Our Experts

Tierra Bills

Assistant Professor, Public Policy and Civil and Environmental Engineering, UCLA

Recent Projects

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Our Experts

Jesus M. Barajas

Assistant Professor, Department of Environmental Science and Policy, UC Davis

Recent Projects

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Research Team:

Jesus M. Barajas (lead)

UC Campus(es):

UC Davis

Research Team:

Jesus M. Barajas (lead)

UC Campus(es):

UC Davis

policy brief

Decline of Rail Transit Requires New Strategies

Abstract

During the pandemic, California’s four major rail systems— Bay Area Rapid Transit (BART), San Diego Metropolitan Transit System (MTS), Sacramento Regional Transit (SacRT), and Los Angeles County Metropolitan Transportation Authority (LA Metro)—experienced an average ridership decline of 72 percent between 2019 and 2021. BART had the greatest decrease (87 percent) and MTS the lowest (47 percent). However, ridership changes varied significantly across individual stations, with stations located in the central business district or at the end of lines having the highest ridership losses. Land use, development density, and the pedestrian environment are strongly associated with station-level transit ridership. This brief examines how these characteristics affect transit ridership pre- and post-COVID and how they differ across station types based on longitudinal data collected between 2019 and 2021 for 242 rail stations belonging to BART, MTS, SacRT, and LA Metro.

policy brief

What Challenges Can Arise from Coordinating Housing Development with Transportation?

Abstract

More systematic coordination between transportation and housing development is increasingly recognized as a promising strategy for creating more sustainable communities. One approach is to encourage higher density affordable housing developments near transit or in similarly transportation-efficient areas, such as locations with low vehicle miles traveled (VMT). However, little is known about how transportation access should be considered in guiding housing development, what challenges can arise from coordinating housing development with transportation, and what the state can do to better deal with these challenges and achieve more equitable residential densification.

This brief examines equity issues and other challenges that may arise in pursuing transportation-informed housing development. Specifically, it touches on the potential impacts of Senate Bill 743, which made it easier to build more housing in low VMT locations by shifting the way traffic impacts from new housing development are evaluated under the California Environmental Quality Act. It also explores ways to achieve more inclusive development in non-rail transit areas which have received less attention compared to rail transit areas.

research report

Assessing the Potential for Densification and VMT Reduction in Areas without Rail Transit Access

Abstract

While transportation infrastructure and efficiency should inform where to build more housing, little is known about how housing allocation and development processes can be coordinated more systematically with transportation. To date, transportation-housing coordination has often relied on the densification of areas near rail transit stations, putting heavy burdens on these locations and their residents. Much less attention has been paid to how densification can be achieved in a more equitable manner by encompassing other sites.

This report directs attention to non-rail locations, specifically low vehicle miles traveled (VMT) areas and bus corridors, and examines the challenges that can arise in promoting densification more broadly. It shows that data uncertainties can make it challenging to identify low VMT locations and that prioritizing only low VMT locations for residential development may have limited effectiveness in expanding housing opportunities in high opportunity areas. The report further explores ways to achieve more inclusive densification of non-rail transit areas and highlights the importance of anti-displacement strategies.

research report

Rail Transit Ridership Changes in COVID-19: Lessons from Station Area Characteristics

Abstract

The COVID-19 pandemic has had a significant impact on public transit ridership in the United States, especially for rail transit. Land use, development density, and the pedestrian environment are strongly associated with station-level transit ridership. This study examines how these characteristics affect transit ridership pre- and post-COVID and how they differ across station types based on longitudinal data for 242 rail stations belonging to Bay Area Rapid Transit, San Diego Metropolitan Transit System, Sacramento Regional Transit, and LA Metro between 2019 and 2021.

