# Measurement of Regional Electric Vehicle Adoption Using Multiagent Deep Reinforcement Learning
## 2 Related Work  
### Current EV Incentive and Policy Program  
Incentives for customers to purchase EVs come in the form of either federal or state-specific programs. Federal funding for EV subsidies was first allocated during the [PERSON] Administration and has been heavily promoted under the [PERSON]. Initial incentives aimed at promoting the purchase of Plug-in Electric Vehicles (PEVs) were introduced in the American Clean Energy and Security Act of 2009. However, these were diversified a year later as PHEVs and BEVs entered the market [32].  
The tax credit for new purchases could be as high as $7500 [32]. As of now, the amount of tax credit remains the same. According to the U.S. Department of Energy [33], all EVs, whether PHEVs or BEVs, are eligible for a tax credit of up to $7500 if purchased in or after 2023. Pre-owned vehicles purchased in or after 2023 also qualify for a tax credit of up to $4000, provided the purchase price is less than $25,000. These credits may be increased through regional policy portfolio programs. The federal tax credit has significantly impacted consumers' decisions to switch from ICEVs to EVs [34]. However, the effect is not uniformly distributed. Interestingly, the incentive might not significantly influence the purchasing decision of buyers interested in luxury EVs [34].  
State-specific programs vary in incentives, ranging between $2500 and $7500. While the premise of these programs is generally robust, specific criteria must be met for applicants to receive the total amount. [PERSON] et al. [19] pointed out that current incentive programs are solely targeted at first adopters and need to take into account the existence of second-hand EV owners. Factors such as income levels and household characteristics, including family type and number of children, can pose potential barriers preventing applicantsfrom receiving the maximum incentive [35]. A study by [PERSON] et al. [35] performed an equity analysis on state-level Income Tax Credit (ITC) programs. They found that high-income households with fewer children were typically more likely to receive the total amount. However, this trend can vary based on the state's tax treatments, tax rate structures, and thresholds. Overall, incentives have a significant impact on increasing EV sales [17; 36]. [PERSON] et al. [36] examined both the impacts of monetary and non-monetary incentives on EV sales across all states in the U.S., compiling data on 198 different incentives. In addition to ITCs, other factors such as fleet credits, High-occupancy Vehicle (HOV) lane access, inspection exemptions, registration fee reductions, Time of Use (TOU) rates, and charging subsidies also contribute to the increase in EV sales.  
Most evaluations of EV incentives in the U.S. focus primarily on the state level [36; 37] or leading states [20; 22]. Subsidy and rebate programs are already in place, and there is a need for them. However, measuring their actual effect on adoption is often challenging [38]. While new guidelines limiting the $7500 tax credit under the Inflation Reduction Act have been announced, it will take years to finalize, and the outcome remains uncertain [39]. Meanwhile, policies ought to take into account the distinct characteristics of each city, underscoring localized strategies and solutions. We need a more diverse set of case studies to increase the probability of substantial EV adoption and overcome potential barriers [40] By simplifying real-world environments using reinforcement learning, our presented research framework will offer a nuanced understanding of EV adoption, enabling more effective incentive implementation.