UC Davis Institute of Transportation Studies

A lack of reliable and affordable transportation exacerbates socioeconomic inequities for low-income individuals, especially people of color. Universal Basic Mobility (UBM) pilots or programs are a relatively new approach to addressing financial barriers to travel among the transport-disadvantaged. UBMs provide individuals with funds for various mobilityoptions, including transit and shared modes. This study reviews the UBM programs and pilots implemented in the United States. It also reviews international applications of Mobility as a Service (MaaS) platforms. These platforms may reduce the administrative cost of implementing UBMs and help users identify and compare available travel options. In addition, the review describes critical program design tradeoffs to consider when developing a UBM program or pilot. Finally, key UBM elements and lessons learned are summarized to assist other communities considering UBMs.

Lithium-ion batteries (LIBs) are the enabling technology for modern electric vehicles (EVs), allowing them to reach driving ranges and costs comparable to internal combustion engine vehicles, an important development with EVs being integral to greenhouse gas mitigation efforts. However, LIB advancements include the use of rapidly evolving and chemically diverse batteries as well as larger battery packs, raising concerns about battery production sustainability as well as battery end-of-life (EoL). This study seeks to respond to these concerns by analyzing potential pathways for EoL EV batteries, quantifies flows of retiring EV battery materials, proposes economically and environmentally preferable LIB EoL strategies, and recommends pertinent policies with an emphasis on environmental justice. The researchers used a loosely coupled dynamic systems model that utilized life cycle assessment and material flow analysis and a mixed methods research approach. They find that the U.S. can make significant gains in securing supply chains for critical materials and decrease life cycle environmental impacts through the adoption of Recycled Content Standard policies similar to those found in the European Union. In addition, they examine the currently understood waste hierarchy in the context of LIB technology. Comparing immediate recycling to repurposing and reusing, they find that repurposing and reusing reduces life cycle environmental impacts relative to recycling. This project also includes an investigation of EoL battery collection and transportation and the vehicle afterlife ecosystem, as well as general stakeholders in the LiB life cycle, informed by expert interviews and a case study of a developing lithium industry in Imperial, California.

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Pooled trips in private vehicles, or pooling, can lead to smaller environmental impacts and more efficient use of the limited roadway capacity, especially during peak hours. However, pooling has not been well adopted in part because of difficulties in coordinating schedules among various travelers and the lack of flexibility to changes in schedules and locations. In the meantime, ridehailing (RH) provides pooled services at a discounted fare (compared to the single-travel-party option) via advanced information and communication technology. This study examines individuals’ preferences for/against pooled RH services using information collected among travelers answering a set of questions related to their last RH trip. In doing so, both trip attributes and rider characteristics are considered. Taste heterogeneity is modeled in a way that assumes the presence of unobserved groups (i.e., latent classes), each with unique preferences, in a given sample of RH riders (N=1,190) recruited in four metropolitan regions in Southern U.S. cities from June 2019 to March 2020. The researchers find two latent classes with qualitatively different preferences, choosy poolers and non-selective poolers, regarding their choice in favor of/against pooling based on wait time, travel costs, purpose, and travel party size of the last RH trip. Personal characteristics are also identified, specifically age and three attitudes (travel satisfaction, environmentalism, and travel multitasking), which account for individuals’ class membership. This research contributes to the literature by explicitly modeling taste heterogeneity towards pooled ridehailing. In addition, unlike existing studies either at the person level or employing stated-preference data, a trip-level analysis is performed in connection with revealed preferences, which generates more realistic and relevant implications to policy and practice.

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Vehicle electrification has attracted strong policy support in California due to its air quality and climate benefits from adoption. However, it is unclear whether these benefits are equitable across the state’s sensitive populations and socioeconomic groups and whether disadvantaged communities are able to take advantage of the emission savings and associated health benefits of electric vehicle (EV) adoption. In this study, we analyze the statewide health impacts from the reduction of on-road emissions reduction (from reducing gasoline powered cars) and the increase in power plant emissions (from EV charging) across disadvantaged communities (DACs) detected by using the environmental justice screening tool CalEnviroScreen. The results indicate that EV adoption will reduce statewide primary PM2.5 emissions by 24.02-25.05 kilotonnes and CO2 emissions by 1,223-1,255 megatonnes through 2045, and the overall monetized emission-related health benefits from decreased mortality and morbidity can be 2.52-2.76 billion dollars overall. However, the average per capita per year air pollution benefit in DACs is about $1.60 lower than that in the least 10% vulnerable communities in 2020, and this disparity expands to over $31 per capita per year in 2045, indicating that the benefits overlook some of the state's most vulnerable population, and suggesting clear distributive and equity impacts of existing EV support policies. This study contributes to our growing understanding of environmental justice rising from vehicle electrification, underscoring the need for policy frameworks that create a more equitable transportation system.

