research report

Brace for Impact: The Environmental and Economic Effects of Shifting Passenger Travel from Airplanes to High-Speed Rail

Abstract

This research synthesis surveys recent literature from 2011 to 2020 on the environmental and economic effects of high-speed rail (HSR) projects from across the globe, with relevant lessons for implementation of the California High-Speed Rail (CAHSR) project. Recent literature shows that—under the right conditions—HSR can lead to both environmental and economic gains across a variety of metrics. To maximize environmental gains, HSR ridership needs to be high, energy propulsion must be powered largely by renewables, and displaced demand for intrastate air travel must not be replaced by longer-haul flights. For there to be economic gains, cities connected by HSR must play complementary roles, rather than competitive ones, within the economy. Otherwise, economic benefits will be consolidated in core cities along HSR routes at the expense of intermediate cities, and efficiencies from agglomeration may lead to an overall decline in employment and economic value added. This synthesis closes with some recommendations for future research questions that can inform the development or refinement of policies that support the successful implementation of CAHSR.

published journal article

An L.A. story: The impact of housing costs on commuting

Abstract

The empirical impact of housing costs on commuting is still relatively poorly understood. This impact is especially salient in California given the state’s notoriously high housing costs, which have forced many lower- and middle-class households to move inland in search of affordable housing at the cost of longer commutes. To investigate this linkage, we relied on Generalized Structural Equation Modeling and analyzed 2012 CHTS data for Los Angeles County – the most populous county in the U.S. Our model, which jointly explains commuting distance and time, accounts for residential self-selection and car use endogeneity, while controlling for household characteristics and land use around residences and workplaces. We find that households who can afford more expensive neighborhoods have shorter commute distances (−2.3% and − 3.1% per additional $100 k to median home values around workplaces and residences respectively). Job density, distance to the CBD, and land-use diversity around workplaces have a relatively greater impact on commuting than the corresponding variables around commuters’ residences. Compared to non-Hispanics, Hispanic workers commute longer distances (+3.5%), and so do African American (+5.1%) and Asian (+2.0%) workers compared to Caucasians, while college-educated workers have shorter (−2.6% to −3.6%) commutes. Furthermore, commuters in the top income brackets tend to have faster commutes than lower-income workers. Finally, women’s commutes are ~41% shorter than men’s, possibly because they are balancing work with domestic responsibilities. A better understanding of the determinants of commuting is critical to inform housing and transportation policy, improve the health of commuters, reduce air pollution, and achieve climate goals.

published journal article

Estimating short-term travel demand models that incorporate personally owned autonomous vehicles

Abstract

We estimated travel demand models that incorporate a private autonomous vehicle (AV) option using revealed preference data in which personal chauffeurs simulated a personally owned AV. We investigated four components of activity-based models (ABM): activity pattern and primary destination choice, mode choice, and time of day. We compared the chauffeur week models (“AV future”) to the non-chauffeur week models (current conditions). We found no statistically significant differences in parameters of the individual activity pattern, time of day, or destination choice. For mode choice, however, while the auto constant did not change, the mean value of time decreased by 60%. As the destination choice model included the mode choice log sum, this results in longer average tour lengths. Moreover, while the trip-making propensity of individuals did not change significantly, there was a 25% increase in systemwide trips due to “AVs” (chauffeurs) being sent on errands. This points to the importance of incorporating zero-occupancy vehicle (ZOV) trips into the ABM framework. Our findings suggest that these can be incorporated via the standard ABM development process by adding as additional model components ZOV home-based tours and ZOV subtours. Relatedly, as inter-regional travel is modeled outside the ABM framework, our results indicated that modifications should be made to account for the increase in inter-regional tours, which were 54% more frequent during chauffeur weeks. While these results are from a relatively small sample of 71 individuals, they are the first such travel demand estimation results available from a field experiment, and further studies can build on our framework.

policy brief

Real-World Simulations of Life with an Autonomous Vehicle Suggest Increased Mobility and Vehicle Travel

Abstract

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.

published journal article

Glimpse of the Future: Simulating Life with Personally Owned Autonomous Vehicles and Their Implications on Travel Behaviors

Abstract

To explore potential travel behavior shifts induced by personally owned, fully autonomous vehicles (AVs), we ran an experiment that provided personal chauffeurs to 43 households in the Sacramento region to simulate life with an AV. Like an advanced AV, the chauffeurs took over driving duties. Households were recruited from the 2018 Sacramento household travel survey sample. Sampling was stratified by weekly vehicle miles traveled (VMT), and households were selected to be diverse by demographics, modal preferences, mobility barriers, and residential location. Thirty-four households received 60 hours of chauffeur service for 1 week, and nine households received 60 hours per week for 2 weeks. Smartphone-based travel diaries were recorded for the chauffeur week(s), 1 week before, and 1 week after. During the chauffeur week, the overall systemwide VMT (summing across all sampled households) increased by 60%, over half of which came from “zero-occupancy vehicle” (ZOV) trips (when the chauffeur was the only occupant). The number of trips made in the system increased by 25%, with ZOV trips accounting for 85% of these additional trips. There was a shift away from transit, ride-hailing, biking, and walking trips, which dropped by 70%, 55%, 38%, and 10%, respectively. Households with mobility barriers and those with less auto dependency had the greatest percent increase in VMT, whereas higher VMT households and families with children had the lowest. The results highlight how AVs can enhance mobility, but also caution against the potential detrimental effects on the transportation system and the need to regulate AVs and ZOVs.

