Congestion pricing in its various forms is the most promising tool that planners and policymakers have for combatting congestion, and the various ancillary problems—like crashes and pollution—that congestion helps cause. Merely suggesting prices, however, raises understandable concerns about fairness. People need cars. Some people, already burdened by high housing prices, are driving many miles every day—how would tolling the roads affect them? Despite improvements to public transit systems, ridership has steadily declined in recent years with the COVID-19 pandemic further exacerbating the issue. Research has shown that the riders who left transit in the pandemic tended to be higher income, better educated, more likely white or Asian, and with access to private motor vehicles. Spatial patterns of ridership have shifted dramatically as well, with downtowns and other major job centers losing the most riders, and low-income neighborhoods retaining the most riders. This study will draw on previous research by the principal investigator on transit usage changes in the pandemic, and will supplement it with more research travel data from transit operators and mobile device services to characterize the new patterns of transit usage, and how they are evolving as the pandemic matures and recedes.
The economic fallout of the current COVID crisis has been hardest on low-income families. A recent survey from the Pew Research Center indicates that 43 percent of U.S. adults report that they or someone in their household has either lost a job or taken a cut in pay. Moreover, more than half of lower-income households (53%) report being unable to pay some of their bills. These data suggest that the current crisis likely saddles low-income families with untenable debt, which for some households may result in the loss of household vehicles. The team will analyze the potential effects of the COVID-19 crisis on automobile debt and delinquencies across neighborhoods by income and race/ethnicity. In 2020-21, the project team initiated a research project on auto debt using data from the University of California Consumer Credit Panel and the American Community Survey. The credit data include information on both auto debt and delinquency. From 2010, the dataset also includes a census tract identifier. To match the credit data to demographic characteristics, the team drew on the 5-year American Community Survey and assembled data on census tracts by income quintile and majority race neighborhoods.
Growing public interest in fare-free transit demands an assessment of fare-free and/or reduced transit fare programs, particularly how these programs may benefit disadvantaged communities, both urban and rural. Fare policy equity entials decisions about the similarities and differences in treatment afforded to various constituent groups. It also involves decisions about the extent to which travelers are expected to pay for the costs of serving their travel demand. This is of particular concern with regard to low-income, largely non-White, travelers, who are both disproportionately likely to use transit and to be burdened by the monetary costs of transit use. Given the foregoing, there is rising popular and scholarly interest in making public transit systems “fare-free.” Accordingly, in this research we will carefully review and synthesize the current states of both the practice of and research literature on fare-free transit. We will focus our review on the various dimensions of equity raised by charging for transit fares, and how they have/are likely to play out with conversion to fare-free transit service.
In February 2019, the US Congress announced a resolution for the Green New Deal (GND), a set of policies to drive renewable energy and the low-carbon economy and eradicate poverty while protecting against climate change. This project takes on transportation and urban climate futures by focusing on social and ecological questions of transportation infrastructure prompted by the GND and how to design for them. This research addresses this by focusing on the intersection of urban design, environmental ethnography, and transportation planning. It proceeds in two parts: The first is a spatial ethnography of regions confronting unjust impacts from old infrastructure. It looks at two case studies in the LA area: Boyle Heights and Long Beach, two sites often cited as having among the worst impacts of transportation networks. The second is the development of a theoretical framework to imagine new transportation futures, bridging the social sciences and the urban design fields.
Past research has highlighted (a) the relationship between affordable housing and commute distance (b) the growing jobs/housing imbalance in California cities and affordable housing, and (c) commute distance and transit-rich neighborhoods. A continued research need is to explore these relationships by race and class. The project team will examine the role of affordable housing in explaining commute distance. There are relatively few majority black neighborhoods in California; therefore, the team will expand our study to include (with supplemental funding from another source) the 10 largest U.S. metropolitan areas (New York, Los Angeles, Chicago, Dallas, Houston, Washington DC, Miami, Philadelphia, Atlanta and Phoenix). As part of this project, the team would update the commute distance data to the most recent available data (currently 2018), produce a review of the literature on affordable housing and travel behavior, and analyze data by income and race/ethnicity as well as by metropolitan area.
New transportation networks facilitate mobility and may also spur economic development. Over the past decades, a new transportation technology — high-speed rail (HSR) — has brought a profound impact on urban-regional accessibility and intercity travel across Europe and East and South-East Asia. But the economic and spatial impacts of HSR have been varied and are largely contingent on a variety of factors, as well as local planning and policy. As California is in the process of building its own HSR network, it is important to review the experience of established HSR networks abroad and understand the possible economic effects that HSR can bring to regional and local economies, and their prerequisites. While the impacts of California’s plan on the direct creation of jobs in local markets (e.g., construction sector) and on the travel sector (e.g., forecasts for HSR travel demand) have been investigated, the possible indirect impacts (e.g., on land values, tourism, firm location, and local and regional development) have not gathered enough attention. This research proposal attempts to fill this gap.
