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.

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.

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

Estimating the Electricity System Benefits of Scaling up E-Bike Usage in California

Abstract

The replacement of short-distance, low-occupancy automobile trips with electric bicycles (e-bikes) can reduce energy consumption and emissions related to transportation activities. Due to the low electricity consumption per mile of e-bikes compared to battery electric vehicles, e-bikes can also reduce the peak and total electric loads that battery electric vehicles impose on local and regional electricity systems, potentially translating into benefits for electricity system operation and distribution infrastructure lifetimes. This study leverages synthetic travel pattern data for the San Diego, California, region, along with National Household Travel Survey data for bike trip characteristics to estimate the battery electric vehicle trips that e-bikes can displace. Moreover, we use electricity system modeling to estimate the electricity system cost savings in the years 2030 and 2045 from replacing battery electric vehicle trips with e-bikes. We find that using e-bikes to displace battery electric vehicle trips where feasible can reduce California wholesale electricity system costs by up to 3.0% in 2030 and 3.8% in 2045, translating to annual savings of $770 million and $1360 million, respectively. Additional potential savings can also occur in the distribution system through extending the lifetime of distribution transformers, depending on the current loading of distribution transformers on a residential circuit.

policy brief

California’s High-Speed Rail Yields the Greatest Accessibility Gains to the Most Vulnerable Communities

Abstract

A major criticism of California’s high-speed rail project is that it will mainly serve urban elites and that low-income people and people of color likely won’t be able to afford the fares. Also, the project may benefit the middle-income group the least since the proposed station locations, usually in or near city centers, will probably serve high- and low-income populations better than middle-income families. Besides these arguments, however, there are very few studies that have analyzed the equity impacts of California’s high-speed rail project. Current studies have either focused on benefits to California residents as a whole with little consideration to the specific opportunities for how high- speed rail will improve the lives of marginalized groups; or only studied the disproportionate adverse impacts received by marginalized groups.

policy brief

Charging-as-a-Service is an Innovative Business Model that Could Help with California’s Vehicle Electrification Goals

Abstract

Access to electric vehicle (EV) charging infrastructure is critical to advancing California’s EV adoption goals. The California Energy Commission has projected the state needs “nearly 1.2 million” chargers by 2030 “to meet the fueling demands of 7.5 million passenger plug-in electric vehicles.” Currently, California has about 152,000 publicly available EV chargers.

Innovative asset ownership models, like charging-as-a-service (CaaS), could help overcome some of the barriers to deploying and maintaining charging infrastructure. For example, CaaS providers could procure, install, maintain, and replace charging equipment for subscription customers. To better understand how CaaS solutions could expand EV use and charging access, this researchers conducted semi-structured interviews with 13 CaaS companies, electric utilities, and customers to identify the perceptions, challenges, and opportunities of the CaaS business model in addressing charging station needs in California.

research report

Enhanced Perception with Cooperation between Connected Automated Vehicles and Smart Infrastructure

Abstract

This project showcased how advanced infrastructure data supports connected automated driving systems in perceiving their surroundings cooperatively. The UCLA Mobility Lab established a smart intersection on the UCLA main campus, collecting infrastructure LiDAR data and combining it with sensor and global navigation satellite system data for research on cooperative perception. It also examined the system’s resilience to data spoofing attacks via the V2X channel from a compromised onboard unit (OBU), evaluating different attack scenarios to understand emerging security risks in V2X-based cooperative perception technologies.

published journal article

Transitioning Ridehailing Fleets to Zero Emission: Economic Insights for Electric Vehicle Acquisition

Abstract

Under California’s Clean Miles Standard (or SB 1014), transportation network companies (TNCs) must transition to zero-emission vehicles by 2030. One significant hurdle for TNC drivers is the electric vehicle (EV) acquisition and operating costs versus an internal combustion engine (ICE) vehicle. This study therefore evaluates net TNC driving earnings through EV acquisition pathways—financing, leasing, and renting—along with EV-favoring policy options. Key metrics assessed include (1) total TNC income when considering service fees, fuel costs, monthly vehicle payments, etc., and (2) the time EVs take to reach parity with their ICE counterparts. Monthly comparisons illustrate the earning differentials between new/used EVs and gas-powered vehicles. The analyses employs TNC data from 2019 to 2020 suggesting that EV leasing is optimal for short-term low-mileage drivers; EV financing is more feasible for those planning to drive for TNCs for over two years; EV rentals are only optimal for higher mileages, and they are not an economical pathway for longer-term driving. Sensitivity analyses further indicate that EV charging price discounts are effective in shortening the time for EVs to reach cost parity over ICEs. Drivers may experience a total asset gain when reselling their TNC vehicle after two to three years.

preprint journal article

Political Preferences and Transport Infrastructure: Evidence from California's High-Speed Rail

Abstract

We study how political preferences shaped California’s High-Speed Rail (CHSR), a largetransportation project approved by referendum in 2008. Voters’ support responded significantly to the projected economic gains in their tract of residence, as measured by a quantitative model of high-speed rail matched to CHSR plans. Given this response, a revealed-preference approach comparing the proposed network with alternative designs identifies strong planner’s preferences for political support. The optimal politically-blind design would have placed the stations nearer to California’s dense metro areas, where it was harder to sway votes, thus increasing the projected economic gains.

published journal article

A Case for Race and Space in Auto Ownership Modeling: A Los Angeles County Study

Abstract

Auto ownership behavior is driven by complex relationships that can vary dramatically across different traveler groups and communities. Differences in auto ownership among racial groups have been of particular interest, given ongoing efforts to advance equity in transportation outcomes. There are a number of studies documenting racial disparities in auto ownership associated with racial and ethnic residential clustering, termed “automobile mismatch.” Yet, these differences in auto ownership behavior by race and residential location are virtually never considered in models of travel behavior, despite calls for the consideration for race in transportation planning and decision making. This study aims to bridge the gap between understandings of the connections between race and space and transportation outcomes, using Los Angeles County as a case study. A series of auto ownership model specifications are used to investigate statistical connections between the racial and ethnic categories of residents, and neighborhoods, revealing systematic variations across racial and spatial dimensions. The composite model, which includes racial and spatial indicators, outperforms the base model, suggesting that the inclusion of race and space explains significantly more information on variations in auto ownership and provides a superior fit to the data. Our findings also suggest that the exclusion of racial and spatial indicators may lead to overestimation of certain effects, and may completely misrepresent the importance of certain household, individual-level, and built environment effects in explaining auto ownership preferences. Given the increasing attention to equity and representation in transportation outcomes, models that exclude considerations for race and space may be poorly positioned to support meaningful transportation equity analyses.