Spatial Modeling of Future Light- and Heavy-Duty Vehicle Travel and Refueling Patterns in California

UC-ITS-2020-46A spatial optimization model was developed for deploying, over the next two decades, hydrogen refueling stations for heavy-duty zero-emission hydrogen vehicles. The model assigns trips to vehicles by applying a routing algorithm to travel demand data derived from another model\u2014the California Statewide Travel Demand Model (developed by the California Department of Transportation). Across a range of adoption levels of hydrogen fuel-cell truck technology, from 2020 through 2030, the results suggest that heterogeneity of travel demand may necessitate an extensive distribution of refueling stations, which may lead to low utilization of stations in the short term. To efficiently employ the capacity of stations, a certain volume of vehicle adoption must be met, and/or truck routes must be planned and committed to specific roadways. Once the number of stations reaches a threshold to meet the principal demand in affected transportation area zones, a small set of smaller \u201ctop-off\u201d stations can be built to meet marginal excess demand. The best location of a hydrogen refueling station within a transportation area zone also depends on the criteria such as land cover, slope, and distance from gas stations, truck hubs, and the truck network

What Do Men Want from a Health Screening Mobile App? A Qualitative Study.

There is a lack of mobile app which aims to improve health screening uptake developed for men. As part of the study to develop an effective mobile app to increase health screening uptake in men, we conducted a needs assessment to find out what do men want from a health screening mobile app. In-depth interviews and focus group discussions were conducted with 31 men from a banking institution in Kuala Lumpur. The participants were purposely sampled according to their job position, age, ethnicity and screening status. The recruitment was stopped once data saturation was achieved. The audio-recorded interviews were transcribed verbatim and analyzed using thematic approach. Three themes emerged from the analysis and they were: content, feature and dissemination. In terms of the content, men wanted the app to provide information regarding health screening and functions that can assess their health; which must be personalized to them and are trustable. The app must have user-friendly features in terms of information delivery, ease of use, attention allocation and social connectivity. For dissemination, men proposed that advertisements, recommendations by health professionals, providing incentive and integrating the app as into existing systems may help to increase the dissemination of the app. This study identified important factors that need to be considered when developing a mobile app to improve health screening uptake. Future studies on mobile app development should elicit users' preference and need in terms of its content, features and dissemination strategies to improve the acceptability and the chance of successful implementation

Tolling Lessons Learned for Road Usage Charge

In 2021, the federal gasoline tax raised about $32.8 billion which accounted for about 70$14 billion (FHWA, 2021). In response, many states have launched pilot or full-scale programs of road-usage charge (RUC) as an alternative transportation funding source. One of the fundamental challenges of RUC is the high cost of implementation compared to a traditional motor fuel tax (Caltrans, 2017). To address this, states look to leverage existing vehicle-level pricing programs, such as road tolling to learn possible synergies between RUC and tolling. In this paper, the authors conducted semi-structured interviews with experts from tolling programs across the U.S. to identify areas of overlap between tolling and RUC. Consequently, they built upon the interview findings with a multi-criteria decision analysis (MCDA) to evaluate how ready the RUC pilot programs are for implementation. The results demonstrated that there are numerous lessons that the RUC pilots can learn from the tolling industry and develop an integrated system—tolling hub operations, methods to maintain data privacy, technology, etc. RUC programs can benefit from integration with tolling from the increased scale of operations which would largely reduce administrative costs. Lastly, ensuring equity in RUC rate design to alleviate any potential financial burdens on low-income populations and ensuring that unbanked and underbanked populations have access to the system is important

New Metrics Are Needed to Understand the Environmental Benefits of Micromobility Services

Micromobility services (e.g., conventional and electric bikeshare programs and electric scootershare programs) hold great potential for reducing vehicle miles traveled and greenhouse gas emissions if these services are used as substitutes for car travel and/or to access public transit. But estimating these environmental effects is challenging, as it requires measuring changes in human behavior—that is, the choice of what transportation mode to use. While many cities collect various micromobility usage metrics to regulate services, these metrics are not sufficient for calculating the sustainability benefits of these services

New UC Davis Model Shows Promise in Identifying Optimal Locations of Hydrogen Refueling Stations for Medium- and Heavy-Duty Trucks in California

Researchers at UC Davis developed “Spatial Transportation Infrastructure, Energy, Vehicles, and Emissions (STIEVE),” an optimization model for hydrogen refueling stations in California. The model uses inputs from the California Statewide Travel Demand Model (CSTDM) and other sources to determine heavy-duty vehicle travel demand across the state, and the corresponding, localized energy demand. The model then determines which of the transportation analysis zones (areas based on census geography used to replicate areas of trip origins and destinations) delineated by the CSTDM are optimal areas for refueling stations and the number of stations needed in each zone to meet demand while minimizing costs. The final step is a suitability analysis that identifies each station’s specific location within a designated transportation analysis zone, based on a determined footprint for the refueling station