Transportation & Communities, Transportation & Health
The racist legacy of freeways has come into stark focus in the past year. This research focuses on one specific impact of freeways: neighborhood severance. Freeways disrupt the neighborhood street grid, creating particular hardships for pedestrians who must take circuitous routes to access transit and to walk to stores, schools, and other destinations. The impacts of disconnected streets on walking and public health are well documented (e.g. Handy 2003; Marshall et al. 2014; Barrington-Leigh and Millard-Ball 2019). But the environmental justice dimension of connectivity has remained unexplored, as has the link between most academic studies of street connectivity and local planning efforts. The research team will test the hypothesis that, while freeways disrupt street networks everywhere, the severance effects are greatest in BIPOC communities. This injustice might arise if White residents have more political voice to advocate for a denser mesh of local streets that cross the freeway, or to cancel a freeway proposal altogether.
California voters and taxpayers have made a substantial financial commitment to improving and expanding public transit to provide essential mobility for those unable to drive and to provide drivers with a sustainable alternative to sitting in traffic. But the novel coronavirus (COVID-19) pandemic and the related economic downturn have significantly depressed transit ridership and altered the operations of transit agencies across California. While federal stimulus funds have helped operators and while vaccination distribution has helped ease the effects of the pandemic, governmental responses—in city halls, county seats, Sacramento, and Washington, D.C.—to transit’s financial straits will importantly shape the future of the state’s substantial commitment to public transportation. This study will investigate the scope and scale of the budgetary impact of the pandemic on transit operators and the measures—enacted, proposed, and possible—that transit systems and their funders might adopt in response, both in the near term and over the longer run.
Prior to the COVID-19 pandemic, about five percent of the U.S. labor force worked primarily from home. Between February and April of 2020, the share of the labor force working from home skyrocketed to well over 50 percent in response to public health orders to contain the pandemic. While no one expects the share of those working from home to stay at such high levels as the pandemic recedes, there is considerable debate among experts on just how many workers will return full-time to employment sites. This research will review the well-established and substantial pre-pandemic literature on working from home and travel as well as the nascent but rapidly growing literature on working from home and travel in the COVID-19 pandemic to offer insights on the future of home/work location choices, commuting, and transportation mode usage, likely through the presentation of plausible future location/travel scenarios and their policy implications.
The COVID-19 pandemic has laid bare the necessity of childcare as essential infrastructure. Without access to affordable childcare, working outside of the home is difficult or, in many cases, impossible. The need for child care is particularly pressing for mothers who continue to bear disproportionate responsibility for the care of their children. Childcare is in short supply and access to child care varies across neighborhoods by income, race, and ethnicity. Given the critical importance of childcare access to women’s ability to work, the research team will study child care-related travel in California, a topic that has received relatively little study. The researchers are particularly interested in testing whether geographic disparities in access to child care are associated with the distance that parents travel to child care centers.
My overall research objective is to produce transportation research on access to opportunity for low-income and communities and people of color, done in partnership with community partners. Through this work, I seek to understand better what transportation access intervention models designed in collaboration with the community can improve people’s life outcomes. Historically, transportation plans and programs have not met the needs of disadvantaged populations. Newer technological advances in transportation — ride-hailing and micro-mobility — have similarly failed to provide increased access to high-need communities partially due to not being scoped and designed in collaboration with the community. For this reason, I seek to advance research towards my research objectives through building relationships with community-based organizations and doing research in partnership to help solve real-world problems.
More than 150,000 people in California experience homelessness every day. In the last decade, homeless counts have risen in many metropolitan areas, despite efforts and funding from local governments and nonprofits to address the issue. The limited capacity of shelters and social service agencies to meet the needs of a rapidly growing homeless population has forced many individuals experiencing homelessness to look for shelter in various public spaces. Without other options, many turn to settings under the auspices of departments of transportation (DOTs) like the California Department of Transportation (Caltrans), including freeway rights-of-way, underpasses, rest areas, parking lots, maintenance facilities, state highways, and Caltrans-managed urban streets and sidewalks. With affordable housing scarce in California and the scale of the homelessness crisis often surpassing the capacities of existing safety nets, Caltrans is facing these pressing issues and must implement policy measures from realms beyond transportation to address them.
Transportation & Communities, Transportation & Health
California has a long, tragic history of racial discrimination, including in land use and transportation. Discriminatory immigration laws separated Asian families by the insurmountable width of the Pacific Ocean, prevented Asians from owning land, and incarcerated a whole population during World War II because of ancestry only. Indeed, the origins of zoning are rooted in white bigoted desires to isolate and segregate Asians. It is impossible to understand fully past systemic racism in California and the United States without including the Asian American experience. This project will employ a mixed-method approach to investigate the impact of the crosstown freeway development (State Route 4) in Stockton, California. This freeway devastated one of the largest Filipino American communities in the country, Little Manila. Anecdotal information indicates that the freeway also displaced a large number of Chinese Americans and Japanese Americans.
