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

Status

In Progress

Project Timeline

October 1, 2021 - March 31, 2023

Principal Investigator

Project Team

Jaime Soza Parra, Junia Compostella

Campus(es)

UC Davis

Project Summary

Over the past year, academic studies of COVID-19’s impact on the transportation sector have focused on preferences for and perceptions of different travel modes, changes in vehicle mileage, traffic congestion and pollutant emissions, public transportation operations and ridership, and equity considerations, among many others. Overall, some of the impacts of the pandemic are likely to be transitory whereas others might have longer-term consequences. In partnership with several planning agencies, the research team will construct short-range mobility scenarios for Northern California to help inform planning and policy-making processes. The project team will review the available literature on the impacts that the pandemic has had on different cities’ passenger mobility patterns (i.e., non-freight related travel), focusing on studies based on the analysis of both passively-collected data (e.g., location data from personal mobile devices and survey data (and their integration). The research team will use passively-collected data supplied by the Streetlight Data platform from various location-based services, and information from concurrent survey research being conducted by UC Davis researchers, to build a baseline and future multimodal mobility scenarios to explore the extent to which recent changes induced by the pandemic (e.g., increased telecommuting, remote shopping, mode shifts from public transit to cars, changes in vehicle ownership, changes in time of day of trips) might affect multimodal passenger travel (e.g., changes in vehicle mileage, trip patterns, transit ridership, and bicycling) in different geographic locations, at different times of day, and by multiple modes. Finally, the project team will draw insights and policy recommendations to help inform agencies’ investment and policy decisions.

Addressing the Impacts of Truck Idling and Searching for Parking on Environmental Justice Communities

Status

In Progress

Project Timeline

January 1, 2022 - June 30, 2023

Principal Investigator

Project Team

Ivan Xiao, Carlos Otero, Daniel Rivera

Project Summary

Truck idling and searching for parking consume fuels and produce emissions that degrade air quality. In the U.S., more than 6 billion gallons of fuel at an estimated cost of $20 billion are wasted each year due to idling. An idling heavy‐duty diesel truck emits about 10 times more nitrogen oxides (NOx) than a passenger car, and truck idling emits more than 11 million tons of carbon dioxide and more than 180,000 tons of NOx per year, in addition to particulate matter and other air pollutants. Trucks usually idle near warehouses and distribution centers, and research has shown that these facilities are disproportionally located in disadvantaged communities. The California Air Resources Board (CARB) has been trying to address the negative consequences of community exposure to particulates from idling through various policies such as Airborne Toxic Control Measures. Moreover, emissions from idling or searching for parking are not the only problem; a recent study of disadvantaged communities in Southern California found that safety is also a critical factor. However, despite new regulations and technological improvements, the negative effects continue to occur, especially in disadvantaged communities. This research project addresses the issue of truck idling and searching for parking in disadvantaged communities in the Central Valley, specifically in Kern County, where the CARB has already identified the cities of Shafter, Arvin, and Lamont as environmental justice communities (as part of Assembly Bill 617 implementation). First, using publicly available information about parking and idling behavior from GeoTAB’s Intelligence Data tool, the team will conduct spatial analyses to identify truck parking and idling hotspots. This information will be enhanced with data from other public sources about the physical infrastructure, and socio‐demographic and economic conditions, to develop exploratory econometric models to identify the factors that contribute to idling time, or time and distance spent searching for parking. The team will use data from the San Joaquin Valley Air Pollution Control District’s Community Air Monitoring portal to determine whether higher emission levels are associated with locations with more idling or searching for parking. Using emission rates from the CARB’s Emission FACtor (EMFAC) model, the team will estimate the emissions from idling and searching for parking and quantify the vehicle mileage traveled in and around the hotspots. Second, the team will conduct fieldwork at the various locations (hotspots identified in AB 617 and other disadvantaged communities) to document actual truck parking/idling conditions to identify other factors that may affect this behavior, and any additional negative effects brought about. Through collaboration with the Kern Council of Governments and Caltrans, the team will gather input and feedback from the local impacted communities. It is expected that the process developed in this project could be replicated with other communities.

