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.

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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.

Exploring the Impacts of Working at Home and Online Shopping on Post-Pandemic Travel and Transportation Policy in California

Status

In Progress

Project Timeline

August 5, 2024 - August 31, 2025

Principal Investigator

Campus(es)

UC Berkeley

Project Summary

The COVID-19 pandemic of ongoing changes in the workplace and within households that have significantly influenced travel patterns. Foremost among these are two related trends: people working for pay at home, and increasing household reliance on online shopping and home package delivery. Household travel over this period has markedly changed, with a precipitous falloff in transit ridership and an increase in the share of trips conducted via auto.

This research project explores how working from home and urban freight delivery have shaped household travel behavior in the post-pandemic period. Specifically, the project team will: (i) review empirical literature on trends in working from home and home freight delivery (and the relationship between them) before and during the pandemic; (ii) conduct data description and analysis of four national secondary data sources available through 2022, and explore the relationship between working at home, home freight delivery, online shopping, and patterns in trip frequency and distance by mode; (iii) conduct an online survey in one or more large metropolitan areas in California to explicitly investigate current self-reported and pre-pandemic household behavior, focusing on working at home, online shopping, home freight delivery, and travel behavior as mediated by occupation, income, neighborhood characteristics, and race/ethnicity; and (iv) as a final step, explore policy and planning responses by regional and local agencies.

Examining the Interplay of Remote Work, Economic Complexity, and City Structure in How People Travel at the Individual Level and a Metropolitan Scale

Status

In Progress

Project Timeline

August 5, 2024 - February 28, 2026

Principal Investigator

Campus(es)

UC Berkeley

Project Summary

Post-pandemic travel is being shaped by three important and interrelated factors: (i) work-from-home (i.e., telecommuting) alters daily commutes, (ii) regional economic complexity determines telecommuting potential, and (iii) city structure differentiates the spatial distribution of teleworkers, remote jobs, and amenities. Despite a growing understanding of changes in individual travel behavior, little is known on a regional scale about possible “new normal” mobility scenarios and trajectories as they unfold over the long term.

Building on existing studies, this research project leverages location-based data to dissect the interplay of work-from-home, regional economic complexity, and city structure in reshaping the commuting dynamics of California’s major metro areas. Specifically, the analyses will (i) apply comprehensive mobility metrics to examine longitudinal and cross-population telecommuter behavior, and (ii) propose novel measures to characterize regional telecommuting dynamics based on industry diversity and sophistication, and urban spatial structure. These parameters offer critical insights into metropolitan dynamics driven by shifting individual mobility under an emerging work-from-home economy.

Pandemic-related Shifts in Work, Travel, and Transit Use: Implications for Public Policy

Status

In Progress

Project Timeline

July 1, 2022 - December 31, 2023

Principal Investigator

Project Summary

While the COVID-19 pandemic dramatically affected travel and transportation systems, driving has largely returned to pre-pandemic levels, even as a significantly larger share of the workforce works from home full- or part-time. However, there have been significant changes in the timing and patterns of car travel since before the pandemic. Moreover, public transit systems have been especially hard hit, and riders have proven slow to return. While transit use by those unable to drive (who are more likely poor, immigrants, people of color, and/or disabled) has substantially recovered since the shutdowns in the spring of 2020, daily commuting to and from major employment centers collapsed and is just beginning to recover. The shifts in motor vehicle travel and the more dramatic changes in public transit use are both likely related to workplace changes, as the number of remote and hybrid workers has increased. The longer-term effects of the pandemic on travel remain uncertain, as do the appropriate policy responses to changing traffic patterns broadly, and to depressed transit ridership specifically. Public transit is a key transportation pillar of California’s climate and equity goals, which will be harder to meet with driving up and transit riding down. This research will investigate how metropolitan travel patterns have shifted in the late stages of the pandemic and what these shifts imply for driving and public transit use in the years ahead. The project will build on current research underway in Northern and Southern California drawing on and integrating both survey and mobile device data that reflect traveler movements before and during the pandemic. Specifically, it will look at how these pandemic-induced shifts in travel relate to the rise of working from home, how this might affect the demand for public transit in the future, and what evidence-based policy recommendations can be offered to state, regional, and local transportation agencies to better respond to and address these new patterns of travel demand.

Exploring Gender and Travel Complexity

Status

In Progress

Project Timeline

October 1, 2023 - March 31, 2025

Principal Investigator

Campus(es)

UCLA

Project Summary

In the United States, research reveals that women tend to travel shorter distances and durations compared to men. They also often have more complex travel patterns as they balance work and household responsibilities. This distinct travel behavior creates mobility challenges that can limit women’s access to resources and opportunities. Recently, several forward-thinking California transportation agencies have started efforts to gain a better understanding of women’s travel needs. They aim to implement services and policies that cater to these needs. However, existing analyses are often limited in scope, and as a result, they underestimate the intricacies of women’s travel patterns.

This project will analyze gender-related differences in the complexity of daily travel patterns in California. The analysis will rely on data from the California add-on to the 2017 National Household Travel Survey (NHTS), which includes information about all trips, modes of transportation, and purposes within a single travel day. The research will specifically focus on three aspects of complexity: i) trip complexity, which measures the number of linked destinations in a chain of trips; ii) modal complexity, which evaluates the number of different transportation modes used; and iii) spatial complexity, which assesses the geographic extent of the activity space. The study will quantify travel complexity, investigate the connection between complexity and gender, and estimate how gender relates to the key factors influencing these outcomes, such as race, income, household structure, and the presence of children. The findings from this research can provide valuable insights to transportation agencies currently involved in gender-inclusive planning efforts. Additionally, this data may justify greater attention to gender-related issues among California’s transportation agencies and organizations.

Working from Home and Travel: What Does the Future Hold?

Status

In Progress

Project Timeline

September 1, 2023 - December 31, 2024

Principal Investigator

Project Team

Campus(es)

UCLA, UC Davis

Project Summary

The COVID-19 pandemic transformed the American work landscape. Before March 2020, the majority of workers (about 95%) worked outside of their homes most of the time. In the spring of 2020, due to stay-at-home orders and new online video-communication technologies, over half of workers started working from home. Although many aspects of life have returned to pre-pandemic norms, remote work is a notable exception. As of May 2023, approximately 58% of U.S. companies now permit employees to work from home at least part of the week, indicating that remote work is here to stay. While it was hoped that telecommuting would significantly reduce vehicle travel, traffic congestion, and transportation emissions, research suggests that working from home is not associated with reduced vehicle travel. This is because home-based workers tend to swap fewer commute trips for more household-related trips, and when they do commute to work, they often live farther from their workplaces. However, the surge in remote work during and after the pandemic raises questions about the relevance of pre-pandemic research on this topic.

This project aims to address the following questions: i) Does pre-pandemic research on who works from home, in what occupations, and how they travel still hold today now that many more work from home? ii) How have commute mode shares, durations, and departure times changed, and how do these changes relate to working from home? iii) What types of neighborhoods have hosted the largest and smallest changes in traffic and transit use, and does the ability to work from home explain these patterns? This project builds on the researchers’ recent synthesis of remote work and travel, as well as their studies on transit and vehicle travel during the pandemic. It will analyze national and California data from the Public Use MicroSample to understand the demographics of those working from home and changes in commuting post-pandemic. Additionally, it will use vehicle and transit movement data from StreetLight to examine neighborhood-level changes in vehicle travel and transit use, exploring their correlation with the ability to work from home.