Institute of Transportation Studies at UC Berkeley

In the event of a wildfire, government agencies need to make quick, well-informed decisions to safely evacuate people. Small communities, such as in Marin County, with a mix of residences and flammable vegetation in Wildland-Urban Interface zones tend to lack resources to conduct evacuation studies. Consequently, this study uses a framework of wildfire and traffic simulations to test the performance of potential evacuation strategies, including reducing the volume of evacuating vehicles through car-pooling, phasing evacuations by staggering evacuation times by zone, and prohibiting street parking in four representative areas of Marin County. Results show that reducing vehicle numbers lowers the average travel time by 20%-70% and average exposure time to wildfire by 27%-60% from the baseline. Phased evacuations with suitable time intervals lower the average travel time by 13.5%-70%, but may expose more vehicles to fire in some situations. Prohibiting street parking yields varying results due to different numbers of exits and evacuees. In some cases, prohibiting street parking reduces the average travel time by over 50%, while in other cases it only reduces the average travel time by 9%, contributing little to evacuation efficiency. Altogether, Marin County may want to consider developing a communication and parking plan to reduce the number of evacuating vehicles in wildfire situations. Phased evacuation is also highly recommended, but the suitable phasing interval depends on the speed of fire spread and number of evacuees. Further, whether to establish street parking prohibition policies for a certain area depends on the number of exits and the number of vehicles on the streets.

This report explores opportunities for employing autonomous driving technology to dampen stop-and-go waves on freeways. If successful, it could reduce fuel consumption and emissions. This technology was tested in an on-road experiment with 100 vehicles over one week. Public stakeholders were engaged to assess the planning effort and feasibility of taking the technology to the next level: a pilot involving 1000+ vehicles over several months. Considerations included the possible geographical boundaries, target fleets of vehicles, and suitable facilities such as bridges or managed lanes. Flow smoothing technology may improve the user experience and operations of managed lanes or bridges, however it may require external incentives such as reduced tolls to entice the traveling public to use it. This must be matched with other goals such as verifying vehicle occupancy. It might be possible for some hybrid solution that addresses both challenges to provide a way forward. A concept of operations needs to be developed specifically for a target road geometry and a California partner. This concept should benefit from lessons learned from previous pilot projects and will need to be defined so as to achieve both (1) a penetration rate sufficient to achieve measurable effects; and (2) sufficient quality and quantity of data to confirm benefits.

We explore how rail transit’s first- and last-mile issue might be addressed by partnering with transportation network companies (TNCs) like Uber and Lyft. The goal is to lure high-income commuters to shift from cars to TNCs and rail. We also explore how rail and TNC partnerships can improve travel for low-income commuters who currently rely on low-frequency bus service. We parametrically test subsidizing TNC fares for feeder services in the San Francisco Bay Area in

an idealized fashion. Inputs such as the residents’ value of time and vehicle ownership were taken from various local data sources. The communities that were selected for our study are served to different degrees by the BART rail system. We found that the optimal policy must be tailored to the characteristics of the community it serves. In dense, walkable communities with strong bus service near rail stations, TNC subsidies should be targeted to less-accessible neighborhoods and low-income commuters to not compete with bus transit and active modes like walking. For lower-density communities with limited dedicated bus feeder service, TNC subsidization can be applied more broadly, although disincentives, like increasing rail parking fees, must be considered carefully, because they can induce commuters to drive directly to work instead. We conclude with a discussion of how subsidies might be covered by reallocating existing resources in different ways.

Advanced air mobility (AAM) is a broad concept that enables consumers access to air mobility, goods delivery, and emergency services through an integrated and connected multimodal transportation network. AAM can provide short-range urban, suburban, and rural flights of about 50-miles and mid-range regional flights up to a several hundred miles. State law delegates responsibility for oversight in aviation primarily to the California Department of Transportation (Caltrans). This white paper presents an overview of the state of the market, such as the aircraft under development and forecast market growth and discusses factors that could facilitate the development of AAM or pose risks to its deployment or to the public, including the safety and the regulatory environment, airspace and air traffic management, security, environmental impacts, weather, infrastructure and multimodal integration, workforce and economic development, social equity, and community engagement and social acceptance. It concludes by recommending actions that Caltrans and other state agencies can take to facilitate the development of AAM.

California's goal to eliminate internal combustion engine sales by 2035 poses challenges for lower- and moderate-income residents, hindering their access to electric vehicles (EVs). Barriers include limited EV charging stations, exacerbated by lower home ownership and inadequate grid infrastructure in lower-income communities. To address this, UC Berkeley School of Law's Center for Law, Energy & the Environment (CLEE) partnered with the City of Watsonville. Due to its location, demographics, and ambitious policy goals, Watsonville represents a potential model and case study for other cities around the state grappling with how to boost EV charging infrastructure. CLEE conducted stakeholder interviews and a convening in Watsonville in May2023, and developed a set of policy recommendations for both state and local entities to accelerate investment in EV charging infrastructure in Watsonville, which could inform other cities facing similar challenges and seeking to meet state targets and residents’ needs.