Assessing the Incorporation of Racial Equity into Analytical and Modeling Practices in Transportation Planning

Status

Complete

Project Timeline

February 15, 2021 - August 31, 2021

Principal Investigator

Project Team

Gian Claudia Sciara

By Transit, By-Right: How Housing Development Approval Processes Can Support Higher Transit-Friendly Density

Status

Complete

Project Timeline

July 20, 2020 - June 30, 2021

Principal Investigator

Project Team

Michael Manville, Shane Phillips

Campus(es)

UCLA

Project Summary

Density is important for successful transit service, and recent state and local housing policies tie production to transit proximity. Multifamily housing, however, often faces many obstacles. One important obstacle is that most cities evaluate transit-adjacent multifamily housing developments with discretionary processes. Discretionary approval is slow and uncertain: developers and city officials negotiate project-by-project, sometimes adding years to project timelines. The resulting delays and conditions can depress housing production and raise costs, with the result being fewer transit-accessible homes. An alternative is by-right approvals, which automatically approve projects that meet published standards, bringing housing to market quicker and at a lower cost. By-right approval could deliver denser and more affordable housing to urban areas, supporting increased transit ridership and other mobility goals. Because by-right approval is relatively rare, however, estimates of how much more housing it could deliver remain vague. This project used the City of Los Angeles’ Transit-Oriented Communities (TOC) program to help identify the role of by-right approval in delivering more housing near transit. The TOC program presents a rare opportunity to compare the impact of by-right and discretionary approvals in a single political and market context. The analysis compared costs, project timelines, and community benefits of by-right and nearby discretionary projects. The research team estimated reductions in project costs and time to market resulting from by-right approvals compared to affordable units provided by developers. This quantitative analysis was complemented by interviews with developers, community-based organizations, lenders, city officials, and others. The research team found that by-right projects were permitted 28% faster than discretionary projects, controlling for project and neighborhood characteristics. By-right projects also had less variance in their approval times, suggesting that by-right approval offers not just more speed but more certainty.

The Spatial Dilemma of Sustainable Transportation and Just Affordable Housing

Status

Complete

Project Timeline

July 20, 2020 - June 30, 2021

Principal Investigator

Campus(es)

UCLA

Project Summary

Siting subsidized affordable housing in dense urban areas near transit can help the state meet its environmental goals by reducing vehicle travel and lowering the amount of vehicle miles traveled (VMT). However, more information is needed on exactly how best to allocate housing subsidies that both improve access to economic and educational opportunities for underrepresented groups, and improve mobility throughout the state more broadly while reducing VMT. This project will address the challenge of identifying neighborhoods that are best suited to promoting the state’s housing and environmental goals. The research will look at VMT rates in neighborhoods with affordable housing and examine the access and environmental benefits of subsidized affordable housing near transit in dense, urban areas. The project will assemble tract-level data and indicators, and will analyze changes in the location of subsidized and non-subsidized housing between 2007 and 2018 to determine if the current and expected future distribution of affordable housing is consistent with the state’s VMT reduction goals. Findings from this analysis will be used to identify target priority areas for renters at the policy and program levels, including the siting of new federal Low-Income Housing Tax Credit construction. In addition, the project will examine if and how transportation considerations are being incorporated into three important and innovative housing programs, which have a shared goal of increasing residential choice and mobility.

Changes in Traffic Patterns and Localized Air Quality in Southern California

Status

Complete

Project Timeline

June 17, 2020 - December 1, 2021

Principal Investigator

Shams Tanvir

Project Summary

This project will develop an integrated analytical framework to determine changes in traffic at various scales (local, corridor level, and regional) due to the COVID-19 sheltering-in-place orders measures and conduct an analysis of the relationship of traffic-related changes to critical air pollutant concentrations. Traffic data and air quality data will be used from various existing sources, along with satellite-based measurements to complement the land-based measurements. The research team will estimate spatial-temporal changes in emissions for several traffic-related pollutants (e.g., NOX, CO, CO2, and HC). The team will then conduct a map-based relationship analysis between localized air-quality monitoring data and the estimated emissions. Finally, the team will overlay the map on CalEnviroScreen maps and correlate the changes with geographic locations of disadvantaged communities.