research report

Assessing the Incorporation of Racial Equity into Analytical and Modeling Practices in Transportation Planning

Abstract

This report examines if and to what extent state-level transportation departments in four states incorporate race and equity considerations into transportation planning technical analyses and modeling practices, particularly for long-range transportation plans, and how such equity-infused practices can be improved. The research team examined relevant literature, reviewed statewide long-range transportation plans for California and three other states, consulted with other experts, and conducted interviews with scholars and knowledgeable agency staff and practitioners. The findings indicate widespread acknowledgment that racial disparities in transportation exist, and state agencies have expressed a strong commitment to redressing the inequalities. However, while there has been progress in creating analytical equity tools to assess transportation projects and programs, they lack standardization. There have also been few noticeable revisions to existing regional transportation planning models to incorporate equity, and the profession lags behind what is technically possible based on the work of academic researchers. Technical staff need better training in regard to equity issues and agencies should encourage greater collaboration between equity and analytical units to develop and improve frameworks to assess equity performance in plans, programs, and projects.

published journal article

Gender differences in elderly mobility in the United States

Abstract

Mobility is a critical element of one’s quality of life regardless of one’s age. Although the challenges for women are more significant than those for men as they age, far less is known about the gender differences in mobility patterns of older adults, especially in the United States (US) context. This paper reports on a study that examined potential gender gaps in mobility patterns of older adults (aged 65 years and over) in the US by analyzing data from the 2017 National Household Travel Survey. Elderly respondents were first classified into one of six clusters based on socio-demographic variables. A Structural Equation Model (SEM) was then estimated and showed that gender gaps existed in the mobility patterns of the elderly, and the differences were diverse across the different clusters. The most substantial gender gap was found in the Senior Elder with Medical Condition(s) cluster, followed by the High-income Workers cluster and the Middle-income Urban Residents cluster. In contrast, females in the Low-Income Single Elder cluster enjoyed statistically significant positive mobility differences with their male counterparts. Our results also found that female elderly in the Senior Elder with Medical Condition(s) and the Low-income Family Elder clusters suffered most after the cessation of driving, with the largest mobility gender gap in the Middle-income Urban Resident cluster. This study will help transportation planners and policymakers understand gender and other socio-demographic differences in elderly mobility. Thus, it will facilitate the development of measures to improve elderly mobility and reduce gender gaps by recognizing and addressing specific target groups’ mobility characteristics and needs rather than treating the elderly as a single potential user group.

policy brief

Where Do Ridehail Drivers Go Between Paid Trips? A San Francisco Case Study

Abstract

App-based ridehailing services such as Uber and Lyft have revolutionized urban travel. These services improve mobility and reduce demand for parking, but also increase vehicle travel and shift some trips away from walking and public transit.1 As a result, ridehailing has been the largest contributor to increased congestion in recent years in cities such as San Francisco.2 Ridehil services could also be contributing to traffic congestion and pollution when vehicles are out of service between paid rides. Drivers might cruise (circle around while waiting for the next paid ride) or reposition (move to another location in anticipation of the next ride request), both of which can exacerbate congestion and pollution. They might also park (either on- or off-street), which would reduce congestion and pollution but may affect parking and curbspace availability or interfere with other street activities such as drop-offs and deliveries. To gain a better understanding of ridehail driver behavior between paid rides, UC researchers evaluated over 5.3 million ridehail trips in San Francisco in November and December 2016. Each trip was divided into cruising, repositioning, and parking segments.

policy brief

How is the COVID-19 Pandemic Shifting Retail Purchases and Related Travel in the Sacramento Region?

Abstract

A significant portion of the population stayed, and continue to stay, at home due to the COVID-19 pandemic. With more people staying home, online shopping increased along with trips related to pickups and deliveries. To gain a better understanding of the change in retail purchases and related travel, UC Berkeley researchers compared pre-pandemic shopping to pandemic-related shifts in consumer purchases in the greater Sacramento area for nine types of essential and non-essential commodities (e.g., groceries, meals, clothing, paper products, cleaning supplies). In May 2020, the research team resampled 327 respondents that participated in the 2018 Sacramento Area Council of Governments (SACOG) household travel survey. The 2018 SACOG survey collected responses over a rolling six-week period from April to May 2018 and asked residents about their motivations for, attitudes toward, and ease of use of online shopping. They were also were asked about the number of e-commerce purchases made, and the number of deliveries and pickups made from those e-commerce purchases for each commodity type. In addition, respondents also reported changes (less or more) in their behavior from a typical week in January or February 2020 (prior to the COVID-19 pandemic) for: 1) tripmaking, e-commerce purchases, and delivery and pick up frequencies; 2) purchase sizes; 3) distances traveled; and 4) modes used for in-person trips. This brief highlights findings from an analysis on changes in frequency of purchases, deliveries and pickups, and order sizes.

policy brief

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

Abstract

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.