published journal article

The Road, Home: Challenges of and Responses to Homelessness in State Transportation Environments

Abstract

In recent decades, homelessness has become an increasingly major challenge in the U.S., reaching about half a million unhoused people. Many of them seek shelter in settings such as freeways, underpasses, and rest areas. State departments of transportation (DOTs) are responsible for the health and safety of these settings and their occupants, housed and unhoused. This study synthesizes existing literature and findings from interviews with staff from 13 state DOTs and eight service providers and organizations responding to homelessness. Homelessness represents a recognized and common challenge for DOTs, which face jurisdictional, financial, and legal hurdles in addressing it. DOT staff employ both “push” and “pull” strategies, the most common of which is encampment removals (“sweeps”). However, the effectiveness of such removals is limited, as encampments often reappear in nearby sites. Other strategies include “defensive design” and, more proactively, establishing or partnering with low-barrier shelters, providing shelters and sanitation on DOT land, and coordinating rehousing and outreach efforts. Our findings suggest that DOTs should acquire better data on homelessness on their lands, create a homelessness coordinating office, establish formal partnerships with nonprofits/service providers, and evaluate the necessity of encampment removals, through the development and utilization of prioritization criteria.

blog

Transit Ridership at Bay: Reflections on the UCLA ITS Bay Area Transit Use Study

published journal article

Who’s on Board?: Examining the Changing Characteristics of Transit Riders Using Latent Profile Analysis

Abstract

Subsidies of public transit have more than doubled since the late 1980s, with a disproportionate share of funds going to rail services. These investments have important implications, including how they affect both the composition of transit users and their travel behavior. To investigate how transit users and use are changing, we use Latent Profile Analysis and data from the 2009 and 2017 National Household Travel Surveys to examine changes in transit users in the U.S. and in five major metropolitan areas. Nationwide, we find that the share of Transit Dependents grew by 17% to account for two-thirds of all transit users in 2017. These least advantaged riders were more likely over time to reside in very poor households and to be carless. There was a corresponding decline in Occasional Transit Users, for whom transit is part of a multi-modal travel profile. Higher-income, mostly car-owning Choice Transit Riders increased slightly over time but accounted for less than one in ten transit riders in 2017. Their growth was concentrated in a few large metropolitan areas where densities and land use are most transit-supportive. While increased rail transit service has shifted riders away from buses, transit’s role as a redistributive social service that provides mobility to disadvantaged travelers has grown over time. Efforts to draw more multi-modal and car-owning travelers onto transit have been less successful. As transit systems struggle to recover riders following the pandemic, transit’s waxing role of providing mobility for those without will likely become even more prominent.

published journal article

Rating the Composition: Deconstructing the Demand-side Effects on Transit Use Changes in California

Abstract

Transit use in the U.S. has been sliding since 2014, well before the onset of the COVID-19 pandemic. The largest state, California, was also losing transit riders despite substantial public investment and increased service in the pre-pandemic period. This downturn prompted concern among transit managers and planners interested in service-side interventions to reverse the decline. However, relatively little is known about changes in the demand for public transit and how shifts in demand-side factors have affected patronage. Drawing on California data from the 2009 and 2017 National Household Travel Surveys, we quantify demand-side changes as a function of two factors—changes in ridership rates of various classes of transit riders (“rate effects”) and changes in the composition of those riders classes (“composition effects”). Statewide, we find that while shifts in the population composition were in some cases associated with lower levels of ridership, the largest declines in transit patronage were associated with falling ridership rates. Specifically, those with limited automobile access and Hispanic travelers rode transit far less frequently in 2017 compared to 2009. Transit ridership rates and rider composition in the San Francisco Bay Area were relatively stable during the study period, while both rate and compositional changes in the Los Angeles area were associated with much lower levels of total ridership. Overall, our findings demonstrate the important role of demand-side factors in understanding aggregate transit use and suggest that planners and managers may have limited policy tools at their disposal when seeking to bolster ridership levels.

research report

Vehicle Purchasing Behavior, Expenditure, and Potential Barriers to Uptake of Battery Electric Vehicles in Underserved Communities