This report presents analytical review of empirical research on the interactions between housing availability and production, and travel behavior, accessibility, land use policies, and transportation policies. It identifies lessons from this review for California state legislative efforts to improve housing and transportation linkages, and to increase both transportation sustainability and housing affordability. Relevant California state efforts include legislation to influence parking standards; to require up-zoning near transit stations; to influence regional housing and transportation planning goals; and to change environmental review to focus on reducing vehicle miles traveled instead of accommodating road traffic.

California must operate and maintain an effective and efficient transportation infrastructure while ensuring that the health of communities and the planet are not compromised. By assessing transportation projects using a life-cycle perspective, all relevant emission sources and activities from the construction, operation, maintenance, and end-of-life phases can be analyzed and mitigated. This report presents a framework to assess the life-cycle human health and climate change impacts from six types of transportation projects: (1) Roadways; (2) Marine ports; (3) Logistical distribution centers; (4) Railyards; (5) Bridges and overpasses; and (6) Airports. The framework was applied using an integrated model to assess fine particulate matter (PM2.5) and greenhouse gas (GHG) emissions, noise impacts, and monetized damages (Value of Statistical Life, Social Cost of Carbon) from two case studies: routine resurfacing and vehicle operations on road segments within the San Francisco Bay Area using 2019 data, and annual marine, cargo, rail, trucking, and infrastructure maintenance operations at the Port of Oakland in 2020. The results suggest that emission sources in a project’s supply chain and construction (material production and deliveries, construction activities, fuel refining) can significantly contribute to the full scope of impacts from transportation systems. Equitable mitigation policies (e.g., electrification, pollution control technologies) need to be tailored to address the sources that impact communities the most.

This report describes how current methods of estimating truck traffic volumes from existing fixed roadway sensors could be improved by using tracking data collected from commercial truck fleets and other connected technology sources (e.g., onboard GPS-enabled navigation systems and smartphones supplied by third-party vendors). Using Caltrans District 1 in Northern California as an example, the study first reviews existing fixed-location data collection capabilities and highlights gaps in the ability to monitor truck movements. It then reviews emerging data sources and analyzes the analytical capabilities of StreetLight 2021, a commercial software package. The study then looks at the Sample Trip Count and uncalibrated Index values obtained from three weigh-in-motion (WIM) and twelve Traffic Census stations operated by Caltrans in District 1. The study suggests improvements to StreetLight’s “single-factor” calibration process which limits its ability to convert raw truck count data into accurate traffic volume estimates across an area, and suggests how improved truck-related calibration data can be extracted from the truck classification counts obtained from Caltrans’ WIM and Traffic Census stations. The report compares uncalibrated StreetLight Index values to observed truck counts to assess data quality and evaluates the impacts of considering alternate calibration data sets and analysis periods. Two test cases are presented to highlight issues with the single-factor calibration process. The report concludes that probe data analytical platforms such as StreetLight can be used to obtain rough estimates of truck volumes on roadway segments or to analyze routing patterns. The results further indicate that the accuracy of volume estimates depends heavily on the availability of sufficiently large samples of tracking data and stable and representative month-by-month calibration data across multiple reference locations.

This report highlights risk and prioritization factors for housing developments with expiring affordability protections, focused on preserving transit-accessible affordable housing. It presents a regional framework for identifying and preserving subsidized affordable housing in the Southern California Association of Governments (SCAG) region (Los Angeles, Imperial, Orange, Riverside, San Bernardino, and Ventura counties). First, we analyze data from the California Housing Partnership (CHPC) and the National Housing Preservation Database (NHPD) to understand risk factors for expiring housing units, and design a prioritization tool for entities in the region to use when prioritizing developments to focus preservation and anti-displacement efforts. Second, we highlight affordable housing preservation policy solutions and characteristics unique to the Southern California context. Third, we draw on the strategies and experiences of other jurisdictions in the United States with experience strategizing around affordable housing preservation efforts to present key lessons and takeaways.

Dynamic toll pricing based on demand can increase transportation revenue while also incentivizing travelers to avoid peak traffic periods. However, given the unpredictable nature of traffic, travelers lack the information necessary to accurately predict congestion, so dynamic pricing has minimal effect on demand. Dynamic toll pricing also poses equity concerns for those who lack other travel options. This research explores a potential remedy to these concerns by using a simple “futures market” pricing mechanism in which travelers can lock in a toll price for expected trips by prepaying for future tolls, with the future price increasing as more travelers book an overlapping time slot. This approach encourages travelers to avoid driving during the peak periods when pricing increases toward capacity or to purchase trips in advance when the price remains low or discounted, thus using infrastructure capacity more efficiently. Travelers that do not prepurchase their trip are subject to the real-time market price, which is determined by dynamic congestion pricing. This futures-market mechanism can augment existing toll collection technologies and provide travelers with sufficient pricing information and purchasing options to preplan their travel and avoid excessive prices.