policy brief

How is Climate Change Affecting Landslide Susceptibility in California?

Abstract

Environmental shifts resulting from climate change have led to increased risk of natural hazards such as drought, wildfires, floods, and landslides, which all represent major threats to the state’s infrastructure. One particular risk that is posed by greater precipitation in areas affected by wildfires, which can lead to an increase in landslide hazard. There is little research available for predicting future landslide susceptibility. To address this gap, the research team developed a landslide susceptibility assessment framework which reflects changing climate conditions under different levels of projected greenhouse gas emissions and applied it to assess the vulnerability of California’s transportation infrastructure.

policy brief

Test Publication for Automations

policy brief

Shared Automated Vehicles Could Greatly Benefit Visually Impaired Travelers if Designed and Operated with Their Needs in Mind

Abstract

Automated vehicles (AVs) are one of the most significant technological advances in transportation. The benefits of AV technologies could be maximized by increasing vehicle occupancy through pooling and ridesharing, integrating AV use with high-capacity transit systems (e.g., using AVs to complement existing transit), and promoting multimodality (e.g., connecting travelers to public transit). Additionally, shared automated vehicles (SAVs), in which ridesharing companies (similar as today’s Uber or Lyft) offer driverless on-demand mobility services to customers, could enhance transportation access for visually impaired travelers who face unique challenges navigating current transportation systems including public transit and rideshare services. To this point, the research team interviewed 15 visually impaired individuals to understand their current transportation experience (e.g., what challenges they face and how they cope with these challenges); how SAVs might address their transportation needs and challenges; potential issues and solutions for using SAVs; how their travel behavior may change due to SAVs; and how much they would pay for SAV rides.

policy brief

What Would it Take for Drivers to Adopt Eco-Driving Behaviors?

Abstract

Climate change in California could greatly impact the state’s economy, nature, and public health. One strategy to reduce fuel consumption and greenhouse gas emissions from the transportation sector is eco-driving. Eco-driving is a set of behaviors or driving styles that encourage fuel-efficient driving that could help minimize energy consumption anywhere from five to 30 percent. With the advance of connected-vehicle technologies, the dynamic eco-driving concept uses real-time vehicle-specific information to optimize vehicle speed and reduce fuel consumption and emissions.

This policy brief finds that driver motivations for adopting eco-driving behaviors varies, perceived ease of use was a key factor influencing a
driver’s intention to use an eco-driving system, and (3) based on the result of the driving simulator experiment, drivers may become distracted while trying to follow the information provided by the eco-driving interface.

research report

Headed Out Less: Analyzing Teen and Young Adult Travel Trends in the 21st Century

Publication Date

August 4, 2025

Author(s)

Andy Fung, Fariba Siddiq, Yu Hong Hwang, Brian D. Taylor

Abstract

Since the turn of the millennium, daily travel per person in the U.S. has been declining. Leading up to the pandemic, travel by older teens and young adults declined even more steeply than among older adults. After collapsing early in the pandemic, per capita travel by all ages has rebounded, but remains below pre-pandemic levels. To explore changes in personal travel, particularly among younger travelers, we examine National Household Travel Survey data from 2001, 2009, 2017, and 2022 to compare measures of everyday travel by youth (aged 15 to 29) with middle-aged adults (aged 30 to 59). The data presented in this report point to even lower levels of youth travel compared to pre-pandemic levels. Trips for all purposes have declined in absolute terms, especially for shopping/errands and, for youth in particular, social/recreational purposes. In relative terms, private vehicle use has increased, and travel by public transit and active modes has decreased. These shifts in personal travel – down overall and toward cars – suggest that pandemic-prompted travel shifts toward fewer out-of-home activities and increased use of information and communications technologies for shopping and other trips may be having enduring effects on personal travel, particularly among younger travelers.

research report

Accessibility of Shared Automated Vehicles for Visually Impaired Travelers

Abstract

Researchers at UC Berkeley conducted semi-structured interviews with 15 visually impaired individuals. The researchers explored perspectives regarding current travel behavior and transportation experience, and the potential of Shared Automated Vehicles (SAVs) to enhance their travel experiences and address existing transportation challenges. The results revealed a range of expectations and concerns related to SAVs, particularly in the areas of accessibility, safety, communication, and affordability. Most participants expressed enthusiasm for the potential benefits of SAVs to increase independence and access to underserved areas. The researchers also highlighted critical accessibility needs, such as reliable vehicle identification, accurate drop-off locations, clear communication channels, and accessible interfaces. Affordability emerged as a key factor influencing potential SAV adoption, with many participants indicating a preference for SAVs if they were priced competitively with existing transportation options, especially rideshare services. The findings of this study provide valuable insights for policymakers, transportation planners, and SAV developers to ensure that future autonomous transportation solutions are truly inclusive and meet the diverse needs of visually impaired travelers.

research report

A Review of Data Systems to Track Zero-Emission Truck Adoption and Suggestions for Future Improvements

Abstract

To guide databases that track progress on the uptake and use of zero emission trucks and buses, this project identified types of data that should be collected on a regular basis and compiled in a repository, preferably with public access. Funding will need to be identified to support this effort on an on-going basis. Data recommended for collection include those related to vehicles, infrastructure, projections, funding, the spatial location of charging power demand as a function of time, and exemptions from regulations that require fleets to purchase zero-emissions trucks and buses. These data recommendations were developed in part from conversations with staff at California agencies, such as the California Energy Commission and Air Resources Board, and with individuals working on the Alliance for Renewable Clean Hydrogen Energy Systems (ARCHES) hydrogen hub. The recommendations are evolving and could continue to evolve once data collection has begun.

policy brief

Use of Probe Data Analytical Platforms for Analyzing Truck Movements

Abstract

Determining where trucks are traveling is crucial for planning and maintaining transportation networks. In California, information about truck movements is primarily derived from a network of fixed monitoring stations. However, the data provides limited information about trip origins and destinations and the routes taken in between stations. Estimating truck movements within a region thus largely depends on extrapolating data between known collection points. While this can be done with relative ease in simple networks containing few alternate routes, it can be a difficult task in complex networks without significantly increasing the number of fixed monitoring stations. Real-time truck tracking data (i.e., probe-data) from thirdparty commercial vendors, such as StreetLight and INRIX, can be used to fill this gap. However, their ability to produce reliable traffic volume estimates has not been well studied. The research team used StreetLight data to estimate truck movements within Caltrans District 1 to assess the potential for using probe data to provide a more accurate picture of truck travel not available from roadside monitors alone.

published journal article

Spatial analysis and predictive modeling framework of truck parking and idling impacts on environmental justice communities

Abstract

This study introduces a comprehensive modeling framework to analyze truck idling and parking activities, illustrated through a case study in environmental justice communities in Kern County, California. It includes 1) exploratory spatial and cluster analysis to identify hotspots of those truck activities and their influencing factors, and 2) advanced predictive models, particularly the Cross-Validated Random Forests model, to predict and investigate critical factors influencing truck idling time, parking search time, and inferred truck parking demand. The results reveal that the percentage of heavy-duty trucks and the specific land use influence truck idling time. For parking search time, key predictors include distance to major roads and employment in certain industries. The inferred truck parking demand model underscores the impact of commercial land use areas, proximity to major roads, and socioeconomic factors. These findings enable the identification of hotspots for truck idling and parking searches, facilitating targeted interventions such as optimizing land use planning, improving infrastructure around major roads, and enhancing parking facilities in commercial zones. Integrating spatial, socioeconomic, and GPS aggregate data, the methodology provides a scalable framework applicable to other regions facing similar challenges through data-driven planning and policy initiatives.