Authors: Mollie Cohen D’Agostino, Jerel Francisco, Susan A. Shaheen, and Daniel Sperling
Senate Bill (SB) 1298 granted the California Department of Motor Vehicles (DMV) a legislative mandate to develop the Autonomous Vehicle Program. In this landmark 2012 bill, the DMV is allowed to “consult with the [California Highway Patrol (CHP)], Institute of Transportation Studies at the University of California, or any other entity DMV identifies that has expertise in automotive technology, automotive safety, and autonomous system design.”2This issue paper is offered to the State of California in the spirit of this consultation privilege. This research is also a project component of the Climate Smart Transportation and Communities Consortium (C-STACC) for the Strategic Growth Council (SGC) (Task 3.4.4). A review draft of this issue paper was submitted to the California State Transportation Agency (CalSTA) in March 2021 in response to their solicitation for feedback of the draft Automated Vehicle (AV) Framework. This paper leverages the eight principles for AV policy included in the draft CalSTA framework...
Authors: Sam Fuller, Tatjana Kunz, Austin L. Brown, Mollie C. D’Agostino
Cities and states across the U.S. are assessing fees or taxes on transportation network company (TNC) platforms, such as Uber and Lyft. The goals of these policies include traffic and emissions mitigation, as well as revenue generation, among other objectives. This research aims to assess the goals and effectiveness of these fees in achieving some of these policy objectives, primarily congestion and emissions mitigation. The analysis addresses a core difficulty in comparing TNC fees—some fees are assessed per mile and others per trip. The researchers compared 21 fees implemented by state and local governments across theUnited States and apply a methodology to compare these diverse fees and taxes based on a hypothetical ride informed by Uber’s fare calculator, as well as other sources. The findings show that when adjusted for comparison, the highest fees, by a wide margin, are assessed in downtown New York City and Chicago (during peak hours). A key policy implication of this research is that most fees or taxes are not large enough to affect enough travelers' choices to hail a TNC, and most do not differentiate between solo and pooled/shared rides. Only San Francisco, Chicago, New York City, and New Jersey differentiate between solo and shared rides, which is likely to influence travelers in choosing to share a ride. This is problematic given that increasing passengers per vehicle mile traveled is an essential strategy in managing congestion and reducing emissions associated with all vehicle travel, including TNCs.
Authors: Mollie Cohen D’Agostino, Paige Pellaton, and Brittany White
Congestion pricing can be an equitable policy strategy. This project consisted of a review of case studies of existing and planned congestion pricing strategies in North America (Vancouver, Seattle, and New York) and elsewhere(Singapore, London, Stockholm, and Gothenberg). The analysis shows that the most equitable congestion pricing systems include 1) a meaningful community-engagement processes to help policymakers identify equitable priorities; 2) pricing structures that strike a balance between efficiency and equity, while encouraging multi-modal travel; 3) clear plans for investing CP revenues to equalize the costs and benefits of congestion relief; and lastly,4) a comprehensive data reporting plan to ensure equity goals are achieved. This project was developed to support the San Francisco County Transportation Authority in its efforts to conduct the Downtown Congestion Project.
Authors: Authors:Kelly L. Fleming, Mollie Cohen D’Agostino
Contributors: Austin L. Brown , Alan Jenn, Gil Tal, Ken Kurani, Angela Sanguinetti, Giovanni Circella, Scott Hardman, Nic Lutsey
This issue paper synthesizes research related to electrification of TNC vehicles and considers policy pathways for addressing barriers to electric-vehicle (EV) use among TNC drivers. Only 0.5% of the 2–3 million TNC drivers in the United States currently drive EVs. A primary barrier to wider EV adoption is the larger upfront cost of an EV relative to a conventional vehicle, a barrier that persists despite the potential for EV ownership to yield long-term savings. The short-term nature of this barrier speaks to a need for additional policies—such as purchase incentives for used EVs or support for TNC-EV rental programs—that can make EV access more equitable for TNC drivers.
Author: Kelly L. Fleming; Contributors: Austin Brown, Mollie D’Agostino, Tatjana Kunz, Hannah Safford, Yoon Jae Annie Lee
Existing statutes related to Automated Vehicles (AVs) tend to be preliminary in scope. This paper creates a scale for evaluating AV policy: from most permissive to most restrictive. Our findings are that AV policy among states varies considerably, but many policies are in the middle of the road, and many states have limited legislative actions to codifying definitions or establishing exploratory committees. This assessment points to the fact that states are readying to take more decisive action. Therefore, it is critical to identify some possible best practices for AV policy development as states explore the topic. Our analysis points to guidelines for developing safe, equitable and sustainable AV policy.
