  In this paper we propose and solve a real options model for the optimal
adoption of an electric vehicle. A policymaker promotes the abeyance of
fossil-fueled vehicles through an incentive, and the representative
fossil-fueled vehicle's owner decides the time at which buying an electric
vehicle, while minimizing a certain expected cost. This involves a combination
of various types of costs: the stochastic opportunity cost of driving one unit
distance with a traditional fossil-fueled vehicle instead of an electric one,
the cost associated to traffic bans, and the net purchase cost. After
determining the optimal switching time and the minimal cost function for a
general diffusive opportunity cost, we specialize to the case of a
mean-reverting process. In such a setting, we provide a model calibration on
real data from Italy, and we study the dependency of the optimal switching time
with respect to the model's parameters. Moreover, we study the effect of
traffic bans and incentive on the expected optimal switching time. We observe
that incentive and traffic bans on fossil-fueled transport can be used as
effective tools in the hand of the policymaker to encourage the adoption of
electric vehicles, and hence to reduce air pollution.