Abstract

Plug-in electric vehicles (PEVs), including both battery-electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) are crucial for reducing emissions and meeting sustainability targets, yet their adoption has been limited primarily to higher-income and new car buyers, leaving most low-income households without access. To help inform policies that will accelerate access to used BEVs in particular, this study explored car buying behavior, costs, and usage within and between groups defined by vehicle condition (new vs. used), fuel type (battery-electric vehicles [BEVs] vs. internal combustion engine vehicles [ICEVs], and income level. BEV owning, new-car buying, and having higher income were each associated with one another. On average the proportion of total income spent on vehicle-related expenses is at least six times higher for households with incomes less than $75,000 than households with incomes of $250,000 or more. While BEVs offer savings in maintenance and fuel cost compared to ICEVs, the initial price for both new and used BEVs may need to be subsidized to alleviate cost burden for lower-income households. Used car buyers, ICEV owners, and lower-income households predominantly do not purchase or maintain their vehicles at automaker dealerships and tend to buy older vehicles with more mileage than would be covered by BEV warranties. These findings have implications for the current structure of financial incentives being limited to automaker dealerships. Other possible barriers to BEV uptake for lower-income households and used car buyers, include reliability concerns and limited home charging access. BEV adoption across all income groups could be increased by broadening eligibility for incentives, enhancing battery warranties, offering battery replacement rebates, and expanding home charging infrastructure.

policy brief

Opportunities to Improve Patient Transportation Access: Piloting a Transportation Resource Fair at the Saban Community Clinic

Abstract

People who need health care services but do not have access to an automobile are more likely to experience challenges getting to health care appointments. A lack of transportation is a problem for patients and healthcare providers. Healthcare providers and patients would benefit from transportation improvements but cannot make systematic transportation changes. Therefore, healthcare clinics are looking for strategic opportunities to help their patients address transportation needs, and we partnered with the Saban Community Clinic (SCC) in Los Angeles to find ways to support their patients’ transportation needs. Most patients have public insurance through Medi-Cal, and a third are uninsured. In 2022, UCLA partnered with the Saban Community Clinic to better understand their patients’ transportation challenges and determine what strategic transportation efforts the clinic could consider. This project found that many patients travel
long distances from South Los Angeles to clinic locations.

preprint journal article

Provably Safe and Human-Like Car-Following Behaviors: Part 1. Analysis of Phases and Dynamics in Standard Models

Abstract

Trajectory planning is essential for ensuring safe driving in the face of uncertainties related to communication, sensing, and dynamic factors such as weather, road conditions, policies, and other road users. Existing car-following models often lack rigorous safety proofs and the ability to replicate human-like driving behaviors consistently. This article applies multi-phase dynamical systems analysis to well-known car-following models to highlight the characteristics and limitations of existing approaches. It begins by formulating fundamental principles for safe and human-like car-following behaviors, which include zeroth-order principles for comfort and minimum jam spacings, first-order principles for speeds and time gaps, and second-order principles for comfort acceleration/deceleration bounds as well as braking profiles. From a set of these zeroth- and first-order principles, it derives Newell’s simplified car-following model. Subsequently, the study analyzes phases within the speed-spacing plane for the stationary lead-vehicle problem in Newell’s model and its extensions, which incorporate both bounded acceleration and deceleration. It then analyzes the performance of the Intelligent Driver Model and the Gipps model. Through this analysis, the study highlights the limitations of these models with respect to some of the aforementioned principles. Numerical simulations and empirical observations validate the theoretical insights. Finally, it discuss future research directions to further integrate safety, human-like behaviors, and vehicular automation in car-following models, which are addressed in Part 2 of this study, where it develops a novel multi-phase projection-based car-following model that addresses the limitations identified there.

published journal article

Investigating Travel Demand Heterogeneity During and After the Pandemic in the Northern California Megaregion: A Data-Driven Analysis of Origin-Destination Structural Patterns

Abstract

The study delves into the complexities of travel disruption and recovery during and after the COVID-19 pandemic. Using a data-driven methodology, we explore spatial-temporal patterns across regions by times of the day, weekdays/weekends, and trip purposes. Using passively collected location-based data from January 2019 to October 2021 in the Northern California Megaregion, our analysis compares travel patterns through the structural similarity of origin-destination (OD) matrices. Introducing the concept of a “local sliding geographical window” based on natural trip flow, the study identifies various impacts of the pandemic on travel demand including but not limited to (a) trip volume and recovery (e.g., weekday trips dropped by 47% in April 2020, gradually recovering already by October 2021); (b) impact on home-based work and other trips which were significantly disrupted on weekdays compared with non-home-based; (c) OD pattern changes (e.g., all sub-regions experienced significant changes, but the San Francisco Bay area faced the maximum disruptions); (d) gradual recovery with regional variations (e.g., San Francisco lagged in its travel activity recovery but this improved after April 2021, whereas the Northern San Joaquin Valley recovered fastest); (e) disruption and recovery linked to socioeconomic factors (e.g., parts of San Francisco, characterized by higher income, white-collar jobs, faced maximum disruption, whereas the Northern San Joaquin Valley, with a higher proportion of blue-collar workers, experienced the least disruption); and (f) differential recovery rates across and within regions, with areas rich in white-collar jobs showing slower recovery for work trips compared with areas with a higher proportion of blue-collar jobs.