Accelerating the Adoption of Automated Vehicles by Subsidies: A Dynamic Games Approach

26 Pages Posted: 12 Dec 2018 Last revised: 1 May 2019

See all articles by Qi Luo

Qi Luo

Industrial Engineering, Clemson University

Romesh Saigal

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Zhibin Chen

University of Michigan at Ann Arbor

Yafeng Yin

University of Michigan, Ann Arbor

Date Written: October 30, 2018

Abstract

Early deployment of automated vehicles (AVs) may likely cause a loss of efficiency of 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 utility because of 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.

Keywords: Automated vehicles, subsidy policy, dynamic Stackelberg games, diffusion of innovations.

Suggested Citation

Luo, Qi and Saigal, Romesh and Chen, Zhibin and Yin, Yafeng, Accelerating the Adoption of Automated Vehicles by Subsidies: A Dynamic Games Approach (October 30, 2018). Available at SSRN: https://ssrn.com/abstract=3275580 or http://dx.doi.org/10.2139/ssrn.3275580

Qi Luo (Contact Author)

Industrial Engineering, Clemson University ( email )

227B Freeman Hall
Clemson, SC 29634
United States

Romesh Saigal

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Zhibin Chen

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Yafeng Yin

University of Michigan, Ann Arbor ( email )

2350
Hayward Street
Ann Arbor, MI 48109
United States

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