The research team found an overall 72% decrease in station-level ridership, but changes were not uniform. Station areas with a higher number of low-income workers and more retail or entertainment jobs tend to have lower ridership declines, while areas with a large number of high-income workers, high-wage jobs, and higher job accessibility by transit had more ridership losses. When comparing station area ridership and activity changes based on mobile phone user data, ridership declined more drastically than activity across all four rail systems, which implies that rail transit riders switched to other modes of transportation when accessing the station areas. Given these findings, it is likely that rail transit services oriented toward commute travel, especially core station areas with jobs for higher-income workers, will continue to have an uneven recovery, posing critical implications for transit resilience planning and equity in the post-pandemic era. Considering sources of funding other than passenger fares to sustain rail transit, strategizing to reinvent and reinforce downtowns as destinations, and shifting rail transit services to appeal to non-commute travel can be promising strategies to support rail transit.

published journal article

Using a Modified Delphi Approach to Explore California's Possible Transportation and Land Use Futures

Abstract

Many methods exist for engaging experts in interactive groups to explore, clarify, and/or decide on various issues. In an investigation of four possible future scenarios concerning transportation and land use in California, researchers at UCLA developed a novel “hybrid policy Delphi” method for use with a panel of 18 experts. Through this process, panel members discussed and reflected on the scenarios in multiple ways. The scenario they considered most desirable they also deemed least likely to occur, and they foresaw the likely trajectory of California transportation and land use leading to less desirable scenarios. The mix of discussion and questionnaires traded the benefit of anonymity for the benefit of exploratory, interactive discussion. In addition, the use of surveys before and after meetings allowed the research team to track changes in panel opinion on a central question and discuss the survey results at meetings, at the cost of greater administrative effort.

Our Experts

Charisma Acey

Associate Professor, City and Regional Planning, IURD, UC Berkeley

Recent Projects

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Understanding Post-Pandemic Travel Behavior Patterns and Trends in California

Status

In Progress

Project Timeline

October 1, 2024 - September 30, 2025

Principal Investigator

Campus(es)

UC Irvine

Project Summary

COVID-19 has reshaped people’s mobility patterns worldwide (Arellana et al., 2020; Hensher et al., 2021; Orro et al., 2020; Park, 2020), including in the US (Brough et al., 2021; Ehsani et al., 2021; Hu and Chen, 2021; Kim and Kwan, 2021; Liu et al., 2020). Public transit and transportation network companies (TNCs) were hit particularly hard (Du and Rakha, 2020; Khatun and Saphores, 2023). For example, San Francisco experienced a staggering 94% drop in transit ridership during the lockdown (Toussaint, 2020), and an 87% drop in Uber trips in April-May 2020 compared to early 2020 (Brown and Williams, 2023). 

Many public policies that aim to reduce solo driving, congestion, and vehicle emissions, and increase walking, biking, and shared mobility are based on pre-pandemic travel behaviors. However, higher levels of working from home, streaming, e-shopping, and micro-mobility options post-pandemic have changed travel behavior. How does post-pandemic household travel patterns differ from their pre-pandemic values? Do the policies and plans that aim to advance California’s mobility, environmental, and equity goals warrant review and possible amendment? The purpose of this project is to answer these questions and to analyze the potential impacts of changes in household travel on the California Transportation Plan 2050.

Improving Induced Travel Demand Forecasting for Different Road Types: A Research Synthesis and Meta-Analysis

Status

In Progress

Project Timeline

October 1, 2024 - September 30, 2025

Principal Investigator

Keuntae Kim

Campus(es)

UC Davis

Project Summary

The current approach to estimating the environmental impacts of roadway expansions often underestimates the induced travel effect, leading to inaccurate forecasts of vehicle miles traveled and project outcomes like greenhouse gas emissions and traffic congestion. The Induced Travel Calculator, developed by researchers at the National Center for Sustainable Transportation, helps estimate induced vehicle miles traveled, but there is debate about which vehicle miles traveled elasticities to use for accurate forecasts across different contexts. Since Caltrans began requiring induced travel analysis for capacity-expanding projects in 2020, these elasticity estimates have become increasingly important.

This research project seeks to enhance the understanding of induced vehicle miles traveled elasticity to help practitioners and policymakers more accurately account for the induced travel effect in both project-specific and policy-level decisions. Through a systematic literature review and meta-analysis, the study will synthesize findings from a broad range of induced travel research and employ meta-regression to calculate pooled elasticity estimates. This approach will facilitate the examination of variability in elasticity across different roadway types, including class 1 (interstate highways) and class 2 (freeways and expressways). By analyzing these variations, the meta-regression will help uncover key factors influencing differences in induced VMT elasticity, such as geographic location, traffic conditions, and project characteristics.