University of California Institute of Transportation Studies

The Federal Highway Administration (FHWA) vehicle classification scheme is designed to serve various transportation operational and planning needs. Many transportation agencies rely on Weigh-In-Motion and automatic vehicle classification sites to collect vehicle classification count data. However, these systems are not widely deployed due to high installation and operations costs. One cost-effective approach investigated by researchers has been the use of single inductive loop sensors as an alternative to obtain FHWA vehicle classification data. However, most models do not accurately classify under-represented classes, even though many of these minority classes pose disproportionally adverse impacts on pavement infrastructure and the environment. As a consequence, previous models have not been able to adequately classify under-represented classes, and the overall performance of the models are often masked by excellent classification accuracy of the majority classes, such as passenger vehicles and five-axle tractor trailers. This project developed a bootstrap aggregating (bagging) deep neural network (DNN) model on a truck-focused dataset obtained from Truck Activity Monitoring System (TAMS) sites, which leverage existing inductive loop sensor infrastructure coupled with deployed inductive loop signature technology, and already deployed statewide at over ninety locations across all Caltrans Districts. The proposed method significantly improved the model performance on truck-related classes, especially minority classes such as Classes 7 and 11 which were overlooked in previous research studies. Remarkably, the proposed model is also capable of distinguishing classes with overlapping axle configuration, which is generally a challenge for axle-based sensor systems. 

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.

Connected Vehicles (CV) technology offers significant potential for managing traffic congestion and improving mobility along transportation corridors. This report presents a novel approach using integrated corridor management (ICM) technology to divert CVs to underutilized park-and-ride facilities where drivers can park their vehicle and access public transportation. Using vehicle-to-infrastructure (V2I) communication protocols, the system collects data on downstream traffic and sends messages regarding available park-and-ride options to upstream traffic. A deep reinforcement learning (DRL) program controls the messaging, with the objective of maximizing traffic throughput and minimizing CO2 emissions and travel time. The ICM strategy is simulated on a realistic model of Interstate 5 using Veins simulation software. The results show marginal improvement in throughput, freeway travel time, and CO2 emissions, but increased travel delay for drivers choosing to divert to a park-and-ride facility to take public transportation for a portion of their travel.

This study used a simulation to examine nonpharmaceutical interventions (NPIs) that could have been implemented early in a COVID-19 surge to avoid a large wave of infections, deaths, and an overwhelmed hospital system. The authors integrated a dynamic agent-based travel model with an infection dynamic model. Both models were developed with and calibrated to local data from Los Angeles County (LAC), resulting in a synthetic population of 10 million agents with detailed socio-economic and activity-based characteristics representative of the County’s population. The study focused on the time of the second wave of COVID-19 in LAC (November 1, 2020, to February 10, 2021), before vaccines were introduced. The model accounted for mandated and self-imposed interventions at the time, by incorporating mobile device data providing observed reductions in activity patterns from pre-pandemic norm, and it represented multiple employment categories with literature-informed contact distributions. The combination of NPIs—such as masks, antigen testing, and reduced contact intensity—were the most effective, among the least restrictive, means to reduce infections. The findings may be relevant to public health policy interventions in the community and at the workplace. The study demonstrates that investments in activity-based travel models, including detailedindividual-level socio-demographic characteristics and activity behaviors, can facilitate the evaluation of NPIs to reduce infectious disease epidemics, including COVID-19. The framework developed is generalizable across SARS-COV-2 variants, or even other viral infections, with minimal modifications to the modeling infrastructure.

This paper reviews literature on technological, market, and policy factors affecting the growth of alternative aviation fuels. At present, they represent a minimal fraction of global aviation fuel used but are a critical tool for lowering GHG emissions from aviation. Even with electric and hydrogen power, substantial volumes of low-carbon liquid fuels are likely needed; these will draw heavily on biomass. Beyond hydroprocessed esters and fatty acid (HEFA) fuels, technologies, including lower carbon e-fuels, remain pre-commercial. More jurisdictions are providing incentives for alternative aviation fuel, and some on-road biofuels may be redirected towards aviation in a favorable market, because production processes for these fuels overlap. Biomass feedstocks at different demand levels need to be sourced and evaluated for unintended impacts. Research suggests alternative aviation fuels improve air quality impacts compared to conventional jet fuel. Key uncertainties in scaling alternative jet fuel remain, including ongoing concerns about land use change from biofuels, how to right-size incentives with no technology clearly dominant, what the long-term carbon budget is for aviation, and how to build fuel delivery infrastructure.

This project estimates the safety and mobility impact of changing speed limits on California highways. The safety impact is estimated using statistical models to predict the change in the frequency of all crashes and fatal-or-severe crashes that would result by varying the design speed (85th percentile speed). Statewide crash and traffic data (from the Statewide Integrated Traffic Records System, the Highway Safety Information System, and the Performance Measurement System) were combined to develop a balanced and sampled dataset for the statistical models. Three different increases in differential speed limits (DSLs; whereby trucks and cars have different speed limits) lead to increases in the frequency of all crashes, including fatal and severe crashes, for all of the classified segments (urban, rural, and different design speed segments). The operational condition (speed, travel time, delay) is tested using seven simulation segments with urban-rural classification. Four different DSL scenarios and four uniform speed limit (USL) scenarios are tested for each of the simulation segments. The results show a decrease of travel time but an increase of fuel consumption as the speed limits get higher. The safety cost of crashes and operational costs were also estimated based on the simulation models. In general, as the speed limits are increased, the safety costs increase with the predicted increases in crashes, particularly severe and fatal crashes. The operational costs, on the other hand, generally decrease as the speed limits are increased. However, the amount of operational cost decreases are subject to greater uncertainty than the safety cost estimates are, due to uncertainties in sampling and demand estimation and in negligence of construction costs of roadway and signage changes to accommodate the new speed limits. From the economic perspective in this study, raising speed limits on rural California highways could reduce monetary costs, as savings in operational costs would exceed losses from more crashes.

