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COVID-19 altered travel patterns in the U.S. Studies have analyzed the effect of the pandemic on travel mode, including working from home, but few have focused on automobile ownership—a relationship with potentially long-term consequences for accessibility, household budgets and debt, and policy efforts to meet climate goals.To understand the association between the pandemic and automobile ownership, we rely on a unique credit panel dataset from Experian and examine three different automobile loan-related outcome measures: annualized growth rate of new automobile loan balances, average new loan size, and the number of new loans. We focus specifically on changes across loans in neighborhoods by race/ethnicity, hypothesizing larger increases in automobile debt in Black and Latino/a neighborhoods, where workers are less likely to be able to telework. The annualized growth rate of new automobile loans increased during the pandemic across all neighborhoods by race/ethnicity, increasing most rapidly in Latino/a neighborhoods. Controlling for other factors, loan size increased similarly across neighborhoods by race/ethnicity. The increase in automobile lending in Latino/a neighborhoods, therefore, likely was explained by a significant uptick in the number of new loans.The growth in automobile lending during the pandemic was potentially prompted by pandemic-induced changes in the need for automobiles and facilitated by an expanded social safety net. As the pandemic and its various forms of public financial assistance recede, the findings underscore the importance of ongoing assistance in enabling automobile ownership or shared access among households with limited means whose livelihoods depend on the access that vehicles provide.

Problem, research strategy, and findingsCarsharing programs—subscription-based car rentals—allow users to purchase only the automobility that they need. These programs may benefit low-income travelers by increasing access at lower prices than private auto ownership. Most carshare programs, however, disproportionately serve higher-income drivers. To assess carsharing’s potential to address the accessibility needs of disadvantaged households, we interviewed members of BlueLA, an electric carsharing program in central Los Angeles (CA) that offers both subsidized and regular memberships. We found few differences in how travelers with different membership types used BlueLA. They both used the service to complement travel by other modes like public transit and ridehail. In addition, members cited the benefits of gaining car access without the financial burden of car ownership or the unpredictability of ridehail fares. Neighborhood context, including residential density and the availability of non-automobile transportation options, also increased BlueLA’s appeal. However, due to limited and unreliable vehicle availability, most users did not rely on BlueLA for time-sensitive trips. BlueLA both eased and increased access to destinations outside of the commute and complemented public transit for subsidized and regular members. Takeaway for practiceServices like BlueLA cannot meet all transportation needs. However, subsidized electric carsharing—particularly targeted to central-city neighborhoods—may address some accessibility needs of low-income households without imposing the burdens of automobile ownership.

We examine pre-COVID declines in transit ridership, using Southern California as a case study. We first illustrate Southern California's unique position in the transit landscape: it is a large transit market that demographically resembles a small one. We then draw on administrative data, travel diaries, rider surveys, accessibility indices, and Census microdata for Southern California, and demonstrate a strong association between rising private vehicle access, particularly among the populations most likely to ride transit, and falling transit use. Because we cannot control quantitatively for the endogeneity between vehicle acquisition and transit use, our results are not causal. Nevertheless, the results strongly suggest that increasing private vehicle access helped depress transit ridership. Given Southern California's similarity to most US transit markets, we conclude that vehicle access may have played a role in transit losses across the US since 2000.

Homelessness continues to grow and to affect the lives of an increasingly diverse group of individuals. Many scholars have studied people living in homeless shelters and outdoors in tents. An overlooked population is the growing number of the unhoused living in vehicles. We draw on data from the Los Angeles Homeless Services Authority’s Homeless Demographic Survey to understand the characteristics of people living in vehicles and the extent to which they differ from the nonvehicular unhoused population. Compared to those living in tents, in makeshift shelters, and in public spaces, people living in vehicles are more likely to be women and to live in larger households with children, and are less likely to be chronically unhoused. These findings will help effectively target policies and services. Safe parking programs can provide temporary relief to those living in vehicles and, if done well, the interventions necessary to transition into permanent housing.

Problem, research strategy, and findingsShelter is a necessity, yet approximately 17 out of every 10,000 people in the United States are unhoused. Public attention to homelessness has centered on individuals sitting and sleeping in public spaces. However, as many as 50% of the unsheltered live in vehicles. For people sleeping in vehicles, finding a safe place to park is an ongoing challenge, further complicated by the growing number of ordinances restricting vehicular dwelling. We drew on point-in-time count data from the Los Angeles (CA) Homeless Services Authority to examine spatial patterns of vehicular homelessness in Los Angeles from 2016 to 2020. We tested the relationship between the presence of vehicle regulations and the number of people sleeping in vehicles. Although the data likely underestimated vehicular homelessness, we found that ordinances directly reduced the number of people living in vehicles in particular census tracts. On average, cities with citywide and overnight bans had greater impacts on people sleeping in vehicles than cities with less restrictive ordinances. However, the indirect effects in neighboring tracts were stronger and demonstrate the role of these ordinances in simply shifting the vehicular homeless between areas. Takeaway for practiceGiven the slow pace of delivering permanent housing for people experiencing homelessness, cities should reduce the harm and precariousness of living in vehicles. Strategies to do this include the reform of punitive vehicle towing and vehicle dwelling regulations. Safe parking programs can provide individuals with a safe place to park their vehicles at night, offer ancillary services, and deter harassment from neighborhood residents and the police. Longer term, transformative change will require additional policies and programs to place people into permanently affordable housing.

