policy brief

Shifting Future Electric Vehicle Trips to e-Bikes Could Help Reduce Electricity Demand at Critical Times in California

Abstract

California aims to replace gasoline and diesel light-duty vehicles (LDVs) with zero-emission LDVs, many of which will be plug-in battery electric vehicles (BEVs) and achieve 100% zero-carbon electricity by 2045. Large-scale plug-in BEV deployment will substantially increase electricity demand, particularly during peak hours (4:00pm to 9:00pm) when renewable energy is in short supply. Popular strategies for charging BEVs with electricity produced from renewable energy include smart charging and creating more energy storage that soaks up renewable energy during the day and dispenses it later when needed. These strategies, however, may not be enough. Consumer acceptance limits smart charging, and increased energy storage capacity is expensive. Another potential strategy involves lowering the overall demand for electricity by shifting BEV trips to electric-powered bicycles (e-bikes). While e-bikes cannot entirely replace BEV trips, they are ideal for short trips (five miles or less). Currently, 64% of US vehicle trips fall into the short trip category. Using synthetic travel pattern data from the San Diego region, we quantified the electric grid cost savings of shifting future BEV trips to e-bikes. For our analysis, we determined the passenger LDV trips that e-bikes could potentially replace. To provide an upper bound on replaceable trips, we considered trips that met the following criteria: LDV trips within home-based tours (a sequence of trips starting and ending at the home location) made by no more than two household members (between 16 and 70 years old), with less than five stops, under four hours in travel duration, and with individual trip distances up to seven miles long. We also created three scenarios that differ in terms of the tour purposes:
• Scenario 1: All purposes (e.g., work, recreation, eating out, etc.) except escort (i.e., transporting someone else to their activity) and shopping tours
• Scenario 2: All purposes except escort tours
• Scenario 3: All purposes

published journal article

Large-scale Public Charging Demand Prediction with a Scenario- and Activity-based Approach

Abstract

Transportation system electrification is expected to bring millions of electric vehicles (EVs) on road within decades. Accurately predicting the charging demand is necessary to accommodate the surge in EV deployment. This paper presents a novel modeling framework to predict the public charging demand profile derived from people’s travel trajectories, with the consideration of the demand and supply stochasticity of transportation systems and the charging behavior heterogeneity of EV users. The vehicle charging decision-making process is explicitly modeled, and the charging need of each EV user is estimated associated with their travel trajectories. The methodology enables charging demand prediction with a high spatial–temporal resolution for transportation system electrification planning. A case study was conducted in Los Angeles County to predict the demand for public charging facilities in 2035 and perform corresponding spatial–temporal analysis of EV public charging under various scenarios of future electrification levels and network conditions.

research report

Evaluating the Safety Effects of Adopting a Stop-as-Yield Law for Cyclists in California

Abstract

This report investigates how stop-as-yield laws can positively or negatively affect safety and provides insights and guidelines for California policymakers and safety practitioners if such a law passes in California. The research team collected cyclist data from five states that enacted stop-as-yield laws—Idaho, Arkansas, Oregon, Washington and Delaware—and data from some of their contiguous states without such legislation. Using an observational before-after study with comparison groups at the state level, the research examined changes in cyclist crash frequencies after the laws were implemented. Additionally, a random-effects negative binomial regression model with panel data was employed to estimate a law’s overall impact. The results did not indicate a significant change in cyclist crashes among the states with stop-as-yield laws.

research report

Barriers to Reducing the Carbon Footprint of Transportation Part 2: Investigating Evolving Travel Behaviors in the Post-Pandemic Period in California

Publication Date

May 1, 2024

Author(s)

Basar Ozbilen, Siddhartha Gulhare, Keita Makino, Aurojeet Jena, Xiatian Iogansen, Patrick Loa, Yongsung Lee, Giovanni Circella