Bicycles and other forms of micromobility have been anecdotally used in past disasters to help save lives and improve community recovery. However, research and practice are scarce on this resilient transportation strategy, which limits its usefulness and possible benefits. To fill this gap, our paper investigates the potential role bicycles and micromobility in facilitating (or limiting) disaster response and recovery. Given the lack of exploration on the topic, we convened an online workshop where we conducted brainstorming and focus group discussions with disaster experts from various government agencies, not-for-profit organizations, academia, and policy groups. We present a synthesis of that discussion, along with a review of the existing literature. We conclude there is strong potential for bicycles and micromobility for different disaster phases, hazard types, and groups of people. However, multiple barriers exist related to implementation and safety, suggesting a need for future research and policy in the transportation and emergency management fields and practices.

California and its regional and local governments have invested heavily in public transit over the past half-century to provide an alternative to driving, ease traffic congestion, reduce emissions, slow climate change, steer new development, and provide mobility for those without. As a result, bus service has improved and expanded, and many parts of the state’s metropolitan areas are now served by rail transit.

Yet today, many of the state’s transit systems are struggling operationally and financially. Ridership began eroding in the half-decade leading up to 2020 and plummeted at the start of the COVID-19 pandemic. Three federal pandemic relief bills provided a critical lifeline to keep struggling transit systems afloat early on, but these funds are running out. Meanwhile, operating costs have risen, ridership and fare revenues have only partially returned, and some transit systems face “fiscal cliffs,” where they will need substantial new infusions of funding, substantial cuts in costs and service, or some combination of the two.

Against this backdrop, this report examines the current state of California transit finance: why ridership and fare revenues are down and their prospects for recovery; what lessons the successful federal relief bills provide; why commuter-oriented systems are struggling financially much more than those that primarily service transit-reliant riders; and what the financial managers at transit systems have done to cope with this turbulent time and how they see their future financial prospects.

With more people experiencing homelessness in California cities, some transit agencies have begun to comprehensively address the needs of people experiencing homelessness, a population which historically may not have been included in their planning. Research suggests that people experiencing homelessness rely on public transit for the same variety of reasons that all riders do, and that, like other riders, they find it difficult to reach those destinations due to prohibitive costs and transit schedules that do not meet their needs. California transit agencies vary in terms of whether, and how well, they engage with the issue of homelessness. Interviews and a review of policy and programming documents show that most major transit agencies in California made some reference to people experiencing homelessness, but just ten of fifteen addressed their transit needs, and only three addressed those needs through dedicated programs. We use this research synthesis to draw greater attention to the ways that transit agencies can serve the mobility needs of people experiencing homelessness. We present findings from a case study on transit accessibility in San Diego County to supplement our statewide review. This includes a geospatial analysis of transit accessibility from locations where people experiencing homelessness have been known to congregate in San Diego County, as well as interviews with three people who have experienced homelessness in the region and three advocates for the unhoused population. We identify the ways that transit accessibility is a complex issue, requiring consideration of proximity, ease of physical access, and programmatic supports. Based on our research, we recommend that transit and service organizations consider the following: (1) establish coordinated outreach in transit environments, (2) offer shuttles to services and employment to help one resolve their homelessness, (3) improve the reliability and connectivity of public transit, (4) support fare assistance programs, and (5) incorporate expertise from people with lived experience of homelessness.

Transit bus operations in California are experiencing new challenges due to economic conditions and the ongoing global pandemic. A confluence of factors has created a focus on this critical public-needs serving industry, due to state and local efforts to reduce emissions of pollutants and climate-changing gases. Transit bus operations in California provide essential and additional useful services that offer critical mobility to needy populations (elderly and handicapped) as well as many other groups for whom transit buses provide the most economical, convenient, and low-emission options. To address the role of transit bus operations in meeting California’s aggressive greenhouse gas (GHG) and emissions, the California Air Resources Board (ARB) has implemented an ambitious Innovative Clean Transit (ICT) regulation that requires all public transit agencies to gradually transition to a 100 percent zero-emission bus (ZEB) fleet.1 Beginning in 2029, 100% of new purchases by transit agencies must be ZEBs, with a goal for a full transition by 2040. Prior to that 25% of purchases of new buses must be ZEBs in 2023-2025 for large transit agencies, rising to 50% in 2026-2028. For smaller transit agencies, defined as those with less than 100 buses in annual maximum service, there is no requirement for 2023-2025 and the requirement for 2026-2028 is 25%, but the 100% ZEB purchase requirement starting in 2029 applies to all agencies.