Database search is coming soon. In the meantime, use the following categories to explore the database resources:
AARP Public Policy Institute, RAND Corporation and Urbanism Next collaborated to better understand the ways in which shared mobility and AVs will be impacting older adults. Through a review of literature, interviews with public and private sector players in this arena, and a roundtable with over 25 experts from around the country, the project team developed a framework that identifies a range of factors around new mobility and AVs that will be affecting older adults’ mobility, independence and safety. The framework is a guide for governments and private sector companies to help them think broadly about impacts, understand barriers, and can serve as an internal checklist to guide future policy, research and development.
Using experience from working on the Knight AV Initiative, Urbanism Next created this white paper to provide a foundation for public sector agencies to approach autonomous vehicle deployment and policy with a focus on equity. This report outlines ways that public agencies can identify community needs and shape deployment to ensure that AVs will be accessible for all.
Autonomous Vehicles (AVs) will impose challenges on cities that are currently difficult to fully envision yet critical to begin addressing. This research makes an incremental step toward quantifying the impacts that AVs by examining current associations between transportation network company (TNC) trips — often viewed as a harbinger of AVs — and parking revenue in Seattle. Using Uber and Lyft trip data combined with parking revenue and built environment data, this research models projected parking revenue in Seattle. Results demonstrate that total revenue generated in each census tract will continue to increase at current rates of TNC trip-making; parking revenue will, however, start to decline if or when trips levels are about 4.7 times higher than the average 2016 level. The results also indicate that per-space parking revenue is likely to increase by about 2.2 percent for each 1,000 additional TNC trips taken if no policy changes are taken. The effects on revenue will vary quite widely by neighborhood, suggesting that a one-size-fits-all policy may not be the best path forward for cities. Instead, flexible and adaptable policies that can more quickly respond (or better yet, be proactive) to changing AV demand will be better suited at managing the changes that will affect parking revenue.
The purpose of this study is to go beyond cataloging pilot projects to determine the lessons learned, emerging trends and considerations, and examples of promising practices from pilot projects in the United States and Canada. Researchers assessed 220 pilot projects and 11 case studies. Based on that assessment, they recommend 10 actions for pilot projects generally. The study resulted in 31 lessons learned organized by pilot goals, evaluation, implementation, outcomes, and policy and infrastructure implications.
The development of automated vehicles is moving into the deployment phase. Automation is being tested in vehicles as well as buses, trains, trucks, and tractors. Some initial deployment could occur in Oregon in the form of pilot programs for a low-speed passenger shuttle and a truck-mounted attenuator. This guide focuses on potential impacts for the next five to fifteen years and discusses policy implications for each use case of automated vehicles.
This report summarizes the major assumptions, predictions and forecasts that have been made for autonomous vehicles. It emphasizes their impact and takes focus on the effects it will have on previously immobile people and what it will take to integrate them legislatively.
The Mcity driverless shuttle began operating on the University of Michigan's campus in June 2018. This report focuses on how the researchers collected data and designed the project in order to achieve the project goals of leaning how people react to riding in the shuttles and a how road users interact with the driverless shuttles.
"In 2017, the City of Arlington contracted with the autonomous shuttle company EasyMile to begin the first self-driving shuttle program open to the public in the United States. From August 2017 to August 2018, the Milo vehicles operated on off-street trails that connect major entertainment venues with remote parking areas. The program’s name represents mile zero - the point at which guest arrive at their destination. Milo operated at over 110 events during the program with a perfect safety record."
Motion sickness is a serious consideration on any car trip where you’re not driving. So what are we supposed to do in self-driving vehicles? Researchers are finally looking into this question with an experiment designed to see just what makes people like us so sick.
