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.