policy brief

Cutting Emissions from Aviation: Is High-Speed Rail the Answer?

Abstract

Per passenger trip, aviation is the most greenhouse gas-intensive mode of transport for intercity travel in California, but there is no clear pathway for decarbonizing this sector. While electrification proves to be the dominant pathway toward decarbonizing ground travel, this pathway is not technically feasible for commercial air travel, at least with currently available technologies.While planners and policymakers wait for breakthroughs in fueling technologies, reducing greenhouse gas (GHG) emissions from aviation will require shifting trips from the air to less GHG-intensive modes of transportation. The California High-Speed Rail project can serve this function, but funding for the full route of the Phase 1 segment⁠ — spanning from Southern California to the San Francisco Bay Area — remains unallocated. In light of the high-speed rail project’s precarious funding status, more information is needed about the potential benefits of the proposed rail network, especially in the wake of the COVID-19 pandemic, which has exacerbated uncertainty around future travel demand.To address this need, UCLA Luskin Center for Innovation staff synthesized recent literature on the environmental and economic impacts of high-speed rail (HSR) projects from around the globe (Table 1). The synthesis looked at studies that examined the effect of HSR on at least one of the following metrics: GHGs, local air pollution, noise, economic value added, employment, property values, societal cost savings, and economic integration. The synthesis also looked at the conditions under which HSR leads to net benefits, so as to potentially reproduce those conditions in California.

research report

Travel Behavior Impacts of Transportation Demand Management Policies: May is Bike Month in Sacramento, California

Abstract

Active modes of transportation like bicycling and walking are extremely beneficial to society, including helping to reduce the amount of travel people may make by car (i.e., vehicle miles traveled) and in turn reducing congestion and transportation-related greenhouse gas emissions and air pollutants. Bicycling and walking also have direct and positive health impacts. Several steps have been taken to promote active transportation in cities and regions, including awareness campaigns, transportation demand management policies, building new bicycling infrastructure, and the launch of bike-sharing programs. However, it is often unclear how much impact a specific strategy can have on actual rates of bicycling and walking in a community or region. UC Davis assisted the Sacramento Council of Governments (SACOG) in evaluating the impact of the agency’s “May is Bike Month” campaign. The purpose of the campaign is to motivate residents working and/or living in the region to start using (or increase the use of) bicycles as a mode of transportation. SACOG conducted a survey as part of the 2018 “May is Bike Month” campaign, which collected self-reported information from participants on the frequency of bicycling before and after the campaign, perceived barriers to bicycling, motivations for bicycling, travel habits, household and individual sociodemographic, and place of residence. UC Davis analyzed the survey data to better understand the role of land use characteristics and transit accessibility in bicycling rates. This information will be used to understand the variables that affect individuals’ decisions to increase, decrease, or not change bicycling levels during and after the “May is Bike Month” campaign. This project helps SACOG identify the groups which are most and least receptive to the campaign, and the ways these groups of individuals have reacted (in terms of changing their bicycling behavior) in response to the campaign. SACOG can use this information to make strategic changes to its annual “May is Bike Month” campaign in order to optimize the campaign’s effectiveness in future years, and/or coordinate the campaign with additional initiatives to promote bicycling in the Sacramento region.

conference paper

A Longitudinal Analysis of the Heterogeneous Changes in Travel Behaviors in Response to the COVID-19 Pandemic in the United States

Abstract

The COVID-19 pandemic has caused a huge disruption worldwide with direct and indirect effects on travel behavior. In response to extensive community spread and potential risk of infection, during the early stage of the pandemic, many state and local governments implemented non-pharmaceutical interventions that restricted non-essential travel for residents. This study evaluates the impacts of the pandemic on mobility by analyzing micro panel data (N = 1,274) collected in the United States via online surveys in two periods, before and during the early phase of the pandemic. The panel makes it possible to observe initial trends in travel behavior change, adoption of online shopping, active travel, and use of shared mobility services. This analysis intends to document a high-level overview of the initial impacts to spur future research to dive deeper into these topics. With the analysis of the panel data, substantial shifts are found from physical commutes to teleworking, more adoption of e-shopping and home delivery services, more frequent trips by walking and biking for leisure purposes, and changes in ride-hailing use with substantial variations across socioeconomic groups. The social and environmental implications of these findings are discussed and suggestions for effective policy and directions for future research are made in the conclusion.

policy brief

By Transit, By-Right: Impacts of Housing Development Approval Processes on Transit-Supportive Density

Abstract

Transit ridership in Los Angeles County has fallen
consistently over the past decade despite major investments
in public transportation. The reasons for this outcome vary,
but one likely culprit is the county’s built environment,
which is generally auto-oriented and low-density. Allowing
more, higher-density housing to be built near transit could
help increase transit ridership, but this solution faces two
obstacles. The first and largest obstacle is widespread
restrictions on multifamily development. The second, and
the focus of this brief, is the housing development process:
Even if new multifamily housing is allowed on a site, a
complicated, lengthy or unpredictable process could still
discourage its production.
Development processes are often categorized as “by-right,”
meaning developments are approved or not based on
whether they meet certain objective requirements, or as
“discretionary” — negotiated project-by-project in a back-
and-forth between city officials and builders.
Compared to discretionary processes, by-right processes
should in theory reduce the cost, delay, and uncertainty
associated with securing approvals, allowing homes to be
delivered more quickly and less expensively. It has been
difficult to test this hypothesis, however, because by-right
approvals are rare in cities where housing is in high demand
and are usually reserved for smaller projects.
The Transit Oriented Communities (TOC) density bonus
program, implemented in Los Angeles in 2017, changed the
city’s development process for certain projects, creating
a by-right approval pathway for many projects that would
have previously been discretionary, and streamlining
the entitlement process for many others that remained
discretionary. We take advantage of this program to measure
the impact of by-right and streamlined processes on project
approval times, with shorter times serving as a proxy for less
costly and potentially less risky housing development. For
each project, we determine the entitlement pathway, total
approval time, size, subsidy status, parking provided, certain
characteristics of the parcel, neighborhood characteristics
such as median household income and distance from the
central business district, and its location relative to the
TOC program boundaries. Using a multivariate analysis, we
compare approval times for each category, with and without
controls for many project and neighborhood characteristics.

published journal article

What travel modes do shared e-scooters displace? A review of recent research findings

Abstract

The impacts of shared e-scooters on modal shifts have received increased attention in recent years. This study provides a review of the literature for modal shifts in the US and other countries. The profile of shared e-scooter users is rather similar to that of station-based and free-floating bikeshare programs. The empirical data reveal that people use shared e-scooters in place of cars at substantial rates, especially in many US cities, which suggests that in many locations shared e-scooters may be a good strategy for reducing car dependence. The use of shared e-scooters as a complement to public transit varies highly by city, highlighting how technology, regulations, and incentives may be needed in some cities to ensure modal integration and harvest the potential societal benefits from the introduction of shared e-scooters.

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.