research report

Emissions Impact of Connected and Automated Vehicle Deployment in California

Abstract

This study helps understand how the anticipated emergence of autonomous vehicles will affect various aspects of society and transportation, including travel demand, vehicle miles traveled, energy consumption, and emissions of greenhouse gases and other pollutants. The study begins with a literature review on connected and automated vehicle (CAV) technology for light-duty vehicles, the factors likely to affect CAV adoption, the expected impacts of CAVs, and approaches to modeling these impacts. The study then uses a set of modifications in the California Statewide Travel Demand Model (CSTDM) to simulate the following scenarios for the deployment of passenger light-duty CAVs in California by 2050: (0) Baseline (no automation); (1) Private CAV; (2) Private CAV + Pricing; (3) Private CAV + Zero emission vehicles (ZEV); (4) Shared CAV; (5) Shared CAV + Pricing; (6) Shared CAV + ZEV. The modified CSTDM is used to forecast travel demand and mode share for each scenario, and this output is used in combination with the emission factors from the EMission FACtor model (EMFAC) and Vision model to calculate energy consumption and criteria pollutant emissions. The modeling results indicate that the mode shares of public transit and in-state air travel will likely sharply decrease, while total vehicle miles traveled and emissions will likely increase, due to the relative convenience of CAVs. The study also reveals limitations in models like the CSTDM that primarily use sociodemographic factors and job/residence location as inputs for the simulation of activity participation and tour patterns, without accounting for some of the disruptive effects of CAVs. The study results also show that total vehicle miles traveled and vehicle hours traveled could be substantially impacted by a modification in future auto travel costs. This means that the eventual implementation of pricing strategies and congestion pricing policies, together with policies that support the deployment of shared and electric CAVs, could help curb tailpipe pollutant emissions in future scenarios, though they may not be able to completely offset the increases in travel demand and road congestion that might result from CAV deployment. Such policies should be considered to counteract and mitigate some of the undesirable impacts of CAVs on society and on the environment.

published journal article

Characteristics and Experiences of Ride-Hailing Drivers with Electric Vehicles

Abstract

Electrification of transportation network companies (TNCs), such as Uber and Lyft, can produce social and environmental benefits from reduced vehicle emissions and enhanced implementation of renewable electricity as well as private benefits to drivers via reduced vehicle fuel and maintenance costs compared to conventional vehicles. We conducted a survey of plug-in electric vehicle (PEV) drivers on the Uber platform in the US. This paper describes these drivers and their experiences to further understanding of motivations for and barriers to PEV adoption among TNC drivers. The TNC-PEV drivers in this sample clearly recognized, and were largely motivated by, economic benefits of fuel and maintenance savings, thus, increased net earnings, associated with using a PEV to provide ride-hailing services rather than a conventional internal combustion engine vehicle. Most drivers reported charging their PEV every day, most often at home and overnight. This is true even of those with plug-in hybrid electric vehicles (PHEVs) that can run on gas if not charged. Increased electric driving range topped the list of drivers’ wishes to better support PEVs on TNCs, and range limitations topped the list of reasons why PHEV drivers did not opt for a battery electric vehicle (BEV; that runs exclusively on electricity). The second most common wish among all PEV drivers was for more charger locations.

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.

published journal article

The width and value of residential streets

Abstract

Problem, research strategy, and findings:
The width of street rights-of-way is normally determined by traffic engineering and urban design conventions, without considering the immense value of the underlying land. In this article, I develop an economic framework that can inform decisions on street width, and I use tax parcel data to quantify the widths, land areas, and land value of streets in 20 of the largest counties in the United States. Residential street rights-of-way in the urbanized portion of these counties average 55 ft wide, far greater than the functional minimum of 16 ft required for access. The land value of residential streets totals $959 billion in the urbanized portion of the 20-county sample. In most counties, subdivision regulations are binding. That is, few developers choose to build streets that are wider than code requirements, implying that softening requirements would mean more land devoted to housing and less to streets. Although I highlighted the potential for narrower street rights-of-way, I did not consider detailed design issues. Nor did I analyze how any windfall from reduced land requirements would be divided among landowners, developers, and house purchasers.

Takeaway for practice:
Particularly in places with high land values and housing costs, reallocating street rights-of-way to housing would increase economic efficiency. In the most expensive county in the data set—Santa Clara (CA)—narrowing the right-of-way to 16 ft would save more than $100,000 per housing unit through reduced land consumption. Where streets have little or no function through traffic, the costs and benefits accrue almost exclusively to neighborhood residents. Thus, planners could reduce or even eliminate street width requirements in subdivision ordinances, leaving developers to make the trade-off between land for streets and land for housing.

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

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

Transit Agency Responses to Homelessness

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

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.