Access to safe, affordable, and reliable transportation is essential to creating and maintaining a high quality of life. There are a multitude of transportation geography and individual characteristics that present barriers to equitable and accessible transportation options. This is especially true in Northern Vermont, where the city of Burlington is a small urban island in a largely rural landscape. Using data from an employee survey in the Burlington area, this study compares the individual characteristics and barriers of commuters who report that they do not use their preferred mode to commute to work (mode-constrained commuters) to those who report that they primarily use their preferred travel mode to commute (mode-choice commuters). Our analysis distinguishes between primary–preferred mode combinations to understand the varying circumstances of travelers in different situations. For example, a traveler who currently bikes to work but prefers to drive likely faces different barriers than someone who currently bikes to work but prefers to take the bus, or someone who currently takes the bus but prefers to drive. This study also evaluates travel outcomes and the extent to which satisfaction with different commute attributes vary across different types of mode-constrained travelers and their mode-choice counterparts. Our findings highlight the importance of understanding the relationships between travelers’ actual and preferred modes and their identities, barriers, outcomes, and satisfaction in order to inform the equitable and effective design of projects, programs, and policies that seek to strengthen transportation options.

The proportion of income a household spends on transportation, or the transportation burden, is difficult to quantify in the United States, though understanding these costs is essential in creating an equitable transportation landscape. Transportation is the second highest expenditure for most households, with vehicle ownership and associated costs making up the bulk of spending. In the past century, American life has been altered by the increasing role of automobility. For those living in transit deserts, rural areas, and communities that have been disrupted by highway projects, car ownership is the minimum that is needed to engage with the job market, or access basic goods and services, placing a regressive burden on low-income households (Litman 2020). Despite this, we do not have a good handle on how this measure varies between places and for different groups of people since existing data sources are flawed in one way or another.

A recently popular strategy to estimate transportation spending is through measures of place-based affordability, which attempt to model costs using assumptions about the built environment. One such effort is the Location Affordability Index, developed by the Center for Neighborhood Technology for the U.S. Department of Housing and Urban Development. Critics of this measure point to high margins of error and variable uncertainty (Haas, Newmark, and Morrison 2016; Ganning 2017). The National Household Travel Survey collects the direct value of transportation cost but is distributed infrequently. These deficiencies have led researchers to the use of the long-running Panel Study of Income Dynamics in more recent analysis of the influence of the built environment on transportation spending (Makarewicz, Dantzler, and Adkins 2020; Smart and Klein 2018). The Consumer Expenditure Survey (CES) similarly circumvents the uncertainty in location affordability models by directly collecting information on household spending, including transportation costs (BLS 2018). The survey is aggregate to high-level sociodemographic and geographic categories, but valuable trends may still be identified.

In this paper, CES is used as the foundation for our analysis. Transportation burden in the United States can shape the lives of individuals, and a detailed examination of these measures is long overdue. We examine 1) how transportation spending varies between groups in the United States, 2) how transportation spending has changed over time, and 3) how the United States compares to other countries with varying transportation systems.

This study looks at results from the Transportation Wallet for Residents of Affordable Housing (TWRAH) pilot program launched by the City of Portland’s Bureau of Transportation (PBOT). The program provided a set of transportation incentives for low-income participants including a $308 pre-paid US Bank visa card which could be applied to public transit or other transportation services, a free bike share membership, and access to discounted rates on several services. We conducted a survey with the program’s participants (278 total responses) to understand how they used the Transportation Wallet and how the program helped them use different modes to get around.

Key findings of the study include: 1) The financial support of this program encouraged some participants to use new mobility services (including Uber/Lyft, bike share, and e-scooter) that they had never used before; 2) the program increased access for participants, helping them make more trips and, for some, get to places they otherwise could not have gone; and, 3) Transportation Fairs, where participants could learn about services and talk to providers, promoted both mode sign-up and mode usage, particularly for new mobility and a reduced fare transit program. The survey results also point to some opportunities to improve the program. Participant feedback suggests that transportation agencies do more to streamline and educate participants on how to use new mobility and coordinate different service providers better to optimize seamless services for participants.

The poster will also look in depth at transportation wallet fund allocation choices made by residents in relation to key transportation accessibility measures, including transit accessibility and measures such as Walk Score. Are residents based in locations with high transit accessibility more likely to expend their wallet funds on transit services? What factors influence whether residents are more likely to spend their funds on Taxis compared to Uber of Lyft? What measures are correlated with increased likelihood of using shared mobility services such as e-scooters or bike share?

Over the years, conventional practices and patterns used in establishing and planning transportation systems in urban settings have largely focused on the mobility of people. The main goal has always been to mitigate congestion, based on the forecasted growth of road users and economic activity in future years. This approach may fail to respond to the need of residents in lower income neighborhoods with Black and Latino residents. This lack of equity in future plans becomes exacerbated when considering the context of past patterns of development and segregation. These systemic patterns of segregation and limited investment have left neighborhoods with inadequate transportation infrastructure. According to Litman (2010), transportation planning affects land value, employment and economic development. A change of practice, where the accessibility to opportunity for all social groups becomes the focus, will enable those neighborhoods to grow economically by improving access to opportunities using public transit or personal vehicle. This research will investigate the role that transportation (mobility and access) measures play in determining community household incomes.