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The Low Carbon Fuel Standard (LCFS) plays a critical role in California’s efforts to reduce greenhouse gas (GHG) and air pollutant emissions from transportation. The LCFS incentivizes the use of fuels with lower life cycle GHG emissions by using a credit market mechanism to provide incentives for low-carbon fuels, using revenue generated by charges applied to high-carbon ones. Maintaining an approximate balance between LCFS credit and deficit supplies helps support a stable LCFS credit price and the broader transition to low-carbon transportation. The Fuel Portfolio Scenario Model, presented here, evaluates bottom-up fuel supply and LCFS compliance to inform LCFS policy decisions. We considered two key fuel demand scenarios: (1) the Low Carbon Transportation scenario, reflecting the expected transition to low-carbon transportation in California over the next 15 years, and (2) the Driving to Zero scenario, featuring a significantly higher consumption of petroleum gasoline. In both scenarios, 2030 LCFS targets around 30% resulted in a near-balance between credits and deficits, with some banked credits remaining. Several additional scenarios were modeled to explore the impact of target trajectory timing, alternate post-2030 targets, greater biofuel use, and other parameters. This fuel portfolio scenario modeling work can meaningfully inform policy development.

This study explores interest in, and the challenges faced by transit agencies and operators in the adoption of open-loop payment systems. The research team focuses on the ways that agencies view passenger needs in the context of adopting open payments. Challenges with cash payments, an increasingly cashless society, and the expanding offerings of digital payment options have spurred increased interest in open-loop payments among transit operators. Paying for transit with cash can require additional time at boarding, add extra steps for passengers who must pay with exact fare, and result in service inefficiencies. It presents security concerns for drivers, and administrative burdens for agencies. While the full costs of cash handling vary per agency, the cost of handling and moving cash may be considerable. Pioneering transit agencies are adopting open payment systems that accept credit cards, debit cards, and smartphone/watch-based transactions. However, there is a huge diversity among transit agencies and as such, agencies face different challenges and to different degrees when considering the adoption of open payment systems. Challenges can include financial barriers, capacity limitations, technological challenges, the duration of existing contracts, competing needs, and a number of passenger challenges such as lack of credit cards or smartphones, or lack of familiarity with the technology. This study uses data collected from California transit agencies in the fall of 2022 that gathered information about agency perceptions of open-loop payments and the challenges with adopting open fare collection systems, and whether assistance programs would benefit transit agencies interested in adopting open-loop payments. Results of the present study indicate that the majority of agencies are considering or have considered implementing open payment systems, but agencies are not fully aware of the assistance available from the California Integrated Travel Program to help in the transition to digital and open payment systems. This study sheds light on the challenges facing small to medium transit agencies in the transition of California’s transit systems to open-loop payment systems.

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The increasing diversity of vehicle type holdings and growing demand for BEVs and PHEVs have serious policy implications for travel demand and air pollution. Consequently, it is important to accurately predict or estimate the preference for vehicle holdings of households as well as the vehicle miles traveled by vehicle body- and fuel-type to project future VMT changes and mobile source emission levels. Leveraging the 2019 California Vehicle Survey data, this report presents the application of a utility-based model for multiple discreteness that combines multiple vehicle types with usage in an integrated model, specifically the MDCEV model. The model results suggest the important effects of household demographics, residence location, and built environment factors on vehicle body type and powertrain choice and usage. Further the predictions associated with changes inbuilt environment factors like population density can inform the design of land-use and transportation policies to influence household vehicle holdings and usage that can in turn impact travel demand and air quality issues in California.

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This white paper presents the synthesis of the literature on the use of cargo bikes for urban goods movement with a particular focus on four barrier and opportunity domains: physical and spatial; economic; political and legal; and social and cultural. It also includes research particularly relevant to California cities, although many of the studies reported were conducted outside California because we found a lack of evidence within California. The barriers to shifting from trucks and vans to cargo bikes for a variety of good movements remain tall in California. They include, among many, a need for a significant shift in the delivery landscape that requires collaboration across different organizations, and support from the local and state level that includes the development of urban consolidation hubs, investment in bike infrastructure, and strict restrictions on larger delivery vehicles. In addition, it may also require initial incentives to freight operators to offset the costs of shifting to cargo bike logistics. Although the barriers are large, the need is paramount, given the rise in e-commerce and local goods movement. Motivated by this need, and with targeted efforts to overcome these barriers, synergistic benefits are possible including a safer and more bike-friendly road network supportive of both personal active transportation and cargo-bike goods movement. These outcomes will help achieve wide-ranging goals in transportation planning, including GHG reduction, improvements to public health through physical activity, and emission reductions, among others.

This study used a simulation to examine nonpharmaceutical interventions (NPIs) that could have been implemented early in a COVID-19 surge to avoid a large wave of infections, deaths, and an overwhelmed hospital system. The authors integrated a dynamic agent-based travel model with an infection dynamic model. Both models were developed with and calibrated to local data from Los Angeles County (LAC), resulting in a synthetic population of 10 million agents with detailed socio-economic and activity-based characteristics representative of the County’s population. The study focused on the time of the second wave of COVID-19 in LAC (November 1, 2020, to February 10, 2021), before vaccines were introduced. The model accounted for mandated and self-imposed interventions at the time, by incorporating mobile device data providing observed reductions in activity patterns from pre-pandemic norm, and it represented multiple employment categories with literature-informed contact distributions. The combination of NPIs—such as masks, antigen testing, and reduced contact intensity—were the most effective, among the least restrictive, means to reduce infections. The findings may be relevant to public health policy interventions in the community and at the workplace. The study demonstrates that investments in activity-based travel models, including detailedindividual-level socio-demographic characteristics and activity behaviors, can facilitate the evaluation of NPIs to reduce infectious disease epidemics, including COVID-19. The framework developed is generalizable across SARS-COV-2 variants, or even other viral infections, with minimal modifications to the modeling infrastructure.