This paper, for the first time, presents comparable projections of travel behavior impacts of the introduction of autonomous vehicles (AVs) into the private car fleet for two countries, namely the USA and Germany. The focus is on fully autonomous vehicles (AVs) which allow drivers to engage in other activities en route. Two 2035 scenarios – a trend scenario and an extreme scenario – are presented for both study countries. For these projections, we combine a vehicle technology diffusion model and an aspatial travel demand model. Factors that influence AV impact in the behavioral model are mainly new automobile user groups, e.g. travelers with mobility impairments, and altered generalized costs of travel, e.g. due to a lower value of travel time savings for car travel. The results indicate that AV penetrations rates might be higher in Germany (10% or 38% respectively) than in the USA (8% or 29% respectively) due to a higher share of luxury cars and quicker fleet turnover. On the contrary, the increase of vehicle mileage induced by AVs is not higher in Germany (+2.4% or +8.6% respectively) than in the USA (+3.4% or +8.6% respectively). This is mainly due to the lack of mode alternatives and lower fuel costs resulting in a higher share of travel times among the total generalized costs of travel in the USA. These results clearly indicate that context factors shaped by national policy will influence AV adoption and impact on travel demand changes. Based on these results the paper draws policy recommendations which will help to harness the advantages of AVs while avoiding their negative consequences.
Continuous and dynamic growth in demand for road transport, especially in developing countries, causes increase of greenhouse gases (GHG) emissions. At the same time the emissions of toxic components of exhaust gases harmful to human health and the environment enhance – particulate matter, nitrogen oxides, carbon monoxide and others. In particular, GHG emission and increase their concentration in the atmosphere, where road transport is the largest issuer in the transport sector, become one of the most important global problems. So far actions towards reducing energy consumption and emissions have not caused a decrease in global emissions. The aim of authors of this paper is to analyze the potential for AV to reduce GHG emissions from road transport. The analysis includes not only technical and technological issues, but also organizational and in the management of transport demand.
The Transportation Authority’s “Emerging Mobility Evaluation Report” provides the first comprehensive look at the rapidly evolving emerging mobility sector in San Francisco. The report outlines the range of services operating in San Francisco, covering everything from ride-hail services to autonomous vehicles and microtransit to scooter sharing. In the report, the Transportation Authority evaluates how these services and technologies align with the city’s 10 Guiding Principles related to collaboration, safety, transit, congestion, sustainability, equitable access, accountability, labor, disabled access, and financial impact.
"Connected and automated vehicle (CAV) technologies have the potential to change transportation on a global scale. These technologies could improve safety, significantly alter transportation costs, and change traffic patterns and congestion." This time is now to begin having these conversations about how CAVs may integrate into our cities and the impact they could have on land use.
Although recent studies of Shared Autonomous Vehicles (SAVs) have explored the economic costs and environmental impacts of this technology, little is known about how SAVs can change urban forms, especially by reducing the demand for parking. This study estimates the potential impact of SAV system on urban parking demand under different system operation scenarios with the help of an agent-based simulation model. The simulation results indicate that we may be able to eliminate up to 90% of parking demand for clients who adopt the system, at a low market penetration rate of 2%. The results also suggest that different SAV operation strategies and client's preferences may lead to different spatial distribution of urban parking demand.
This report recommends potential research and policies that will help shape progress towards that vision. It also clarifies some opportunities and preparatory work for TransLink to consider as an operator. These are explained in the body.
Automated vehicle (AV) policy development and assessment is a difficult and complicated process. Today’s road and vehicle policies are the product of a hundred years of lessons learned. They generally address five areas: safety, efficiency, mobility, convenience, and impact on the environment. Now the prospect-turned-reality of automated vehicles entering public roadways has opened up a number of new policy-related questions. Is it enough to simply modify current road and vehicle policies or will new policies need to be developed addressing much broader aspects of the transportation system? How can these policies be developed to accommodate technologies that either do not yet exist or are only now being tested on the road in constrained environments? Perhaps most importantly, how can policy influence technological design to safely operate with other road users and can we look ahead to have a better view of potential unintended consequences?
"In this paper we propose a new method to study how replacing privately owned conventional vehicles with automated ones affects traffic delays and parking demand in a city. The model solves what we designate as the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP), which dynamically assigns family trips in their automated vehicles in an urban road network from a user equilibrium perspective where, in equilibrium, households with similar trips should have similar transport costs.
