Institute of Transportation Studies at UC Berkeley

Economists have long argued in favor of congestion pricing, under which drivers pay a fee or toll to enter roadways during peak times. An increasing number of global cities have adopted or are considering pricing programs. Even so, these regimes remain relatively rare and controversial. One key concern with congestion pricing is fairness. Road pricing can pose a substantial burden for low-income drivers, many of whom have little option to avoid travel during peak times and limited opportunity to choose other modes of travel. Prior research has shown that congestion pricing regimes tend to be regressive in terms of their initial burden, that is, in terms of who ends up paying more to use the roads.1 But, the ultimate effect of a road pricing program depends also on how its revenue is used. Some or all of the revenue from a congestion pricing program can be returned to households, and this can fundamentally change the program’s fairness.

Curb space has been traditionally designed for private vehicle parking, public transit, and passenger and commercial loading. However, in recent years, a growing number of newservices and activities have increased the demand for limited curb space, including passenger pick-up and drop-off; last-mile delivery (e.g., courier network services, personal delivery devices); electric vehicle (EV) charging; micromobility parking and use (e.g., personally owned and shared bikes and scooters); and carsharing services. The curb serves a variety of functions such as vehicle and device storage (including personally owned and shared vehicles and devices), outdoor dining and retail, greenspace, and other uses. These changes are contributing to a notable shift in how people access and use the curb, and how public agencies plan, prioritize, and manage curbside interactions.

Transportation Network Companies (TNCs, also known as ridehailing and ridesourcing) have expanded across California over the past decade and changed the way people travel. Using a smartphone, travelers can quickly summon a vehicle from almost anywhere and know what the estimated wait time, travel time, and cost will be before stepping into the vehicle. While TNCs are clearly addressing an unmet need for travelers, their growing popularity has raised a number of policy questions, including if TNCs are shifting people away from public transit and other travel modes (e.g., carshare, walking, biking).

As interest in hydrogen as an energy carrier has increased, the various ways that hydrogen is made are being categorized as “green,” “blue,” “gray,” and other colors in relation to their environmental impact. While these categorizations are somewhat useful to indicate the environmental and climate change impacts of different production pathways, they are not especially useful for policy making or industry decisionmaking purposes because they are subjective. For example, most definitions of green pathways for hydrogen production only include electrolysis from renewable electricity sources; however, Figure 1 indicates additional production pathways with some of these having near-zero or even negative greenhouse gas (GHG) emissions as well as low or no other emissions of concern. To help clarify the role of hydrogen in decarbonizing California, this brief summarizes the latest scientific findings from recent and in-progress research across the University of California Institute of Transportation Studies (UC ITS) concerning the relative carbon intensity (CI) of hydrogen production pathways. It also briefly covers the availability of biomass and biogas in California that could be applied to the production of low-CI hydrogen.

In response to California law (SB 743, Chapter No. 386, Statutes of 2013), school districts are encouraged to use vehicle miles traveled (VMT) as criteria when evaluating the transportation impacts of new school construction, and identify feasible mitigation measures that eliminate or substantially reduce VMT generated by the new construction. To better understand the implications of this new law on school siting decisions, researchers at UC Berkeley analyzed 301 new schools constructed between 2008 and 2018 with respect to four VMT mitigation measures identified by the Governor’s Office of Planning and Research (OPR) known to minimize VMT – proximity to high quality transit areas (HQTA), proximity to roads with bicycle facilities, proximity to electric vehicle (EV) charging stations, and walkability scores.

Airports are complex social, technical, and environmental systems. Understanding their complexity is fundamental for advancing transformative climate adaptation policy. For airports to adapt, climate science must be incorporated not only into standards of specific equipment and facilities, but also into the air traffic network and its interconnected infrastructure systems (e.g., road access, ground-based communications, navigation, and surveillance systems). In addition, airport adaptation requires a shift in the way policy is designed, reinforced, and updated, which in turn relies on an understanding of airport governance models and organizational networks. UC Berkeley researchers recently explored how airport planners and policymakers can use climate science to transform standards and update organizational values to promote climate adaptation. After assessing California airports’ exposure to future coastal flooding and reviewing more than 300 policy documents, the UC Berkeley research team developed guidelines on how international, federal, and state policies can better incorporate forward-looking climate science into airport standards and policies.

During the COVID-19 pandemic, public transportation systems worldwide faced many challenges, including significant loss of ridership. Public agencies implemented various COVID-19-related policies to reduce transmission, such as reducing service frequency and network coverage of public transportation. Recent studies have examined the effectiveness of these policies but reach different conclusions due to varying assumptions about how passengers may react to service changes.

In an ideal world, all cars along a congested roadway would travel at the same constant average speed; however, this is hardly the case. As soon as one driver brakes, trailing cars must also brake to compensate, leading to “stop and go” traffic waves. This unnecessary braking and accelerating increases fuel consumption (and greenhouse gas emissions) by as much as 67 percent.1 Fortunately, automated vehicles (AVs) — even Level 2 AVs2 which are commercially available today — have the potential to mitigate this problem. By accelerating less than a human would, an AV with flow smoothing technology is able to smooth out a traffic wave, eventually leading to free-flowing traffic (See Figure 1). To demonstrate the potential of flow smoothing on reducing greenhouse gas emissions, researchers at UC Berkeley used a calibrated model of the I-210 freeway in Los Angeles to simulate and measure the effect of deploying different percentages (10%, 20%, 30%) of flow-smoothing AVs on the average miles per gallon (MPG) of non-AVs in the traffic system.

In recent years, “smart city” information and communication technologies have proliferated. For local government agencies, procuring and introducing these technologies offers the possibility to manage infrastructure assets more effectively, plan for preventive maintenance, and disseminate schedules and information about transit and other services. Many of these technologies are deployed by private firms in the context of local regulations and government-sponsored incentives. In the transportation sector, examples of “smart city” technology services provided by private firms include: electric vehicle (EV) chargers, micro-mobility (e.g., scooter and bike rentals), and transportation network company (TNC) services, such as Uber and Lyft. To understand variation in how private sector smart city transportation technologies are deployed across California, researchers at UC Berkeley webscraped and cross verified data on EV chargers, Uber services, and micro-mobility. EV charger data was obtained from the Department of Energy, and Uber and micromobility access data came from vendor websites.

Fully autonomous vehicles are expected to have a profound effect on travel behavior. The technology will provide convenience and better mobility for many, allowing owners to perform other tasks while traveling, summon their vehicles from a distance, and send vehicles off to complete tasks without them. These travel behaviors could lead to increases in vehicle miles traveled that will have major implications for traffic congestion and pollution. To estimate the extent to which travel behavior will change, researchers and planners have typically relied on adjustments to existing travel simulations or on surveys asking people how they would change their behavior in a hypothetical autonomous vehicle future. Researchers at UC Berkeley and UC Davis used a new approach to understand the potential influence of autonomous vehicles on travel behavior by conducting the first naturalistic experiment mimicking the effect of autonomous vehicle ownership. Private chauffeurs were provided to 43 households in the Sacramento, California region for one or two weeks. By taking over driving duties for the household, the private chauffeurs served the household as an autonomous vehicle would. Researchers tracked household travel prior to, during, and after the week(s) with access to the chauffeur service.