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

Transit Agency Responses to Homelessness

Publication Date

May 25, 2021

Author(s)

Abstract

For many of the more than 500,000 Americans unhoused each night, transit settings provide a common location for shelter, especially since the advent of the COVID-19 pandemic. Transit operators must address the impact of homelessness on their service, while at the same time upholding their social responsibility to serve all riders, housed and unhoused. Agencies large and small have therefore begun implementing programs and partnerships to respond to homelessness.In order to assess the range and effectiveness of these strategies, the researchers documented and analyzed case studies of the ways U.S. transit agencies are addressing homelessness on their systems. Building on the research team’s prior nationwide survey, the authors identified 10 key operators and interviewed 26 relevant staff people, as well as staff from other partnering organizations, in order to learn how they initiated and carried out each strategy. The study also investigated the scope and resulting impacts of each strategy, the challenges each strategy has encountered (especially since the pandemic began), and the lessons learned during its implementation. The identified programs vary in terms of scope, impact, resource burden, and organizational complexity but can be grouped in the four following categories.

policy brief

The Monetary and Non-Monetary Factors Influencing Travel Choices in an Automated, Shared, and Electric Vehicle Future

Abstract

The transportation system is undergoing three revolutions: vehicle automation, electrification, and shared mobility. While these are still nascent trends, studies suggest that they could become ubiquitous in the coming decades. How these revolutionary changes transpire will have significant implications for transportation sustainability. A key factor will be whether autonomous vehicles are deployed as shared cars that serve many travelers such as in ridesourcing or ridehailing fleets, or as privately owned vehicles that could dramatically increase vehicle miles traveled and associated environmental impacts. To anticipate how these revolutions will affect future transportation, and to develop policy to shape that future, it is important to understand the various factors that influence individuals’ travel choices. These choices include whether to travel alone or with others, and whether to use a private vehicle or a shared one. Some of these factors are monetary, such as the cost of fuel, insurance, and a driver, while others are non-monetary, such as the travel time, comfort, and reliability of each transportation option. The significance of these non-monetary factors is poorly understood and often ignored.
Researchers at the University of California, Davis developed a framework for considering the monetary and non-monetary costs of future travel choices and used existing research to develop interim values for several non-monetary travel choice factors. This policy brief summarizes the findings from that research and provides policy implications

policy brief

Leveraging the California Highway Incident Processing System for Traffic Safety Policy and Research

Abstract

Accurate data on crashes and other traffic incidents are critical for analyzing the rates, costs, and causes of crashes, and for evaluating the effects of safety policies and engineering solutions. There are two official sources of data on traffic incidents in California: 1) the Statewide Integrated Traffic Records System (SWITRS),1 managed by the California Highway Patrol (CHP), which includes post-processed data on traffic incidents leading to human injury or death; and 2) Caltrans’ Performance Measurement System (PeMS),2 which includes data on traffic incidents as well as traffic counts, lane closures, and other information. Both databases draw from CHP incident reports that describe the location, conditions, and other important details and observations surrounding each incident. Traffic safety researchers rely heavily on both databases, but each has limitations. PeMS data are limited to state highways. Incident data can take months to appear in SWITRS and may omit crucial information.

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.

policy brief

Do Electricity Prices Affect Electric Vehicle Adoption?

Abstract

The operational costs of electric vehicles are lower than those of gas-powered vehicles. This advantage is often cited by manufacturers, advocates, and policy-makers as a significant benefit of driving electric vehicles. Yet, the question of how consumers value operational costs when purchasing an electric vehicle is largely unexplored. While prior research has suggested that gasoline prices are an important factor for conventional vehicle buyers, consumers may not have the same awareness of electricity prices as they do for salient gasoline prices. The question of whether consumers accurately assess the costs and benefits of using electricity as a transportation fuel has important implications for electric vehicle adoption and for achieving deep decarbonization of the transportation sector through electrification.

research report

Homelessness in Transit Environments Volume II: Transit Agency Strategies and Responses

Publication Date

May 10, 2021

Author(s)

Abstract

Transit settings represent sites of visible homelessness, especially since the advent of COVID-19, for many of the over 500,000 Americans unhoused each night. This report seeks to understand the scale of homelessness in transit and how transit agencies are responding to the problem. Part I describes the extent of homelessness in transit in several areas by using count data and synthesizing prior research. The research team finds that transit serves as shelter for a high, though quite variable, share of unsheltered individuals, who are more likely than their unhoused peers elsewhere to be chronically unhoused and structurally disadvantaged. Part II provides detailed case studies of strategies taken by transit agencies around the country: hub of services, mobile outreach, discounted fares, and transportation to shelters. The team summarizes each strategy’s scope, implementation, impact, challenges, and lessons learned. Reviewing these strategies, the research team finds value in collecting data more systematically, fostering external partnerships, keeping law enforcement distinct from routine homeless outreach, educating the public, and training transit staff—all in the context of a broader need for more housing and services.

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.

research report

Integrating Traffic Network Analysis and Communication Network Analysis at a Regional Scale to Support More Efficient Evacuation in Response to a Wildfire Event

Abstract

As demonstrated by the Camp Fire evacuation, communications (city-to-city, city-to-residents) play important roles in coordinating traffic operations and safeguarding region-wide evacuation processes in wildfire events. This collaborative report across multiple domains (fire, communication, and traffic), documents a series of simulations and findings of the wildfire evacuation process for resource-strapped towns in Northern California. It consists of (1) meteorological and vegetation-status dependent fire spread simulation (cellular automata model); (2) agency-level and agency-to-residents communication simulation (system dynamics model); and (3) dynamic traffic assignment (spatial-queue model). Two case studies are conducted: one for the town of Paradise (and the surrounding areas) and another for the community of Bolinas. The data and models are based on on-site visits and interviews with local agencies and residents. The integrated simulation framework is used to assess the interdependencies among the natural environment, the evacuation traffic, and the communication networks from an interdisciplinary point of view, to determine the performance requirements to ensure viable evacuation strategies under urgent, dynamic wildfire conditions. The case study simulations identify both potential traffic and communication bottlenecks. This research supports integrating fire, communication, and traffic simulation into evacuation performance assessments.

research report

Do Electricity Prices Affect Electric Vehicle Adoption?

Abstract

This report presents evidence that gasoline prices have a larger effect on demand for battery electric vehicles (BEVs) than electricity prices in California. A spatially-disaggregated panel dataset of monthly battery electric vehicle registration records was matched to detailed records of gasoline and electricity prices in California from 2014-2017, and the matched data was used to estimate the effect of energy prices on battery electric vehicle demand. Two distinct empirical approaches (panel fixed-effects and a utility-border discontinuity) yield remarkably similar results: a given change in gasoline prices has roughly four times the effect on battery electric vehicle demand as a similar percentage change in electricity prices.