Authors: Mollie D’Agostino, Paige Pellaton, and Austin Brown; Contributors: Hannah Safford, Kelly Fleming, and Cassidy Craford
Massive amounts of transportation data are generated every day. These data can support transportation planning, policy, and research— especially when it comes to emerging mobility options such as scootersharing, bikesharing, and ridehailing. However, there are not yet well-established mechanisms for sharing mobility data. New policy frameworks are needed to streamline and expand mobility data sharing while respecting privacy and proprietary concerns. Frameworks that achieve these goals must consider how best to (1) standardize, (2) share, (3) securely store, and (4) analyze and apply mobility data. This brief summarizes insights from the UC Davis issue paper “Mobility Data Sharing: Challenges and Policy Recommendations”, which addresses each of the above components....For a concise summary see the 2-page Policy Brief.
Authors: Gordon J. Anderson, Austin L. Brown, and Hannah R. Safford
The American civil liability framework has two basic goals: ensuring the efficient compensation of victims for their injuries and assigning the cost of compensation to the blameworthy party. When it comes to auto crashes, the existing liability system achieves these goals by assigning liability based on human fault and requiring human drivers to carry insurance. But this system, and the legal theories that support it, are predicated on the assumption that car crashes are traceable to human driver error.
In the near future, automated vehicles (AVs) capable of self-driving will come to market. These vehicles will sometimes crash while operating in a self-driving mode. The problem is that the current vehicle liability scheme does not neatly translate to a world where driving errors are made by nonhumans. Failure to update liability laws could be a missed opportunity to promote AV usage and thereby maximize the technology’s safety benefits. Furthermore, a patchwork liability scheme that varies between jurisdictions can jeopardize efficient victim compensation and fair liability assignment.
Authors: by Austin Brown, Executive Director, Policy Institute for Energy, Environment, and the Economy Greg Rodriguez, Of Counsel, Best, Best & Krieger Tiffany Hoang, Graduate Student Researcher, Policy Institute for Energy, Environment, and the Economy
Federal governance of AVs has been limited. To date, the U.S. Department of Transportation (USDOT) has issued only voluntary guidelines on AV development and deployment....So far, twenty-nine states and the District of Columbia have enacted AV-related legislation, while cities like Boston and Portland have adopted AV policy frameworks. State and local AV polices involve a variety of approaches from requiring testing permits to encouraging electric and shared AVs. This illustrates that there is no “one-size-fits-all” way to govern AVs...States and local governments have many goals for their transportation systems, including reducing congestion, improving equity, and reducing pollution. AVs will be a powerful tool to achieve these goals, but only if good governance structures empower these governments to set good policy.
Authors: Farzad Alemi and Caroline Rodier
First-mile ride-hailing access services could reduce the generalized costs for almost one-third of drive-alone commuters. The analysis found that 31% of identified drive-alone trips could see a reduction in generalized costs (accounting for the value of time and monetary costs) by an average of $8 per trip by switching to ride-hailing and BART to get to work (Figure 1). Most of these savings would be monetary; parking costs and bridge tolls in the Bay Area are relatively high. Most commuters would not save time by switching modes. Shared ride-hailing first-mile access services could also reduce generalized costs. Low-income and single-vehicle households may be most likely to benefit from a first-mile ride-hailing service. First-mile ride-hailing access services could also contribute to significant VMT and GHG emissions reductions.
Authors: by Alan Jenn, Institute of Transportation Studies, University of California, Davis
Incentives for plug-in electric vehicles (PEVs) are typically designed to encourage broad consumer adoption of the new technology. However, maximizing electrification of the transportation sector also requires incentives targeted at stakeholders with high travel intensity, i.e., those exhibiting particularly high passenger occupancy and/or vehicle-miles traveled (VMT). This policy brief focuses on one such class of stakeholders: transportation network companies (TNCs) such as Uber and Lyft. It examines empirical data of electric vehicle use in TNCs and discusses research findings on the potential impacts of electrifying TNCs. It also raises important considerations for the development of future policy.
Research by Caroline Rodier Institute of Transportation Studies, UC Davis
Policy Brief by Julia Michaels, 3 Revolutions Future Mobility Program, UC Davis
Automated vehicles (AVs) may significantly disrupt our transportation system, with potentially profound environmental effects. This policy brief outlines the mechanisms by which AVs may affect the environment through influencing travel demand, as well as the magnitude of these effects on vehicle miles travelled (VMT) and greenhouse gas (GHG) emissions. Personal AVs and AV taxis (or ride-hailing services) are likely to increase VMT and GHG emissions, exacerbate traffic congestion in city centers, and potentially lead to suburban sprawl. Electrification and vehicle sharing may reduce some of these environmental effects, but targeted policies must be put in place to ensure that these solutions are effective.