All Research Products

Policies developed to support drivers of used PEVs may ultimately attract a broader group of people into the PEV market, as used vehicles are less expensive than new ones. Researchers at the University of California, Davis used aggregated data at the zip code level to understand where buyers of second-hand PEVs are located, and to explore differences in the location and characteristics of regions with more original owners vs. second owners of PEVs.

Researchers examined the possibility of ride-sharing being able to mitigate traffic congestion by developing a two-stage algorithm to solve the routing problem with ride-share in real-time within a context where ride-sharing drivers are traveling toward their own destinations while making detours to serve passengers with flexible pickup and drop-off locations.

The research report explored the use of High Occupancy Vehicle (HOV) lanes and meeting points in a ride-sharing system where drivers have their own origin and destination.

This data is from the project, Dynamic Routing for Ridesharing. The data is randomly generated within grids where each unit of the grid represents a 1-mile by 1-mile square. It is used to generate the origins and destinations of passengers.

This report focuses on the analyses of the data collected in this project, in particular on the differences in attitudes towards transportation and the environment among different generational groups, the adoption and use of shared mobility services, and their relationship with vehicle ownership, the interest in the adoption of alternative fuel vehicles, and the interest in the future adoption of connected and automated vehicles.

This research assessed the impact of USEPA’s AERMOD dispersion model (version of 19191) source types on predicted pollutant concentrations via a case study for the I-75/I-575 Northwest Corridor (NWC) in Atlanta, GA.

This study follows a deterministic modeling approach to project two scenarios of FCEV adoption and the resulting hydrogen demand (low and high) up to 2050 in California, using a transportation transition model. The study then estimates the number of hydrogen production and refueling facilities required to meet demand.

To understand current climate adaptation workforce development needs, researchers at the University of Vermont surveyed state departments of transportation and metropolitan planning organizations about training needs and opportunities at their agencies and catalogued climate adaptation graduate and certificate programs at universities around the country to assess whether these programs aligned with identified needs.

This data are output from PTV VISSIM via application programming interfaces (APIs). The files are in .csv format. The contents of each file include vehicle ID, vehicle speed (in mph), MOVES estimate of fuel consumption (in grams), and CMEM estimate of fuel consumption (in grams) on the basis of one simulation time step (1 Hz).

This study explores the potential to promote lower-emissions air travel by providing consumers with information about the carbon emissions of alternative flight choices in the context of online flight search and booking.

Researchers at the University of Southern California looked at case studies of ten distressed malls in California’s metropolitan areas to assess their potential for mixed-use development, including housing.

This dataset includes model results on trips, VMT, and emissions for California, generated as the outcome of the research project, "Emissions Impact of Connected and Automated Vehicle Deployment in California".

The dataset is generated as the outcome of the research project - Emissions Impact of Connected and Automated Vehicle Deployment in California.

The market for plug-in electric vehicles (PEVs) that primarily include battery electric vehicles (BEVs) and plug-in hybrid vehicles (PHEVs) has been rapidly growing in California for the past few years. Given the targets for PEV penetration in the state, it is important to have a better understanding of the pattern of technology diffusion and the factors that are driving the process.

As part of the City of Riverside’s Smart-City initiative, UC Riverside researchers have developed an Innovation Corridor testbed for enabling shared electric connected and automated transportation research. The testbed supports various transportation modes including passenger vehicles, trucks, transit (e.g., RTA buses), bicycles, and various forms of micro-mobility.

California has set goals for transitioning the freight sector to near-zero-emission and zero-emission vehicles (ZEVs). California offers several incentive programs to encourage adoption of ZEVs, but purchase decisions are driven by complex factors beyond simple purchase price. Researchers at UC Davis deployed a stated-preference survey of fleet and carrier companies to collect information about vehicle purchase preferences and how they might be influenced by various incentive programs.

Researchers at the University of California, Davis conducted a review of practices in curbside management, and they conducted simulations to evaluate the impact of different management and design strategies on travel time, congestion, vehicle travel, and emissions in residential, commercial, and mixed-use neighborhoods in San Francisco.

The market for plug-in electric vehicles (PEVs) that primarily include battery electric vehicles (BEVs) and plug-in hybrid vehicles (PHEVs) has been rapidly growing in California for the past few years. Given the targets for PEV penetration in the state, it is important to have a better understanding of the pattern of technology diffusion and the factors that are driving the process. Using spatial analysis and Poisson count models, the researchers identify the importance of a neighborhood effect (at home locations) and a workplace effect (at commute destinations) in supporting the diffusion of PEV technology in California.

This policy brief examines the adoption of plug-in electric vehicles in California between 2014 and 2016, both spatially and temporally, to gain a better understanding of the technology diffusion process and the effect of technology exposure, while controlling for sociodemographic factors and the effect of PEV incentive programs on PEV adoption in the state.