Ridesharing transportation services as the leading transport systems in recent years have already invested in shared autonomous vehicles (SAVs) as the next generation of shared transportation systems. Recent years have seen a noticeably accelerating rate in utilizing advanced communications and mapping service technologies that opened new doors to the ridesharing operators to provide a better quality of service to the users; therefore, it is necessary to have a better insight in-to the preferences of the users for using SAVs. This study aims to identify individuals’ preferences for using SAVs and investigate related demographic characteristics and travel behavior attributes. An online Adaptive Choice-Based Conjoint (ACBC) survey will be designed and implemented between March to May 2020 in the United States. Then a series of mixed logit models (MXLs) were used to estimate participants’ preferences. The results show that females are more tended to use door-to-door services, younger riders are more interested in using SAVs and also accept longer travel times, and riders with high-income levels are willing to use SAVs with higher equipment and convenience door-to-door service and not share their trips with others. Furthermore, more educated riders are more likely to use door-to-door service, select a service with shorter travel time, and pay a little more money to insure their trip against possible delays.
User Preferences for Automated Shared Mobility Services: An Alternative-Specific Mixed Logit Regression Approach
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 21 , 2 ; 331-348
2023-08-01
18 pages
Article (Journal)
Electronic Resource
English
Shared autonomous vehicle , Autonomous vehicle , Mixed logit model , Automated mobility , Travel behavior Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , Civil Engineering , User Interfaces and Human Computer Interaction
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