research report

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

Abstract

A 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—the 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 “top-off” 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 criteria such as land cover, slope, and distance from gas stations, truck hubs, and the truck network.

policy brief

Bike-Share in the Sacramento Region Primarily Substitutes for Car and Walking Trips and Reduces Vehicle Miles Traveled

Abstract

Dock-less, electric bike-share services offer cities a new transportation option with the potential to improve environmental, social, and health outcomes by increasing physical activity and reducing vehicle miles traveled (VMT) and related greenhouse gas emissions. But these benefits accrue only if bike-share use replaces car travel. If bikeshare pulls users from public transit, personal bikes, or walking, the benefits will be limited. Little is known about the factors influencing whether bike-share substitutes for driving. Understanding the degree to which and under what circumstances bike-share use reduces car travel can inform cities’ efforts to meet VMT reduction goals set under California’s Sustainable Communities and Climate Protection Act of 2008 (Senate Bill 375). Researchers at the University of California, Davis collected user surveys and system-wide trip data from a Sacramentoarea dockless e-bike-share program in 2018 and 2019 to examine factors influencing travel mode substitution and estimated system-wide VMT reductions caused by bikeshare use. They developed a model to examine factors influencing bike-share demand and estimated potential VMT reductions for hypothetical expanded service scenarios.

research report

How Dock-less Electric Bike Share Influences Travel Behavior, Attitudes, Health, and Equity: Phase II

Abstract

Dock-less, electric bike-share services offer cities a new transportation option with the potential to improve environmental, social, and health outcomes. But these benefits accrue only if bike-share use replaces car travel. The purpose of this study is to examine factors influencing whether bike-share substitutes for driving and the degree to which and under what circumstances bike-share use reduces car travel. Major findings in this report include (1) bike-share in the Sacramento region most commonly substitutes for car and walking trips, (2) each bike in the Sacramento bike-share fleet reduces users’ VMT by an average of approximately 2.8 miles per day, (3) areas with a higher proportion of low-income households tend to use bike-share less, (4) bike-share availability appears to induce new trips to restaurants and shopping and for recreation, (5) bike-share trips from commercial and office areas were more likely to replace walking or transit trips, while bike-share trips from non-commercial areas (and trips to home or restaurants) were more likely to replace car trips, (6) expanding the bike-share service boundary at the same fleet density decreases system efficiency and VMT reductions per bike. The result suggests the need for an efficient rebalancing strategy specific to areas by time of day to increase the service efficiency and its benefits. Further analysis of the data used in this study to examine questions such as how bike share can improve transit connections and factors inducing bike use at the individual level will contribute to the development of more robust models and provide additional insights for bike share operation strategies and policy implementation.

research report

Where Ridehail Drivers Go Between Trips: Trading off Congestion and Curb Availability?

Abstract

The research team analyzed what ride-hail drivers do when out of service between paid trips. The paper utilizes a dataset of 5.3 million trips in San Francisco and partitions each out-of-service trip into cruising, repositioning, and parking segments. We find that repositioning accounts for nearly two-thirds (63%) of the time between trips, with cruising and parking accounting for 23% and 14% respectively (these figures exclude short trips). The regression models suggest that drivers tend to make reasonable choices between repositioning and parking, heading to high-demand locations based on the time of day. However, we also find suggestive evidence of racial bias, supporting previous studies of both taxis and ride-hailing that indicate that drivers tend to avoid neighborhoods with high proportions of residents of color.

published journal article

Perceptions of Neighborhood Change in a Latinx Transit Corridor

Abstract

Understanding how nearby residents feel about transit-induced neighborhood change remains understudied despite growing concerns over displacement and gentrification. This study analyzed 329 surveys of resident perceptions of neighborhood change and associated development near an existing commuter rail station and a planned streetcar route in Santa Ana, California, a largely low-income, Latinx community. We found residents were on average satisfied with neighborhood access to transport and amenities, and that higher neighborhood satisfaction was associated with a more positive assessment of development and neighborhood change. Living near the streetcar route was associated with more negative assessments of change, reflecting residents of these areas had heightened concerns about housing costs, displacement, and parking. Results provide planners with insights regarding support for and concerns about transit-induced neighborhood changes that can help foster more equitable and responsive development processes and outcomes.