This report synthesizes three primary data sources—credit data, unemployment claims data, and small business loan and grant data—to explore the financial conditions of those who drive for a living before and during the COVID-19 pandemic in California. Automobile debt was high among groups likely to contain professional drivers. The occupational categories in which many drivers fall had high absolute and relative levels of automobile debt compared to other workers. After the onset of the pandemic, unemployment rose dramatically in the transportation industry and in transportation occupations, peaking at rates higher than the national average. However, state unemployment claims data, among transportation employee claimants only, show less of a spike. Contractor drivers lived in areas with more Pandemic Unemployment Assistance claims, a special program for self-employed workers like gig drivers. Finally, contractor drivers received unprecedented but uneven federal small business loans and grants. Drivers in many areas, however, did not receive much or any of these funds, though those areas that did tended to have more residents of color. Assessing the full effect of the pandemic on professional drivers’ debt and finances will require additional and better data, particularly workforce data from gig economy firms that contract with drivers.

We examine pre-COVID declines in transit ridership, using Southern California as a case study. We first illustrate Southern California’s unique position in the transit landscape: it is a large transit market that demographically resembles a small one. We then draw on administrative data, travel diaries, rider surveys, accessibility indices, and Census microdata for Southern California, and demonstrate a strong association between rising private vehicle access, particularly among the populations most likely to ride transit, and falling transit use. Because we cannot control quantitatively for the endogeneity between vehicle acquisition and transit use, our results are not causal. Nevertheless, the results strongly suggest that increasing private vehicle access helped depress transit ridership. Given Southern California’s similarity to most US transit markets, we conclude that vehicle access may have played a role in transit losses across the US since 2000.

Driving rates decline with age as vision, health, and cognitive ability cause some older adults to give up driving. Many older adults first gradually limit their driving as they age and later cease driving. Using data from the Health and Retirement Study (HRS), which surveys 22,000 older Americans every two years, we modeled the extent to which older drivers limit and stop driving. The data are longitudinal, allowing analysis of changes in driving and residential location as well as cohort effects that could not be studied using standard, cross-sectional survey data that only allow comparisons of different people at one point in time. The analysis shows that decisions to limit and eventually stop driving vary in statistically significant ways with sex, age, and health conditions. These relationships also differ by birth cohort. More recent cohorts are less likely to stop and limit driving than older ones. To analyze the relationship between residential location and driving behavior, we linked the HRS data to census-tract level data from the US Census and a categorization of community types. We found that residential density and other urban built environment features are associated with changes in driving and vehicle ownership. HRS survey participants showed a greater propensity to reduce or give up driving if they resided in denser, more diverse, transit-oriented neighborhoods. People who prefer non-automotive modes of transportation may have been more likely than others to self-select into walkable and transit-rich areas. The findings should inform California’s strategic planning for aging and its community development policies. In addition to informing planning for the next generation of older Californians, this study demonstrated the utility of longitudinal information and models for the understanding of older populations and their travel.

Public transit ridership has been falling nationally and in California since 2014. The San Francisco Bay Area, with the state’s highest rates of transit use, had until recently resisted those trends, especially compared to Greater Los Angeles. However, in 2017 and 2018 the region lost over five percent (>27 million) of its annual riders, despite a booming economy and service increases. This report examines Bay Area transit ridership to understand the dimensions of changing transit use, its possible causes, and potential solutions. We find that: 1) the steepest ridership losses have come on buses, at off-peak times, on weekends, in non-commute directions, on outlying lines, and on operators that do not serve the region’s core employment clusters; 2) transit trips in the region are increasingly commute-focused, particularly into and out of downtown San Francisco; 3) transit commuters are increasingly non-traditional transit users, such as those with higher incomes and automobile access; 4) the growing job-housing imbalance in the Bay Area is related to rising housing costs and likely depressing transit ridership as more residents live less transit-friendly parts of the region; and 5) ridehail is substituting for some transit trips, particularly in the off-peak. Arresting falling transit use will likely require action both by transit operators (to address peak capacity constraints; improve off-peak service; ease fare payments; adopt fare structures that attract off-peak riders; and better integrate transit with new mobility options) and public policymakers in other realms (to better meter and manage private vehicle use and to increase the supply and affordability of housing near job centers).

