Results from a recent consumer survey were thoroughly analyzed in relation to willingness to adopt and willingness to pay (WTP) for different autonomous vehicle (AV) features. Four different levels of automation were considered including basic vehicles, adding advanced features, partial automation, and full automation. A structural equations model with latent variables was employed, which simultaneously regressed adoption and WTP levels against a variety of available variables including socioeconomic and demographic attributes, private car usage habits, and attitudinal preferences/personal opinions. To address the endogeneity in personal attitudes, these variables were added to the model as latent factors. Accordingly, the analysis revealed four major latent attitudinal factors, respectively labeled as “joy of driving,”“mode choice reasoning,”“trust,” and “technology savviness.” Model results indicated that those who enjoy driving were the hardest to persuade towards AV adoption or to pay for automated features. On the other hand, technology savvy people showed higher tendency towards AV adoption. When it comes to factors affecting mode choice including travel time, travel cost, and functionality, people are willing to pay more for automated features when they believe that these features and services will provide them better utility, in relation to time and cost savings, convenience, stress reduction, and quality of life, and so forth. Interestingly, individuals with trust concerns showed higher WTP values, which may indicate that the market believes autonomous vehicles will bring more privacy and protection, at least compared with existing shared mobility or public transit options.
How do activities conducted while commuting influence mode choice? Using revealed preference models to inform public transportation advantage and autonomous vehicle scenarios
