Fueling Alternatives: Evidence from Naturalistic Driving Data

We use naturalistic driving data to analyze the refueling behavior of drivers. The data come from a year-long study in which drivers were provided with experimental vehicles to use for seven weeks. We use data logged during the experiment to identify the time and location of refueling stops. With this dataset, we estimate a discrete choice model for the driver’s choice of refueling location. We show that drivers make a trade-off between the price of fuel and the time taken to deviate from their route to arrive at the chosen gas station. People differ in their willingness to travel out of their way to pay less for gasoline. Based on the estimated model of refueling demand, we simulate the willingness of drivers to adopt alternative fuel vehicles under different assumptions about the density of the alternative fueling network, and we use these results to understand the role of subsidies in encouraging alternative fuel vehicle adoption. We show that driver heterogeneity has important implications for the design of policies to promote alternatives to gasoline. ∗Department of Economics, University of Arizona. Email: [email protected] †Department of Economics, University of Michigan. Email: [email protected].