This municipal action guide is meant to give cities the ability to better understand and approach the impending roll out of autonomous vehicles in their cities. We hope to lay out the current typologies of how cities and other levels of government are working together with the private sector to begin to integrate self-driving cars onto the roadways.
This resolution by the Governor of Washington speaks support for the testing of autonomous vehicles in the state of Washington.
This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.
This report estimates that by 2030, a substantial share of the 175 million Americans who live in the nation's largest cities will turn to SAEVs, cutting transportation costs by nearly 50%, reclaiming time instead of losing hours a day to traffic and putting up with all the expense and hassle of urban automobile ownership. SAEV fleets will account for nearly 25% of all auto passenger miles traveled in the US by 2030. Such a change will have an enormous impact on health, safety, and quality of life in cities: Traffic accidents and fatalities will be reduced by nearly two-thirds. Pollution will be drastically curtailed. Cities can repurpose millions of square feet once used for parking to new green spaces or commercial uses while securing more affordable mobility and accessibility for elderly, disabled, and low-income people.
Connected and fully automated or autonomous vehicles (CAVs) are becoming increasingly viable 23 as a technology and may soon dominate the automotive industry. Once CAVs are sufficiently 24 reliable and affordable, they will gain greater market penetration, generating significant economic 25 ripple effects throughout many industries. This paper synthesizes and expands upon analysis from 26 multiple reports on the economic effects of CAVs across 13 different industries and the overall 27 economy.
The full story of autonomous vehicles is yet to be written. We created four scenario planning stories that explain how cities could shape the driverless future: tap taxi to tackle isolation, weaving a microtransit mesh, a human touch on robot delivery, reprogramming bus, bikes and barriers.
"The purpose of this report is to provide an overview of the state of automated vehicle (AV) technology in transit. The Florida Department of Transportation (FDOT) wishes to know what AV technology is currently available that could be used in transit with an eye towards possible demonstration projects."
"This research shows that public transportation (in its current form) will only remain economically competitive where demand can be bundled to larger units. In particular, this applies to dense urban areas, where public transportation can be offered at lower prices than autonomous taxis (even if pooled) and private cars. Wherever substantial bundling is not possible, shared and pooled vehicles serve travel demand more efficiently."
This Strategic Plan is designed to help the East-West Gateway Council of Governments (EWG) to better position itself to prepare for emerging transportation technologies in its planning and investment decision making processes.
"Automated driving technologies are currently penetrating the market, and the coming fully autonomous cars will have far-reaching, yet largely unknown, implications. A critical unknown is the impact on traveler behavior, which in turn impacts sustainability, the economy, and well-being. Most behavioral studies, to date, either focus on safety and human factors (driving simulators; test beds), assume travel behavior implications (microsimulators; network analysis), or ask about hypothetical scenarios that are unfamiliar to the subjects (stated preference studies). Here we present a different approach, which is to use a naturalistic experiment to project people into a world of self-driving cars. We mimic potential life with a privately-owned self-driving vehicle by providing 60 h of free chauffeur service for each participating household for use within a 7-day period. We seek to understand the changes in travel behavior as the subjects adjust their travel and activities during the chauffeur week when, as in a self-driving vehicle, they are explicitly relieved of the driving task. In this first pilot application, our sample consisted of 13 subjects from the San Francisco Bay area, drawn from three cohorts: millennials, families, and retirees. We tracked each subject’s travel for 3 weeks (the chauffeur week, 1 week before and 1 week after) and conducted surveys and interviews. During the chauffeur week, we observed sizable increases in vehicle-miles traveled and number of trips, with a more pronounced increase in trips made in the evening and for longer distances and a substantial proportion of “zero-occupancy” vehicle-miles traveled."
