Autonomous vehicles use sensing and communication technologies to navigate safely and efficiently with little or no input from the driver. These driverless technologies will create an unprecedented revolution in how people move, and policymakers will need appropriate tools to plan for and analyze the large impacts of novel navigation systems. In this paper we derive semi-parametric estimates of the willingness to pay for automation. We use data from a nationwide online panel of 1,260 individuals who answered a vehicle-purchase discrete choice experiment focused on energy efficiency and autonomous features. Several models were estimated with the choice micro-data, including a conditional logit with deterministic consumer heterogeneity, a parametric random parameter logit, and a semi-parametric random parameter logit.

Key findings

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The average household is willing to pay a significant amount for automation: about $3,500 for partial automation and $4,900 for full automation.

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There is "substantial heterogeneity in preferences for automation, where a significant share of the sample is willing to pay above $10,000 for full automation technology while many are not willing to pay any positive amount for the technology."

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The semiparametric random parameter logit estimates suggest that the demand for automation is split approximately evenly between high, modest and no demand, highlighting the importance of modeling flexible preferences for emerging vehicle technology.

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