Accelerating the adoption of automated vehicles by subsidies: A dynamic games approach

Abstract Early deployment of automated vehicles (AVs) may likely cause a loss of efficiency in the transportation system. However, after there are a sufficient number of such vehicles in the traffic stream, many benefits can be realized. It thus appears sensible to provide subsidies to promote the early adoption of AVs and shorten the transition period. This paper investigates an optimal subsidy policy that accelerates the deployment of AVs from lower to higher market penetration rates. The policy can maximize the government agency’s expected total payoff associated with the AV deployment. The main contribution is a dynamic games approach that considers the uncertainty in the market forecast and the information asymmetry between the government agency and the subsidized entities.