"This report examines the changes that might result from the large-scale uptake of a shared and self-driving fleet of vehicles in a mid-sized European city. The study explores two different self-driving vehicle concepts, for which we have coined the terms 'TaxiBot' and 'AutoVot'. TaxiBots are self-driving cars that can be shared simultaneously by several passengers. AutoVots pick-up and drop-off single passengers sequentially. We had two premises for this study: First, the urban mobility system upgrade with a fleet of TaxiBots and AutoVots should deliver the same trips as today in terms of origin, destination and timing. Second, it should also replace all car and bus trips. The report looks at impacts on car fleet size, volume of travel and parking requirements over two different time scales: a 24-hour average and for peak hours only."
Through a review of long-range transportation plans and interviews with planners, this article examines how large metropolitan planning organizations are preparing for autonomous vehicles. In just a few years, the prospect of commercially available self-driving cars and trucks has gone from a futurist fantasy to a likely near-term reality. However, uncertainties about the new technology and its relationship to daily investment decisions have kept mention of self-driving cars out of nearly all long-range transportation plans.
"This article intends to advance future research about the travel behavior impacts of SAVs, by identifying the characteristics of users who are likely to adopt SAV services and by eliciting willingness to pay measures for service attributes. The results show that service attributes including travel cost, travel time and waiting time may be critical determinants of the use of SAVs and the acceptance of DRS. Differences in willingness to pay for service attributes indicate that SAVs with DRS and SAVs without DRS are perceived as two distinct mobility options. The results imply that the adoption of SAVs may differ across cohorts, whereby young individuals and individuals with multimodal travel patterns may be more likely to adopt SAVs."
This article discusses the changes that will be necessary once AVs hit our streets. The changes in insurance policies, jobs, land use, etc. will change our societal norms.
This study advances the national conversation about how to cope with the effect of AVs on workers in three ways: by setting forth a framework for discussion, presenting quantitative simulations and qualitative scenarios to help assess key impacts, and providing policy recommendations for mitigating negative impacts while also setting an agenda for research on policy.
This paper discusses the current and future state of AVs, and the implications for policy at the federal, state, and local levels. It does not intend to summarize all the research nor provide new analysis of the potential implications of AVs. The goal is to provide concrete and substantive recommendations for policymakers in order to responsibly deploy AVs on public roads.
This article is an introduction to how AVs may be able to service the general public and become a part of our transit systems.
Waymo, the self-driving car unit of Google parent Alphabet Inc, urged the National Highway Traffic Safety Administration (NHTSA) to “promptly” remove regulatory barriers for cars without steering wheels and brake pedals.
Driverless vehicles will likely have a huge impact on our future; however, it is the government’s actions (now and in the future) that will determine how they are integrated into society and if the impacts are largely positive or negative. The intent of this guide is to outline the role of government in the integration of driverless vehicles in society and present the information that local and regional governments need to inform planning and decision-making – now and in the future.
The purpose of this White Paper is to help cities prepare in advance for autonomous technology by passing formal resolutions and setting in motion Smart Mobility Plans. The document covers: Terminology, Benefits and risks associated with autonomous technology, Common autonomous vehicle deployment phases, How changing transportation technology affects governance, Approaches for harnessing benefits while limiting risks, Examples, Developing resolutions – local context, Conclusion and sample resolution language. The sample language and bullet points can also be used for presentations, policy papers, Comprehensive or Transportation Plan updates and memos. Much of the information is also helpful when drafting policy on other types of technology, including ridehailing/sharing services and smart city technology (e.g., Internet of Things (IoT) and sensors).
This White Paper offers a prototype framework for integrated shared, electric and automated mobility (SEAM) governance. The SEAM Governance Framework Prototype has four phases: (i) governance work principles outlining essential approaches to be considered by developers of SEAM governance; (ii) governance visions, including objectives that the authors believe should be embedded in SEAM governance development goals; (iii) governance instrumentation stock, where creative and exhaustive tools for public- and private-sector actors are presented by type and priority (“SEAM rank”); and (iv) policy evaluation tips and tools, which highlight issues that typically impede the evaluation of governance instruments and present evaluation models.
