenarios. Respondents on average were only willing to pay a premium for automated modes when a vehicle attendant was also present, limiting the potential cost-savings that AV operators might achieve by removing the driver. Scenario analysis additionally revealed that for trips where good transit options were available, transit remained competitive with automated ride-hailing modes. These results suggest that fears of a mass transition away from transit to AVs may be limited by people’s willingness to use AVs, at least in the short term. Future AV operators should also recognize the presence of an AV attendant as a critical feature for early AV adoption.
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