UC Davis Institute of Transportation Studies

Strong policies are needed to accelerate the zero-emission vehicle (ZEV) transition so that it occurs at a pace in line with international climate goals. The purchase price of new vehicles tends to be the variable that most affects consumer decisions. With urgency for a ZEV transition, fiscal pressure for governments can be high as rebates for consumers and incentives supporting manufacturers in the switch to ZEV technologies will be needed for a mass-market transition. Fees on high-polluting vehicles—and rebates on clean ones—have become an effective and increasingly common strategy in European countries. The feebate mechanism can raise the necessary capital for financing a ZEV transition in combination with other regulatory mechanisms. This paper reviews and assesses feebate design types, issues, and implementation strategies in France, Germany, Italy, Sweden, and the United Kingdom. These examples show that feebates can be designed in a variety of ways to meet unique policy objectives and that periodic adjustments are helpful in achieving goals. Among twelve design considerations for an effective feebate, the authors find that: (1) focusing on a single fee parameter, such as CO2 emissions, can be a simple yet effective mechanism; (2) a continuous functional form for the fee and a stepwise rebate are likely to be most effective in driving EV adoption; and (3) pure feebates, where fee revenue funds EV incentives by program design, provide certainty for manufacturers, regulators, and consumers.

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The United States (US), under the Biden Administration, has set a goal of reaching a 50% sales share for zero-emission vehicles by 2030. The administration is pursuing a combination of aggressive fuel economy and greenhouse gas performance standards along with tax credits for consumers who purchase electric vehicles (EVs). Given the anticipated high costs of the EV transition and limited public funds, policy mechanisms that generate extra-budgetary funding are enticing. Feebates—where a fee charged on some purchases is used to offer a rebate for others—can serve as a self-sustaining tool. Feebates have been attempted at the state and federal level in the US but did not pass legislatures due to a lack of political support for levying a fee on internal combustion engine (ICE) vehicles. However, as governments face increasing fiscal constraints, there is greater support for self- funding EV incentive programs. Feebate policies can provide certainty for both producers and consumers to facilitate a steady transition to sustainable transportation. This paper assesses the potential utility of feebates for shaping the US light-duty vehicle market. The analysis demonstrates that: (1) revenue-neutral incentive systems are possible and (2) revenue-neutrality can be achieved with relatively low fees on ICE vehicles to support economic equity among buyers. From an industry perspective, market certainty can be created by incorporating fuel economy targets into a fee schedule as pivot points and allocating fees to finance rebates. This would likely influence industry investment decisions in ways that increase EV production and model availability.

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Vehicle automation represents a new safety frontier that may necessitate a repositioning of our safety oversight systems. This white paper serves as a primer on the technical and legal landscape of automated driving system (ADS) safety. It introduces the latest AI and machine learning techniques that enable ADS functionality. The paper also explores the definitions of safety from the perspectives of standards-setting organizations, federal and state regulations, and legal disciplines. The paper identifies key policy options building on topics raised in the White House’s Blueprint for an AI Bill of Rights, outlining a Blueprint for ADS safety. The analysis concludes that potential ADS safety reforms might include either reform of the Federal Motor Vehicle Safety Standards (FMVSS), or a more holistic risk analysis “safety case” approach. The analysis also looks at caselaw on liability in robotics, as well as judicial activity on consumer and commercial privacy, recognizing that the era of AI will reshape liability frameworks, and data collection must carefully consider how to build in accountability and protect the privacy of consumers and organizations. Lastly, this analysis highlights the need for policies addressing human-machine interaction issues, focusing on guidelines for safety drivers and remote operators. In conclusion, this paper reflects on the need for collaboration among engineers, policy experts, and legal scholars to develop a comprehensive Blueprint for ADS safety and highlights opportunities for future research.

This study explores the factors associated with observed changes in transportation mode shares over the period from 2012 to 2017 (corresponding with the period between the two most recent household travel surveys conducted in California). In contrast with the goals of the California Department of Transportation and the State Transportation agency, walking, biking, and using transit all decreased during this period, and driving and the use of personal vehicles increased. There are a number of factors typically associated with transportation mode choices, including socio-demographics, attitudes, life stages, land use and infrastructure availability. Further, large scale events may also have an effect on travel trends; for example, the Great Recessionmay have impacted individuals’ ability to own a personal vehicle and therefore increased the use of alternative means of transportation during the years leading up to our survey period. Similarly, the 2013 passage of legislation allowing for non-citizens to obtain a driver’s license in the state of California, may have impacted mode shares over the study period. This paper compares these and other factors impacting mode shares in 2012 and in 2017 to answer part of the question about why we see this decrease in the use of active modes over this period and what types of planning, programs, and policy actions may help to reverse this trend and get California back on track to increase walking, biking and the use of public transit.

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Procurement of more environmentally sustainable materials for civil infrastructure can be supported using environmental product declarations (EPDs). An EPD is a standardized label that is a scientifically sound way to communicate the potential environmental impacts and selected resource use and waste production flows from all or part of the life cycle of a product. To be called a Type III EPD, the life cycle assessment (LCA) for products used in civil infrastructure must be performed in accordance with ISO standards and the relevant product category rule (PCR) for the product type. Most EPDs for civil infrastructure materials in North America are “cradle-to-gate”, i.e., they include the impacts from the extraction of raw materials from the earth and end at the point at which the product is ready to leave the gate of the last manufacturing location. The steps leading to publication of an EPD include: 1) Developing the PCR, 2) Developing the LCA for the EPD, 3) Creating the EPD, and 4) Verification and publishing of the EPD. Industry-average, regional-average, product-specific, and facility-specific EPDs—with differing specificity to a particular product—are used for different purposes. EPDs are a source of data for materials impacts for use in assessment of the complete life cycle. They provide information to identify changes in impacts that can be made early in the materials production. They also can be used to help procure lower impact materials. This white paper discusses benefits of using EPDs and makes recommendations for improving their validity. Several areas needing improvement in current use in procurement are identified and recommendations are presented for improving the use of cradle-to-gate EPDs in transport infrastructure construction materials procurement and to provide input to complete life cycle pavement LCA to support decision-making.

