Influence of Choice Experiment Designs on Eliciting Preferences for Autonomous Vehicles

Abstract

Due to potentially high initial purchase prices, automation is likely to hit the transportation market as on-demand autonomous taxis for short-term rentals. In this study, welfare measures associated with the use of autonomous taxis were estimated by conducting discrete choice experiments (DCEs) in New York City. Aiming at more realistic choice scenarios, a method for pivot-efficient designs is proposed and tested that exploits the distribution of attribute levels; however, the analysis suggests the use of a simpler pivot-efficient design with average attributes of reference alternatives. In our sample, New Yorkers were willing to pay on average $3 less per self-driven trip. This reduction in the willingness to pay is coming from the fact that in current conditions not having a driver may be perceived as a nuisance rather than a convenience.

Keywords: discrete choice experiment, pivot-efficient design, willingness to pay