Transit ridership in the San Francisco Bay Area is falling. Yet some operators, areas, times, directions, routes, modes, and services have fared better than others. These differences help reveal the causes of the Bay Area’s overall ridership slump and inform policy and service decisions that aim to restore Bay Area transit use. To investigate these temporal and spatial trends, we analyze ridership on the eight largest Bay Area transit operators in considerable detail in Volume II of our report.Overall, we find a significant level of “peaking.” Ridership losses at off-peak hours, on weekends, on outlying routes, in non-commute directions, and on smaller operators account for a large and disproportionate share of the whole region’s patronage decline. Downtown San Francisco and commute-oriented rail lines like Caltrain have gained ridership as less central, lower-service routes have lost patronage. These patterns match our statistical modeling of BART ridership, on which station-area jobs had the greatest influence, one that has grown over time. The most significant exceptions to the Bay Area’s peaking problem are operators in urban cores, like Muni and AC Transit, where residential and employment density throughout the network have blunted peaking, though not necessarily overall losses.Absolute patronage declines and peaking are intertwined but distinct problems, with cross-cutting divisions. Yet on all agencies, we see at least some evidence of peaking. The resulting dependence on peak trips both incurs high costs and depresses passenger satisfaction.

This report examines whether being more mobile is associated with decisions by older people to remain in the active work force after normal retirement age.  Mobility includes having access to and the capacity to drive cars and being transit accessible or being able to walk to work or work at home.  The report presents findings in three sections and concludes, based on research conducted thus far, that there are indications of causal associations between mobility and delayed retirement.  The report includes a review of the literature linking mobility, travel by the elderly, and retirement decision making. Following the review of the literature is quantitative analysis of data from the California Household Travel Survey, including mathematical models of relationships between mobility and the propensity of older Californians to remain in the active work force.  The final component of the research findings is a summary of the results of qualitative research consisting of focus groups and interviews. While the findings are not conclusive they show relationships which indicate that further research, particularly using longitudinal rather than cross sectional data, are warranted.  After presenting findings, the report concludes with recommendations for further research.

Carsharing programs—subscription-based car rentals—allow users to purchase only the automobility that they need. These programs may benefit low-income travelers by increasing access at lower prices than private auto ownership. Most carshare programs, however, disproportionately serve higher-income drivers. To assess carsharing's potential to address the accessibility needs of disadvantaged households, we interviewed members of BlueLA, an electric carsharing program in central Los Angeles (CA) that offers both subsidized and regular memberships. We found few differences in how travelers with different membership types used BlueLA. They both used the service to complement travel by other modes like public transit and ridehail. In addition, members cited the benefits of gaining car access without the financial burden of car ownership or the unpredictability of ridehail fares. Neighborhood context, including residential density and the availability of non-automobile transportation options, also increased BlueLA's appeal. However, due to limited and unreliable vehicle availability, most users did not rely on BlueLA for time-sensitive trips. BlueLA both eased and increased access to destinations outside of the commute and complemented public transit for subsidized and regular members. Services like BlueLA cannot meet all transportation needs. However, subsidized electric carsharing—particularly targeted to central-city neighborhoods—may address some accessibility needs of low-income households without imposing the burdens of automobile ownership. [ABSTRACT FROM AUTHOR]

Researchers at UCLA examine walking behavior of people in Los Angeles, Sacramento, San Diego, and the San Francicso Bay Area to aid in urban planning.

In the last ten years transit use in Southern California has fallen significantly. This report investigates that falling transit use. We define Southern California as the six counties that participate in the Southern California Association of Governments (SCAG) – Los Angeles, Orange, Riverside, San Bernardino, Ventura and Imperial. We examine patterns of transit service and patronage over time and across the region, and consider an array of explanations for falling transit use: declining transit service levels, eroding transit service quality, rising fares, falling fuel prices, the growth of Lyft and Uber, the migration of frequent transit users to outlying neighborhoods with less transit service, and rising vehicle ownership. While all of these factors probably play some role, we conclude that the most significant factor is increased motor vehicle access, particularly among low-income households that have traditionally supplied the region with its most frequent and reliable transit users.

To explore the characteristics of car-deficit households, researchers at UCLA examined California household travel survey data.Their findings can inform discussions on the factors that lead to car-deficit households, the mobility outcomes of car-deficit households, and the role of gender in access to household vehicles. Planners and policymakers can use these findings to better accommodate car-deficit households in the transportation system.