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Biodiesel and hydrotreated renewable diesel (RD)—or collectively biomass-based diesel (BBD)—have become integral components of compliance with policies aiming to reduce U.S. transportation sector greenhouse gas emissions. Such policies include the U.S. Renewable Fuel Standard (RFS), California’s Low Carbon Fuel Standard (LCFS), and Oregon’s Clean Fuel Program (CFP). These policies, along with a federal Blender’s BBD Tax Credit (BTC), provide financial incentives for BBD. In this white paper, the authors study pass-through of implicit taxes and subsidies, introduced by federal and state policies, to a variety of diesel and soy biodiesel fuel prices in the context of the U.S. diesel sector, focusing on fossil diesel and soy biodiesel. They apply time series methods techniques to estimate how a variety of diesel fuel price spreads across the country and in California and Oregon responds to changes in the implicit taxes placed on petroleum diesel and the implicit subsidies awarded to biodiesel. The results presented in this paper point to some inefficiencies in the RFS, LCFS, and CFP. The primary contribution of this paper was providing the first set of estimates of pass-through of LCFS implicit taxes and subsidies, and doing so for the diesel sector, a critical player in LCFS compliance.

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The expansion of automation in the U.S. economy is increasingly tangible and will presumably entail positive and negative impacts that are not yet well understood. In the freight sector, there is uncertainty about how and when automation will impact labor. Beyond this, there are further unknowns about what the impacts will be on such freight subsectors as warehousing, long- and short-haul. It is expected that penetration rates of freight automation will vary across subsectors. In some subsectors, new jobs will be created and/or working conditions will improve. Other subsectors will see declining job quality and/or job losses that require workers to transition to new roles or sectors entirely, when possible. Changes in job opportunities and quality will vary within sectors and subsectors, by region, and/or by firm. This study offers an overview and recommendations in three directions. First, despite the uncertainties and based on past and present examples of automation, it provides some insights about strategies that may help impacted workers within and outside of the heavy freight sector transition. Second, it discusses examples of existing public policies that can support a transition for automation-impacted workers. And third, it provides insights on how different freight subsectors are likely to be impacted by automation.

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This white paper assesses how cities are modifying transportation impact fees in response to Senate Bill (SB) 743, adopted in 2013 to orient environmental review of transportation impacts of development projects and plans in California to support sustainable development. SB 743 and its implementing guidelines eliminated “level of service” (LOS) standards for automobile traffic delay as an environmental impact to be addressed under the California Environmental Quality Act (CEQA), recommending instead that localities and other lead agencies responsible for CEQA review analyze, and if possible, mitigate impacts on vehicle miles traveled (VMT) instead. As cities proceed to implement SB 743, some are going further than the minimum required to analyze and mitigate for VMT at the development project level. Instead, they are also pursuing “programmatic” approaches, including altering citywide impact fees imposed on developers, to support more systematic analysis and mitigation than is possible at the project level alone. Based on public documents research and interviews with consultants and planners, this paper identifies three basic approaches that cities are taking to design impact fees in conjunction with their policy approaches for addressing SB 743: first, to design impact fee programs that fund VMT-reducing projects, but without employing a VMT “nexus” (the nexus is the basis for identifying impacts to be addressed by the program); second, to employ a VMT nexus for identifying facilities need and cost allocation; and third, to design a fee program that links to systematic CEQA-reviewed VMT analysis in the General Plan and/or other related CEQA-reviewed city wide policy documents. In this latter approach, cities may or may not design their fee program to fund VMT-reducing projects; indeed, this approach may help facilitate a more traditional, LOS-based fee program. This outcome can happen if a city analyzes VMT systematically for the General Plan, and then adopts a “statement of overriding considerations” under CEQA, which allows for development projects to “tier” off the programmatic environmental review so as to avoid the need for conducting cumulative VMT impacts analysis. This approach may facilitate more systematic integration of VMT and LOS analysis at the citywide level, but it does not support SB 743 goals for supporting VMT-reducing projects and programs.

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This project aims to assess the current and future performance and costs of battery electric trucking, through reviewing key recent studies in the U.S. and presenting a detailed comparison of their cost modeling scope and coverage. This white paper presents a review of 10 recent studies of the total cost of ownership (TCO) of battery electric trucks (BET), now and in the future, compared to a baseline diesel truck, for the following 3 important types of truck: heavy-duty long-haul trucks, medium-duty delivery trucks, and heavy-duty drayage/short-haul trucks. The researchers break down the studies into their estimates for a range of important cost and operating factors, such as vehicle purchase cost, efficiency, fuel cost, maintenance cost, required range and thus battery pack sizing, and other factors. Of note are differences in major assumptions of studies and variables that are included or excluded from consideration. The authors do not judge these studies against each other but attempt to derive general findings that are robust across studies, areas of significant difference, and areas for further research. Overall, TCO estimates across the studies, for a given truck type, can vary dramatically, though often several studies cluster together. But as this study explores, the differences in TCO link directly to differences in assumptions, parameters and other differences across the studies. The studies vary in important ways that should be taken into account when comparing TCO estimates. Policy makers should consider the context of truck type, truck use and other factors when reading such studies, and pay attention to assumptions. Policies should reflect the wide range of situations that trucks may encounter and avoid assuming a simple average TCO across all situations.

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