Transit user perceptions of driverless buses
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This paper reports the results of a stated preference survey of regular transit users’ willingness to ride and concerns about driverless buses in the Philadelphia region. As automated technologies advance, driverless buses may offer significant efficiency, safety, and operational improvements over traditional bus services. However, unfamiliarity with automated vehicle technology may challenge its acceptance among the general public and slow the adoption of new technologies. Using a mixed logit modeling framework, this research examines which types of transit users are most willing to ride in driverless buses and whether having a transit employee on board to monitor the vehicle operations and/or provide customer service matters. Of the 891 surveyed members of University of Pennsylvania’s transit pass benefit program, two-thirds express a willingness to ride in a driverless bus when a transit employee is on board to monitor vehicle operations and provide customer service. By contrast, only 13% would agree to ride a bus without an employee on board. Males and those in younger age groups (18–34) are more willing to ride in driverless buses than females and those in older age groups. Findings suggest that, so long as a transit employee is onboard, many transit passengers will willingly board early generation automated buses. An abrupt shift to buses without employees on board, by contrast, will likely alienate many transit users.
KeywordsAutomated vehicles Driverless buses Mixed logit Stated preference survey Willingness to ride
This research was supported by a grant from the U.S. Department of Transportation’s Dwight David Eisenhower Transportation Fellowship Program. Technologies for Safe and Efficient Transportation, a U.S. Department of Transportation University Research Center, also supported this research.
XD: Literature review support, modeling and statistical analysis, writing and editing. MD: Design and management of survey, literature review, writing and editing. EG: Research design support, development of modeling framework, writing and editing.
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