policy brief

Justice-Centered Mapping Tools for Selecting Electric Vehicle Charger Locations

Abstract

Millions of electric vehicles are expected on American roads in the coming decade. California alone will require over two million publicly accessible chargers to support over 15 million electric vehicles by 2035, and nationwide over 28 million total chargers will be needed by 2030. To assist local agencies and community stakeholders with identifying high-priority investment zones for charging infrastructure, a research team at UC Berkeley, developed a public, open-access platform to inform equity-oriented electric vehicle infrastructure decision-making. As part of this work, the team analyzed existing research, electric vehicle and mobility plans, and obtained input from California local and state government program leaders to gather data across four core categories: equity, transportation infrastructure, grid infrastructure, and community resources.

website

Trip Referral Portal for Accessible Transportation in Contra Costa County

Abstract

A directory website for accessible transit services is an online platform that aggregates and organizes information about various transportation options available within the designed area, with a prototyped function of recommending service providers.

policy brief

A Review of SB 1 Project Performance: Cost Overruns, Schedule Delays, and Cancellations

Abstract

The Road Repair and Accountability Act of 2017 (Senate Bill 1 or SB 1) aims to improve and enhance California’s transportation infrastructure. Like many infrastructure programs, however, there are concerns with project cost overruns, delays, and cancellations, as these can undermine program goals and negatively impact quality of life in California.
This brief highlights key findings from an analysis of quarterly Caltrans SB 1 project reports between 2018 and 2023 to provide insights into project costs, delays, and cancellations.

published journal article

Decisions & Distance: The Relationship Between Child Care Access and Child Care Travel

Publication Date

November 27, 2023

Author(s)

Evelyn Blumenberg, Madeline Wander, Zhiyuan Yao

Abstract

In the U.S., child care supply has long fallen short of demand, with variations across neighborhoods that differ by income, race, and ethnicity. Yet there is relatively little research on child care access, use, and travel. This study tests the relationship between formal child care supply and households’ use of formal care and home-to-child-care travel distances in California. Using a two-step floating catchment area method, the study develops a time-weighted spatial measure of child care access and apply this measure in statistical models to predict two outcome measures: the likelihood of making a home-to-child-care trip and travel distance to the child care center, controlling for other factors. Key findings are that child care access is associated with an increased likelihood of using formal child care—and among households that use such care, access is associated with shorter travel distances. The analysis underscores the importance of policies to address spatial barriers to child care, particularly in neighborhoods—low-income, Latinx, non-urban—where child care supply is limited.

research report

Developing a Safety Effectiveness Evaluation Tool for California

Publication Date

September 1, 2024

Author(s)

Jia Li, Michael Zhang, Yanlin Qi

Abstract

Crash modification factor (CMF) is an effectiveness measure of safety countermeasures. It is widely used by state agencies to evaluate and prioritize various safety improvement projects. The Federal Highway Administration (FHWA) CMF Clearinghouse provides CMFs for a broad range of countermeasures, but still, the existing CMFs often cannot meet the needs for characterizing the safety impacts of countermeasures in new scenarios. Developing CMFs, meanwhile, is costly, time-consuming, and requires extensive data collection. This study provides a low-cost and easily extendable data-driven framework for CMF predictions. This framework performs data mining on existing CMF records in the FHWA CMF Clearinghouse. The study also integrates multiple machine-learning models to learn the complex hidden relationships between different safety countermeasure scenarios. Finally, the proposed framework is trained against the CMF Clearinghouse data and performs comprehensive evaluations. The results show that the proposed framework can provide CMF predictions for new countermeasure scenarios with reasonable accuracy, with overall mean absolute errors less than 0.2.

research report

Modeling and Analyzing Cost Overruns, Delays, and Cancellations in Senate Bill 1 Projects

Abstract

In 2017, California passed Senate Bill 1 (SB1) to bolster transportation infrastructure funding. Using data primarily from the California Department of Transportation (Caltrans)’s official SB1 progress reports, this report analyzes the severity of cost overruns, delays, and cancellations across SB1 Transportation Projects. Although events such as the COVID-19 pandemic likely caused some of these negative outcomes, the statistical models developed for this analysis show consistent patterns of overruns associated with fiscal periods, programs, and geographic locations. Results indicate that the common 20% contingency is generally insufficient, indicating the need for better risk estimation in project planning. Results also suggest amplifying data transparency on project performance and re-evaluating project selection criteria to avoid rewarding underestimation of project costs and duration and penalizing accurate estimation.

other

Press Release: Not Going Out is the “New Normal” Post-Covid, Say Experts

research report

Is Micromobility Being Used in Place of Car Trips in Daily Travel (or “Trip Chains”)?

Abstract

To understand the extent to which micromobility services such as bike-share and scooter-share are enabling car-lightlifestyles by replacing driving, this report explores the trip-chaining patterns of micromobility users. The research team used travel diary data collected from micromobility users in 48 cities across the US. Findings from their analysis shows that a considerable portion of car owners are leaving their cars at home when using micromobility. This suggests that, for a subset of users, micromobility can form part of a car-free or car-light day of travel, despite having a car available. In addition, micromobility services are supportive of complex trip chains that include both work and non-work trips with reduced reliance on cars. The use of micromobility services tends to entirely replace shorter car trips on shorter-length trip chains.

published journal article

Brake and Tire Particles Measured from On-road Vehicles: Effects of Vehicle Mass and Braking Intensity

Abstract

Vehicle exhaust emissions have been decreasing due to stricter regulations and advancements in control strategies. However, non-exhaust emissions from brake and tire wear have not been extensively regulated in the past, and their relative contribution to particulate matter (PM) in urban areas is increasing. This article examines the effect of a vehicle’s mass and braking intensity on brake and tire particles based on on-road data collected from three different types of vehicles under real-world driving conditions.

research report

EEZ Mobility: A Tool For Modeling Equitable Installation of Electric Vehicle Charging Stations

Publication Date

December 1, 2022

Author(s)

Ayse Tug Ozturk, Preston Hong, Marta Gonzalez, Scott Moura, Callie Clark

Abstract

Public electric vehicle (EV) chargers are unevenly distributed in California with respect to income, race and education-levels. This creates inequitable access to electric mobility especially for low-income communities of color, which. are less likely to have access to home charging stations. These communities are also more likely to be located in areas with poor air quality and would therefore benefit from EV adoption. Currently programs exist in California that fund incentives for public EV chargers in “Disadvantaged Communities” but the process for identifying these communities does not consider key characteristics such as housing type, potential for local emission reduction, and the degree of access to private chargers that would maximize economic benefits to these areas and the state. This report and study develops a model-based tool that incorporates key additional information to predict economic benefits and health impacts to local communities to guide the location of public charging infrastructure. This tool will improve the equitable distribution of public funds by identifying three types of expected benefits: economic benefit to EV owners/users, economic benefit to infrastructure operators, and greenhouse gas and PM2.5 emission reductions.