Asset managers continue to prepare physical infrastructure investments needed to accommodate the emerging technologies, namely vehicle connectivity, electrification, and automation. The provision of new infrastructure and modification of existing infrastructure is expected to incur a significant amount of capital investment. Secondly, with increasing EV and CAV operations, the revenues typically earned from vehicle registrations and fuel tax are expected to change due to changing demand for vehicle ownership and amount of travel, respectively. This research estimated (i) the changes in highway expenditures in an era of ECAV operations, (ii) the net change in highway revenues that can be expected to arise from ECAV operations, and (iii) the changes in user equity across the highway user groups (vehicle classes). In assessing the changes in highway expenditures, the research developed a model to predict the cost of highway infrastructure stewardship based on current and/ or future system usage. <div><br></div><div>The results of the research reveal that CAVs are expected to significantly change the travel patterns, leading to increased system usage which in turn results in increased wear and tear on highway infrastructure. This, with the need for new infrastructure to support and accommodate the new technologies is expected to result in increased highway expenditure. At the same time, CAVs are expected to have significantly improved fuel economy as compared to their human driven counterparts, leading to a decrease in fuel consumption per vehicle, resulting in reduced fuel revenues. Furthermore, the prominence of EVs is expected to exacerbate this problem. This thesis proposed a revision to the current user fee structure to address these impacts. This revision contains two major parts designed to address the system efficiency and equity in the near and long term. For the near term, this thesis recommended a variable tax scheme under which each vehicle class pays a different fuel tax rate. This ensures that both equity and system efficiency are improved during the transition to ECAV. In the long term, this thesis recommended supplementing the fuel tax with a distance based VMT tax, applicable to electric vehicles.<br></div>

<p>  </p> <p>The trucking industry seems to be resistant to electrification, even though truck electrification can lead to large societal as well as user benefits. This dissertation develops a framework to inform policy making and enhance electric vehicle (EV) preparedness in the trucking industry through the study of two interrelated elements: (a) the adoption of electric trucks and (b) the appropriate implementation of electric truck technology. These two elements cover the user perspective, which is not adequately studied, and the agency perspective, which is pivotal in the decision-making process. Specifically, this study addressed the following research questions: (i) which factors affect the purchase decisions of truck fleet managers or owners for electric trucks? (ii) what is the ranking of and interrelationships between the barriers to the adoption of electric trucks? (iii) which location criteria should be considered for the strategic implementation of dynamic wireless charging (DWC) in a freight transportation network and where should this technology be located based on these criteria, and (iv) what is the impact of electric truck adoption on highway revenue and potential of alternative funding mechanisms to recover the revenue loss?</p> <p>For the adoption of electric trucks, a stated preference survey was designed and distributed online to truck fleet managers/owners in the U.S., gathering 200 completed responses. Statistical and multi-criteria decision-making approaches were employed to identify the factors that affect the purchase intentions of truck fleet managers and explore the barriers to electric truck adoption. The results showed that the purchase intentions of truck fleet managers are affected by trucking firm and truck fleet characteristics, behavioral factors/opinions regarding electric trucks, and awareness of innovative charging technologies. Furthermore, electric truck adoption would be accelerated if stakeholders focused on the barriers related to the business model, product availability, and charging time. Additionally, electric truck adopters and non-adopters may not be viewed as one homogenous group, since differences were found in the ranking and interrelationships of barriers to electric truck adoption between these two groups. </p> <p>The implementation of electric truck technology was examined based on the truck fleet managers’ survey, secondary data sources and the case of Indiana, U.S. A multi-criteria decision-making spatial approach was proposed to identify the candidate locations for the deployment of DWC. It was concluded that the most suitable locations for DWC lanes were on interstates, near airports and ports and away from EV charging stations. A data-driven framework was also developed to quantify the impact of electric truck adoption and estimate the optimal fee for each truck to recover the revenue loss. Using the market penetration levels estimated based on the survey data collected, the average annual fuel tax revenue loss for Indiana was approximately $349M. To maintain the same tax revenue per vehicle, annual fees ranging from $969 (in 2021) to $1,243 (in 2035) for single-unit trucks and $6,192 to $7,321 for combination trucks would be needed. To address public relations problems of EV fee implementation, this study also discussed alternative mitigation measures: a vehicle-miles-traveled fee and a pay-as-you-charge fee.</p> <p>In summary, this dissertation contributes to the body of literature by providing significant insights regarding the perspectives of truck fleet managers for electric trucks as well as a comprehensive list of all the location criteria for DWC. The proposed frameworks and study findings can be used by policymakers and other major stakeholders of the EV ecosystem to frame certain strategies to accelerate electric truck adoption, identify the most suitable locations for charging infrastructure, better understand the impact of electric trucks on the highway revenue, and provide the groundwork for developing EV roadmaps.</p>