Autonomicity: A Modeling Framework for Equitable Policy Analysis for Future Transportation

Status

In Progress

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Campus(es)

UC Irvine

Project Summary

An agent‐based simulation platform (“Autonomicity”) has been under development at UCI with SB‐1 funds. This platform has the necessary modules with proper state‐of‐the art routing, ride‐matching, pricing and other algorithmic components, as well as the real‐time communication among them. While the platform itself is not network‐specific, future mobility requires a study context, and a network in the city of Irvine, CA, is currently incorporated. This proposal is to develop the platform as a policy tool to study efficient and equitable/fair allocation of transportation supply, with methodological focus on congestion pricing under traveler heterogeneity. Current congestion pricing schemes may cause social barriers for low‐income populations. Thus, we devise a smart mobility platform to study equitable options where travelers desiring a faster travel option pay for it, and travelers willing to yield his/her fastest option receive incentives. New behavioral paradigms such as envy‐theory will be used. Two main modules introduced in Autonomicity will be: 1) a pricing module to find the optimal tolls/incentives and 2) a dynamic traffic assignment module to find optimal systemwide traffic patterns. The research will result utilities for a user‐friendly decision‐support tool for policymakers.

Identifying Types of Telecommuters based on Daily Travel and Activity Patterns

Status

In Progress

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Campus(es)

UC Irvine

Project Summary

With the recent advent of telecommunications and information technologies, telecommuting becomes a rising trend as one of the most important alternative work arrangements. Moreover, due to the current worldwide outbreak of the COVID-19 disease, this choice has turned out to be a more vital one than ever. It is, therefore, crucial to identify the potential groups of workers who are more likely to be the telecommuters and to understand how the telecommuters schedule their daily activities and travel. Our research goal is to address these issues. In particular, we will
perform the following three tasks: (1) identification of a number of distinct groups of telecommuters with a representative activity-travel pattern and a similar degree of telecommuting adoption (2) finding out similarities and differences in activity-travel behavior between national-level and regional-level (California) telecommuters and between commuters and telecommuters, and (3) investigation of impacts of telecommuting on individual’s time-use and tour behavior as well as the overall transportation system. Two large household travel survey datasets—2012 California Household Travel Survey (CHTS) and 2017 National Household Travel Survey (NHTS) will be used to conduct necessary analysis. This research is expected to provide valuable insights to policy makers on various telecommuter groups and their activity-travel patterns, adoption of telecommuting, and its impacts on travel.

COVID-19, Commuting, and E-Shopping: Understanding Current and Future Impacts in California

Status

Complete

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Project Summary

With widespread business closures and stay-at-home restrictions due to COVID-19, commuting has dropped while telecommuting and e-commerce have soared. This joint UC Berkeley/UC Irvine project seeks to understand opportunities and potential impacts of COVID-19 on commuting and e-commerce. We propose a mixed-method approach comprised of expert interviews, focus groups in Northern and Southern California, an online survey of Californians (n=~1,000), and a survey of super commuters (n=up to 500). Our survey of the California population will show how travelers have been affected by COVID-19 for commuting and shopping and provide vital information about mode shift, public transit use, and willingness to share transportation post COVID-19. Understanding how Californians work and shop is critical to informing a number of policies at various levels of government including: AB/SB 32 (California’s Climate Change Solutions Act); SB 375 (Smart Growth Strategies); SB 743 (Converting Level of Service to VMT metrics under the California Environmental Quality Act); and other local and state transportation demand management (TDM) and commute trip reduction laws, ordinances, and policies. The data collected on goods delivery behavior will also have widespread implications, such as recommending a new set of TDM policy strategies for retailers, freight/supply chains management, and other stakeholders.

Factors Affecting Development Decisions and Construction Delay of Housing in Transit-Accessible and Jobs-Rich Areas in California

Status

Complete

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Campus(es)

UC Irvine

Project Summary

Recent state legislation has attempted to address California’s housing affordability crisis by encouraging new development in transit-accessible and/or jobs-rich areas. But policymakers lack adequate information in two key areas: the effects of transportation laws and plans on the decisions of developers regarding whether and where to build housing; and the determinants of delays in approvals for proposed projects in jobs-rich and transit-accessible areas. Drawing on a unique dataset detailing all residential projects of five units or more that were approved from 2014 through 2017 in seven Southern California jurisdictions, this project will analyze the extent to which transportation policies, rules, plans, and investments influence the location of new housing and delay the construction of new housing. Using descriptive statistics and multivariate modeling, we will examine developers’ decisions concerning whether and where to build housing, identifying how project-level attributes and contextual variables, including those related to transportation, affect decisions about whether and where to build infill projects in jobs-rich and transit-rich locations. We will also conduct a systematic comparison of permitting timelines for otherwise comparable projects with different degrees of transit availability or job accessibility, along with multivariate modeling to assess the determinants of delay.