At a United States (US) Census block group level, this study investigates the role that transportation plays in household income by calculating the number of opportunities (e.g. employment, healthcare and education) accessible within a particular travel time like thirty minutes using transit or auto. In addition to transportation factors, the study controls for confounding effects within the built environment like land use patterns of density and diversity as well as parcel values and rents to isolate the transportation impact on household incomes.

Anecdotal evidence suggests that the growing affordable housing crisis in major metropolitan areas, such as Los Angeles, is forcing households to seek lower cost housing in the outer reaches of metropolitan areas, helping to explain the recent increase in commute distances (Dougherty & Burton, 2017; Holder, 2018; Lopez, 2017; Sisson, 2017; Tu, 2015). In the Los Angeles metropolitan area, the number of jobs near the average resident decreased by 7.4 percent from 2000 to 2012, with high increases in commute distance in high-poverty and majority-minority neighborhoods (Kneebone & Holmes, 2016). At the same time, housing prices—both home and rental—have continued to climb, even in the midst of the current COVID-19 pandemic (Joint Center for Housing Studies, 2020a). High housing costs may limit the ability of lower-income households to act on their preferences for living in close proximity to where they work (Levine, 1998).

Despite suggestive evidence of the relationship between housing costs and commute distance, there are relatively few studies that document this association and its magnitude. We use spatial regression to examine this relationship between the availability of affordable housing in close proximity to jobs (jobs-housing fit) and commute distance in the Los Angeles metropolitan area controlling for several locational, employment, and housing characteristics of workers’ workplace census tracts. The analysis draws on 2015 Longitudinal Employer-Household Dynamics (LEHD) Origin-Destination Employment Statistics (LODES) by workplace supplemented with data from the 2017 5-Year American Community Survey on affordable housing units.

We find substantial variation in jobs-housing fit across Los Angeles neighborhoods. The imbalance is greatest in higher-income neighborhoods located along the coast and in Orange County, south of Los Angeles. Overall only four percent of low-wage workers work in neighborhoods where cost-appropriate housing units exceed the number of workers.

Controlling for other determinants of commute distance, higher ratio of jobs to affordable housing is associated with longer distance commutes. These findings suggest that the lack of reasonably priced housing options near employment locations likely force low-wage workers to live far from job locations and, consequently, lead to longer commutes. The character and affordability of housing may not adequately meet worker demand—particularly demand from low- and medium-wage workers.

The findings from this study, therefore, underscore the importance of policy efforts to protect and expand the supply of long-term rental housing particularly in job-rich neighborhoods located in large and expensive coastal cities.

Over the years, increasing justice-oriented social and political movements have drawn our attention to a variety of issues under the umbrella of equity. It invites every member of the society to revisit what is equity (or justice) essentially and how it has been deployed in varying modern contexts. The concept is commonly interpreted as resources or impacts distributed proportionally among different groups of people based on their disadvantage level [1,2]. In the transportation field, equity is the guiding ethical principle and labeled as one of the top priorities in many plans [3,4]. Transportation-related equity is multidimensional [5] while accessibility is the main focus of this study. Generally understood as the ease of reaching places, accessibility is the final product delivered by the transportation system when simultaneously interacting with people and land use [6,7]. In a car-dominant society where car access or ownership largely equal accessibility, we are interested to understand the size of the gap between public transportation and car in their ability to reaching destinations.

In this study, we developed two novel approaches that are different from other studies [8,9,10,11] regarding measuring the modal mismatch. The first one is to identify flexible destinations that are highly exchangeable (such as groceries, parks, and restaurants) based on multiple criteria. The count of this type of destination reachable is positively associated with the level of accessibility, which is different from non-flexible ones (such as workplace, school, or church) whose quantity does not necessarily represent accessibility. The second approach is to use comparable travel times for two modes to evaluate the accessibility gap in lieu of the same thresholds whereby car almost certainly outperforms transit. We identified acceptable maximum transit (in-vehicle) travel times corresponding to car travel times in 10-minute increments based on relevant literature, transit agency surveys, and real-time travel information (such as Google Maps and Uber Mobility).

We selected one of most transit-rich cities in the U.S. – San Francisco as our study area and primarily focused on the most heavily used local public transit system Muni. We developed a Modal Mismatch Index (MMI) at block group level which demonstrates the modal mismatch of accessibility (with high values representing larger disparities). We then examined the relationship between MMI and people’s socioeconomic status (SES) in residential locations and used the exhibited correlation to answer our question of equity: are low-SES groups provided with better (or at least equal) transit accessibility.