New UC Davis Model Shows Promise in Identifying Optimal Locations of Hydrogen Refueling Stations for Medium- and Heavy-Duty Trucks in California

Researchers at UC Davis developed “Spatial Transportation Infrastructure, Energy, Vehicles, and Emissions (STIEVE),” an optimization model for hydrogen refueling stations in California. The model uses inputs from the California Statewide Travel Demand Model (CSTDM) and other sources to determine heavy-duty vehicle travel demand across the state, and the corresponding, localized energy demand. The model then determines which of the transportation analysis zones (areas based on census geography used to replicate areas of trip origins and destinations) delineated by the CSTDM are optimal areas for refueling stations and the number of stations needed in each zone to meet demand while minimizing costs. The final step is a suitability analysis that identifies each station’s specific location within a designated transportation analysis zone, based on a determined footprint for the refueling station

Private versus Shared, Automated Electric Vehicles for U.S. Personal Mobility: Energy Use, Greenhouse Gas Emissions, Grid Integration, and Cost Impacts.

Transportation is the fastest-growing source of greenhouse gas (GHG) emissions and energy consumption globally. While the convergence of shared mobility, vehicle automation, and electrification has the potential to drastically reduce transportation impacts, it requires careful integration with rapidly evolving electricity systems. Here, we examine these interactions using a U.S.-wide simulation framework encompassing private electric vehicles (EVs), shared automated EVs (SAEVs), charging infrastructure, controlled EV charging, and a grid economic dispatch model to simulate personal mobility exclusively using EVs. We find that private EVs with uncontrolled charging would reduce GHG emissions by 46% compared to gasoline vehicles. Private EVs with fleetwide controlled charging would achieve a 49% reduction in emissions from baseline and reduce peak charging demand by 53% from the uncontrolled scenario. We also find that an SAEV fleet 9% the size of today's active vehicle fleet can satisfy trip demand with only 2.6 million chargers (0.2 per EV). Such an SAEV fleet would achieve a 70% reduction in GHG emissions at 41% of the lifecycle cost as a private EV fleet with controlled charging. The emissions and cost advantage of SAEVs is primarily due to reduced vehicle manufacturing compared with private EVs

Private versus Shared, Automated Electric Vehicles for U.S. Personal Mobility: Energy Use, Greenhouse Gas Emissions, Grid Integration, and Cost Impacts.

Transportation is the fastest-growing source of greenhouse gas (GHG) emissions and energy consumption globally. While the convergence of shared mobility, vehicle automation, and electrification has the potential to drastically reduce transportation impacts, it requires careful integration with rapidly evolving electricity systems. Here, we examine these interactions using a U.S.-wide simulation framework encompassing private electric vehicles (EVs), shared automated EVs (SAEVs), charging infrastructure, controlled EV charging, and a grid economic dispatch model to simulate personal mobility exclusively using EVs. We find that private EVs with uncontrolled charging would reduce GHG emissions by 46% compared to gasoline vehicles. Private EVs with fleetwide controlled charging would achieve a 49% reduction in emissions from baseline and reduce peak charging demand by 53% from the uncontrolled scenario. We also find that an SAEV fleet 9% the size of today's active vehicle fleet can satisfy trip demand with only 2.6 million chargers (0.2 per EV). Such an SAEV fleet would achieve a 70% reduction in GHG emissions at 41% of the lifecycle cost as a private EV fleet with controlled charging. The emissions and cost advantage of SAEVs is primarily due to reduced vehicle manufacturing compared with private EVs

Micromobility Trip Characteristics, Transit Connections, and COVID-19 Effects

While micromobility services (e.g., bikeshare, e-bike share, e-scooter share) hold great potential for providing clean travel, estimating the effects of those services on vehicle miles traveled and reducing greenhouse gases is challenging. To address some of the challenges, this study examined survey, micromobility, and transit data collected from 2017 to 2021 in approximately 20 U.S. cities. Micromobility fleet utilization ranged widely from 0.7 to 12 trips per vehicle per day, and the average trip distance was 0.8 to 3.6 miles. The median (range) rates at which micromobility trips substituted for other modes were 41% (16–71%) for car trips, 36% (5–48%) for walking, and 8% (2–35%) for transit, 5% (2–42%) for no trip. In most cities, the mean actual trip distance was approximately 1.5 to 2 times longer than the mean distance of a line connecting origin to destination. There was a weak and unclear connection between micromobility use and transit use that requires further study to more clearly delineate, but micromobility use had a stronger positive relationship to nearby rail use than to nearby bus use in cities with rail and bus service. The COVID-19 pandemic led to more moderate declines in docked than in dockless bike-share systems. Metrics that would enable better assessment of the impacts of micromobility are vehicle miles traveled and emissions of micromobility fleets and their service vehicles, and miles and percentage of micromobility trips that connect to transit or substitute for car trips