research report

Measuring Changes in Air Quality from Reduced Travel in Response to COVID-19

Abstract

The lack of a strong reduction in ambient ozone (O3) concentrations during reduced traffic periods associated with COVID-19 calls into question the conventional wisdom that mobile sources dominate air pollution in California. Fossil-fueled motor vehicles emit oxides of nitrogen (NOx) and volatile organic compounds (VOCs) that are precursors to O3 formation, but the chemical reaction system that forms O3 is complex. The ratio of NOx/VOCs determines if the O3 formation regime is NOx-limited (reducing NOx reduces O3) or NOx-rich (reducing NOx increases O3). This project developed new methods to directly measure O3 chemistry in the atmosphere and applied them over long-term campaigns in multiple California cities to quantify traffic contributions to O3 formation. A seasonal cycle was observed of NOx-rich O3 chemistry during cooler months trending toward NOx-limited chemistry in warmer months. Superimposed on this seasonal cycle was a spatial pattern of NOx-rich chemistry in dense urban cores and NOx-limited chemistry in areas downwind of urban cores. Chemistry-based models with source tagging were also developed to better understand these trends. Seasonal changes to biogenic VOC and gasoline evaporative VOC emissions likely explain the seasonal changes in O3 formation chemistry. Reduced traffic emissions in March 2020 did not reduce O3 concentrations because the chemistry was heavily NOx-rich during the spring season. Extended model predictions suggest that similar traffic reductions could have reduced ambient O3 concentrations in small and intermediate cities if they had occurred in the summer months. Traffic reductions alone would not be sufficient to reduce O3 concentrations in the urban cores of larger cities. Reduced emissions from transportation sources can improve air quality in California, but transportation sources no longer exclusively dominate O3 formation. Future emissions controls should be coordinated across multiple sectors (including transportation) to achieve their objectives.

policy brief

Are our Transit Systems Ready for Earthquakes?

Abstract

Located on the tectonic boundary with multiple active faults, the San Francisco Bay Area is highly vulnerable to earthquakes. The United States Geological Survey (USGS) has estimated a 72% probability of an earthquakewith a magnitude of 6.7 or greater striking the region within the next 30 years. Historical seismic events have demonstrated the profound impact earthquakes can have on transportation systems. During the 1989 Loma Prieta Earthquake, the closure of the San Francisco-Oakland Bay Bridge, a critical transit route for San Francisco commuters, left nearly 400,000 commutersand approximately 245,000 vehicles daily with limitedalternative routes.

dataset

California Electric Vehicle Loads by Feeder Circuit

Publication Date

October 30, 2023

Abstract

Please reach out to the project Principal Investigator for more information on this dataset.

presentation

When Will California’s Electric Distribution System Need to be Upgraded to Meet Electric Vehicle Charging Demand?

Publication Date

July 7, 2023

policy brief

How Risky Are Cyber Security Threats Against Autonomous Vehicles?

Abstract

To operate safely, autonomous vehicles (AVs) rely on external sensors such as cameras, light detection and ranging (LiDAR) technology, and radar. These sensors pair with machine learning-based perception modules that interpret the surrounding environment and enable the AV to act accordingly. Perception modules are the “eyes and ears” of the vehicle and are vulnerable to cybersecurity attacks. The most critical and practical threats, however, arise from physical attacks that do not require access to the AV’s internal systems. The risks of these types of attacks are still unknown. To advance the field in this area, we conducted the first ever quantitative risk assessment for physical adversarial attacks on AVs. First, we identified relevant attack vectors, or types of cyber security attacks, targeting AV perception modules. Next, we conducted an in-depth analysis of the stages of an attack. Finally, we used these exercises to identify risk metrics and perform a subsequent computation of risk scores for different attack vectors. Through this process, we were able to quantitatively rank the real-life risks posed by different attack vectors identified in existing research. This analysis provides a framework for comprehensive risk analysis to ensure the safety of AVs on our roadways.

research report

Risk Assessment for Security Threats and Vulnerabilities of Autonomous Vehicles

Abstract

Autonomous vehicles (AVs) heavily rely on machine learning-based perception models to accurately interpret their surroundings. However, these crucial perception components are vulnerable to a range of malicious attacks. Even though individual attacks can be highly successful, the actual security risks such attacks can pose to daily life are unclear. Various factors, such as lack of stealthiness, cost-effectiveness, and ease of deployment, can deter potential attackers from employing certain attacks, thereby reducing the actual risk. This research report presents the first quantitative risk assessment for physical adversarial attacks on AVs. The specific focus is on attacks on an AV’s perception components due to their highly critical function and representation in existing research. The report defines the daily-life risk as the likelihood that a given type of attack will be employed in real life and the authors develop a problem-specific risk scoring system and accompanying metrics. The report provides an initial evaluation of the proposed risk assessment method for all the reported attacks on AVs from 2017 to 2023, and quantitatively ranks the daily-life risks posed by each of eight different categories of attacks and find three attacks with the highest risks: 2D printed images, 2D patches, and coated camouflage stickers, which deserve more focused attention for potential future mitigation strategy development and policy making.

blog

What Happened to Stockton's First Asian Enclaves?: How the City’s Chinatown, Japantown, and Little Manila Were Razed in the Name of "Progress"

policy brief

Pathways to Autonomy: Supporting Youth Independent Mobility in Westlake, Los Angeles

Abstract

Each day, youth in Los Angeles venture out on their own to move to and from home, school, and after-school activities. Their travels represent important pathways to autonomy, agency, and urban citizenship, which a city can support with safe, pleasant paths that offer reassuring familiarity and opportunities for socializing.

research report

Pathways to Autonomy: Supporting Youth Independent Mobility in Westlake, Los Angeles

Abstract

In this study, the research paper uses the concept of “sidewalk ecologies” to highlight the complex interaction between spatially situated social and material features of sidewalks that influence youth mobility. The research team uses a range of interdisciplinary strategies, emphasizing youth-centered research methods and mapping to capture a rich portrait of the independent travel experiences, perceptions, and ideas of youth, in their own voices. This research was conducted in partnership with Heart of Los Angeles (HOLA), a community-based organization in Westlake that provides after-school programming to thousands of neighborhood youths, and yielded important findings.

research report

Fuel Portfolio Scenario Modeling (FPSM) of 2030 and 2035 Low Carbon Fuel Standard Targets in California

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 greenhouse gas 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. The research team 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.