presentation

Changes in Travel and Air Quality in California During COVID-19

published journal article

Investigating the decision to travel more in a partially automated electric vehicle

Abstract

Partially automated battery electric vehicles (BEVs) are already being sold to and used by consumers. Estimates indicate that as of the end of 2019, there were over 1.2 million Partially Automated Tesla Vehicles—the subject of this study—on the roads globally. Despite this, little research has been done to understand how partially automated vehicles may be changing travel behavior. In this study, we conduct qualitative interviews with 35 owners of Tesla BEVs with Autopilot. The focus was to determine whether partially automated BEVs could cause or are causing an increase in travel. Results show that partial automation and electrification lead to interviewees driving more and choosing to drive rather than fly. These changes are due to increased comfort and reduced stress due to the partial automation system, and because of the lower running costs of a BEV. The results show how partially automated BEVs could increase vehicle miles traveled.

policy brief

Partially Automated Vehicles Are Increasing Vehicle Miles Traveled

Abstract

Research is beginning to show that vehicle automation will encourage more driving because it substantially reduces driver workload, making driving more relaxing and less stressful. This will have environmental sustainability implications, given that vehicle electrification alone will not be sufficient to meet state and federal greenhouse gas reduction targets without reductions in vehicle miles traveled (VMT). Research on the effects of vehicle automation has been somewhat speculative because fully automated vehicles are not yet commercially available. But many automakers are already incorporating automated features such as adaptive cruise control and lane keeping assist into their vehicles. These features assist in driving tasks and reduce the “cost” of driving in much the same way fully automated vehicles promise to do. Researchers at UC Davis surveyed owners of partially automated electric vehicles in California to understand the impact of partial automation on VMT. The survey asked respondents about their use of partial automation systems including BMW Driving Assistant, Ford Co-pilot360, Honda Sensing, Nissan ProPilot Assist, Tesla Autopilot, and Toyota Safety Sense. The results of this study show that partial automation has the potential to cause large increases in VMT.

research report

A Quantitative Investigation into the Impact of Partially Automated Vehicles on Vehicle Miles Travelled in California

Abstract

This project investigated changes in travel behavior by owners of partially automated electric vehicles. Partial automation can control vehicle speed and steering using sensors that monitor the external environment. The researchers used review results from survey responses including 940 users of partial automation, of which 628 who have Tesla Autopilot and 312 with systems from other automakers. Autopilot users report using automation more than users of other partial automation systems. Autopilot has the largest impact on travel, notably 36% of Autopilot users reporting more long-distance travel. Respondents who are younger, have a lower household income, use automation in a greater variety of traffic, roads, and weather conditions, and those who have pro-technology attitudes and outdoor lifestyles are more likely to report doing more long-distance travel. The project used propensity score matching to investigate whether automation leads to an increase in respondents’ annual vehicle miles traveled. For simplicity, the researchers focused only on the impact of Tesla Autopilot and found that automation results in an average of 4,884 more miles being driven per year.

policy brief

Driving California’s Transportation Emissions to Zero

Abstract

California has long been a global leader in clean energy and climate policy, and it has demonstrated how industrial economies can reduce greenhouse gas (GHG) emissions while supporting strong economic growth and promoting equitable and just outcomes. In September 2018, Executive Order B-55-18 set a target for the state to achieve carbon neutrality by 2045. The University of California Institute of Transportation Studies (UC ITS) produced the first comprehensive research report analyzing the policy options that could put California’s transportation sector on a path to be carbon-neutral by 2045 while also centering equity, health, and workforce impacts. The report, summarized in this brief, presents a study conducted by 23 researchers from the four branches of the UC ITS located at UC Berkeley, UC Irvine, UC Davis, and UCLA.