Abstract

During the early months of the pandemic, stay-at-home orders and concerns about infection catalyzed a shift toward online activities, such as remote work and e-shopping, resulting in a significant decrease in conventional travel. However, as the effects of the pandemic diminished, the pandemic-induced online activities began to subside, and conventional travel started to rebound. To understand evolving travel-related activities spurred by the COVID-19 pandemic, researchers at ITS-Davis conducted four waves of mobility surveys in California between Spring 2020 and Fall 2023. Key findings from the analysis of these data reveal that remote work and a combination of remote work and physical commuting (i.e., hybrid work) emerge as an enduring outcome of the pandemic. The pandemic accelerated the rise of e-shopping, both for grocery and non-grocery purchases, with findings demonstrating the critical influence of socio-demographic factors, including age, gender, and income, on e-shopping adoption and frequency. The findings show that socio-demographic factors such as work status, income level, and work arrangements are associated with household vehicle ownership changes and individual vehicle miles traveled (VMT). In particular, an increase in commute frequency reduces the likelihood of vehicle shedding (i.e., getting rid of a vehicle), while amplifying the likelihood of vehicle acquisition. In the meantime, remote workers exhibit lower commuting VMT but higher non-commuting VMT compared to hybrid workers. The findings demonstrate a similarity between the percentage of respondents who used public transit, bikes, e-bikes, and e-scooters for commuting and non-commuting trips to some degree between 2019 and 2023.

published journal article

Driving A-loan: Automobile Debt, Neighborhood Race, and the COVID-19 Pandemic

Abstract

COVID-19 altered travel patterns in the U.S. Studies have analyzed the effect of the pandemic on travel mode, including working from home, but few have focused on automobile ownership—a relationship with potentially long-term consequences for accessibility, household budgets, and debt, and policy efforts to meet climate goals.

To understand the association between the pandemic and automobile ownership, we rely on a unique credit panel dataset from Experian and examine three different automobile loan-related outcome measures: annualized growth rate of new automobile loan balances, average new loan size, and the number of new loans. We focus specifically on changes across loans in neighborhoods by race/ethnicity, hypothesizing larger increases in automobile debt in Black and Latino/neighborhoods, where workers are less likely to be able to telework. The annualized growth rate of new automobile loans increased during the pandemic across all neighborhoods by race/ethnicity, increasing most rapidly in Latino/a neighborhoods. Controlling for other factors, loan size increased similarly across neighborhoods by race/ethnicity. The increase in automobile lending in Latino/a neighborhoods, therefore, likely was explained by a significant uptick in the number of new loans.

The growth in automobile lending during the pandemic was potentially prompted by pandemic-induced changes in the need for automobiles and facilitated by an expanded social safety net. As the pandemic and its various forms of public financial assistance recede, the findings underscore the importance of ongoing assistance in enabling automobile ownership or shared access among households with limited means whose livelihoods depend on the access that vehicles provide.

presentation

Understanding the “New Normal:” Activity and Mobility Patterns of Low-Income and Disadvantaged Communities in the Era of Hybrid Work and High Gas Prices

research report

Updated Fuel Portfolio Scenario Modeling to Inform 2024 Low Carbon Fuel Standard Rulemaking

Publication Date

November 1, 2023

Author(s)

Colin Murphy, Jin Wook Ro, Qian Wang

Abstract

The Low Carbon Fuel Standard (LCFS) plays a critical role in California’s efforts to reduce greenhouse gas (GHG) and air pollutant emissions from transportation. The LCFS incentivizes the use of fuels with lower life cycle GHG emissions by using a credit market mechanism to provide incentives for low-carbon fuels, using revenue generated by charges applied to high-carbon ones. Maintaining an approximate balance between LCFS credit and deficit supplies helps support a stable LCFS credit price and the broader transition to low-carbon transportation. The Fuel Portfolio Scenario Model, presented here, evaluates bottom-up fuel supply and LCFS compliance to inform LCFS policy decisions. We considered two key fuel demand scenarios: (1) the Low Carbon Transportation scenario, reflecting the expected transition to low-carbon transportation in California over the next 15 years, and (2) the Driving to Zero scenario, featuring a significantly higher consumption of petroleum gasoline. In both scenarios, 2030 LCFS targets around 30% resulting in a near-balance between credits and deficits, with some banked credits remaining. Several additional scenarios were modeled to explore the impact of target trajectory timing, alternate post-2030 targets, greater biofuel use, and other parameters. This fuel portfolio scenario modeling work can meaningfully inform policy development.

presentation

Fuel Portfolio Scenario Modeling of 2030 LCFS Targets

presentation

Fuel Portfolio Scenario Modeling of 2030 Low Carbon Fuel Standard Targets in California