The U.S. has a relatively old inventory of bridges, which makes the monitoring and maintenance of bridge stock a national priority. Nearly 40% of the country’s 614,387 bridges are 50 years or older, with many more approaching the end of their nominally 50-year-long service lives. Current monitoring and maintenance is mainly based on visual inspections, which is labor-intensive, costly, time-consuming, and subjective (i.e., prone to human errors). We propose the development of an innovative integrated solution for damage identification (detection, localization, quantification) of bridge structures using a non-contact image-based measurement scheme. Computer vision techniques will be used to extract information from raw images, which will be used for joint finite element (FE) model updating and vehicular load estimation. The updated model can be maintained as a digital twin for damage diagnosis of the structural system. The digital twin can be utilized for global load rating and operational condition and post-disaster assessments through the life-cycle of the bridge, so as to help with bridge management decision strategies.
A somber statistic in Science, Technology, Engineering, and Mathematics (STEM) fields, is that underrepresented racial and ethnic groups are less likely than those from well-represented backgrounds to self-report high interest in biomedical faculty careers at research-intensive universities. Hypercompetition in neuroscience careers both at the Ph.D. and post-doctoral level is predicted to result in increased racial and ethnic disparities in this field. African Americans, Hispanics, and Native Americans complete undergraduate STEM degrees at approximately 2 to 3% nationally, yet there is evidence that this can be greatly increased with quality social support and mentoring in these groups.We present key approaches in this application that are aimed at enhancing the inclusive excellence of our NSIDP and develop long-lasting ties with our HBCU partners. The key approaches to increase the impact on students and faculty at both HBCU partner institutions and UCLA are to: 1) engage in active research and teaching partnerships that accompany students before and beyond the 8-week internship at UCLA; and 2) to incentivize quality mentorship of the interns in our UCLA host labs, increasing the impact on students and faculty at both HBCU partner institutions and UCLA.
In the past decade, we have seen a boon in travel opportunities engendered by technology. A major transformation has been the provision of ridehailing services such as Uber and Lyft, companies defined as Transportation Network Companies (TNCs). Their services have been appealing to travelers of varying income levels, equipping them with enhanced access to goods and services. It is predicted that TNC use will continue to grow and form a significant portion of individual and household travel needs. Conversely, transit ridership has fallen over the last decade. Transit has been unable to match the point-to-point mobility the private vehicle provides, pushing transit riders to secure auto-ownership to guarantee adequate levels of accessibility in their regions. As ridership plummets, transit operators are trying to figure out how they can improve their services and expand their markets. This research will utilize a dataset of Lyft rides over three months in Los Angeles region, to understand how TNCs can inform and support transit. This research will also examine the patterns of pooled and non-pooled mobility for the purposes of informing Autonomous Vehicle (AV) Planning.
The National Transit Database (NTD) maintained by the Federal Transit Administration is an invaluable source of comparative data on public transit systems, but it is far from a complete one. In particular, the NTD tells us a lot about public transit services provided by system and mode, as well as their cost. But other than the number of unlinked trips made by transit users, they provide very little data on public transit users. In addition, new transportation services, like transportation network companies and dockless mobility services, may be both complementing and competing with traditional public transit services, but data on the extent and use of these services are sorely lacking. This project will develop a framework that outlines the various types of data relevant to understanding public transit systems and their use, identifies currently available data for each of these types, and their quality, and makes recommendations on how to address data needs for public transit research.
Pacific Southwest Region 9 University Transportation Center
Travel patterns have been significantly altered due to COVID-19. However, LA Metro experienced the smallest percent drop in public transit ridership during this time. Though no public confirmation is currently available, anecdotally, we are witnessing sustained ridership in non-traditional peak hour traffic areas such as in South Los Angeles, and low-income neighborhoods in the South Bay. I will analyze travel patterns from NextGen research to better understand public transportation travel patterns. The project topic would involve identifying multiple low-cost opportunities to adjust LA Metro bus services to improve customer experience by better matching LA Metro service to major travel patterns as identified from Metro’s LBS cell phone database as well as Census “On the Map” data and Metro ridership data. The analysis would include reviewing changes to travel patterns and volumes (as seen in cell phone data patterns) resulting from the impact of COVID-19.
The project’s ultimate goal is threefold. First, we will deliver a broad but accurate and relevant snapshot of vulnerable travelers in California. Second, we will use that information to carefully consider how different forms of congestion pricing might improve or degrade equity. Third and most important, we will use lessons from other safety net programs, and particularly those operating in the utility industry in California, to propose specific safeguards for poor and marginalized populations that can be built into congestion charging programs. We examine the fairness implications of congestion pricing and propose policy mechanisms to mitigate its potential unfair outcomes. Our project first empirically establishes the broad contours of travel by vulnerable populations in California’s major metropolitan areas. We then examine particular forms of congestion charging, and evaluate how they might affect equity. Finally and most importantly, we draw on models of the guardrails instituted by other public utilities to illustrate ways to have congestion pricing while still protecting low-income travelers.