Website provides information for the testing of AVs with a driver, including: adopted regulations, information for manufacturers, testing permit holders, AV collision reports, AV disengagement reports, previous hearings and workshops, and background on AVs in California.
Over the past few years, many studies have provided detailed descriptions of the potential benefits associated with the introduction of autonomous vehicles, such as improvements in traffic flows, local and global emissions, traffic safety, cost efficiency of public and private transport operations, etc. Additionally, the mobilization of mobility-impaired people and the independent car use of travelers without a driver’s license have been identified as potential benefits for users. However, merely estimating the benefits of these direct (or first-order) effects is unlikely to show the full picture of the consequences that will emerge once autonomous vehicles enter the roads. In this paper, we therefore put emphasis on discussing systemic (or second-order) effects. The paper presents a conceptual exploration of these effects based on literature and research findings to date. We show that these systemic effects have the potential – especially in urban areas and without adequate policy intervention – to eliminate at least some of the benefits initially associated with autonomous vehicles. Following this systemic view on autonomous vehicles, we discuss policy aspects for responsible authorities and planners on how to prepare transportation systems for the challenges related to the introduction of autonomous vehicles, and conclude with areas of research that seem highly important in terms of further investigation in this context.
"This report explores autonomous vehicle benefits and costs, and implications for various planning issues. It investigates how quickly self driving vehicles are likely to be developed and deployed based on experience with previous vehicle technologies, their benefits and costs, and how they are likely to affect travel demands and planning decisions such as optimal road, parking and public transit supply."
"As a guide for planners and policymakers, the objective of this thesis is to develop a strong foundation for anticipating the potential impacts resulting from advancements in vehicle automation. To establish the foundation, this thesis uses a robust qualitative methodology, coupling a review of literature on the potential advantages and disadvantages of vehicle automation and lessons from past innovations in transportation, with recent trends of the Millennial Generation, carsharing services, and a series of interviews with thought-leaders in automation, planning, policymaking, transportation, and aviation. From the perspective of understanding the bigger picture, this thesis developed a proposed future scenario of vehicle automation in the next five to ten years that is used to suggest guiding principles for policymakers, and key recommendations for planners, engineers, and researchers."
"To better understand the emerging area of low-speed automated shuttles, the U.S. Department of Transportation (USDOT) Intelligent Transportation Systems Joint Program Office (ITS JPO) partnered with the John A. Volpe National Transportation Systems Center (Volpe) to review the current state of the practice of low-speed automated shuttles. These vehicles share many characteristics with other forms of automated vehicles but include unique considerations in terms of design, operations, and service type, including: fully automated driving (intended for use without a driver); operational design domain (ODD) (restricted to protected and less-complicated environments); low speeds (cruising speeds around 10-15 mph); shared service (typically designed to carry multiple passengers, including unrestrained passengers and standees); and shared right-of-way with other road users, either at designated crossing locations or along the right-of-way itself. This report defines design and service characteristics; discusses the deployers, their motivations, and their partners; and provides information on demonstrations and deployments, both international and domestic. The document also provides context on common challenges and suggested mitigations. Building on all of this information, the document identifies several research questions on topics ranging from safety and accessibility to user acceptance and societal impacts."
This paper presents ten key challenge areas that need to be at the center of automated vehicle discussions across all sectors and stakeholders, along with a glossary of key terms. It is intended to serve as a discussion guide and orientation piece for people entering the conversation from a wide variety of perspectives, including advocacy, public policy, research, injury prevention, and technology developers.
Autonomous vehicles use sensing and communication technologies to navigate safely and efficiently with little or no input from the driver. These driverless technologies will create an unprecedented revolution in how people move, and policymakers will need appropriate tools to plan for and analyze the large impacts of novel navigation systems. In this paper we derive semi-parametric estimates of the willingness to pay for automation. We use data from a nationwide online panel of 1,260 individuals who answered a vehicle-purchase discrete choice experiment focused on energy efficiency and autonomous features. Several models were estimated with the choice micro-data, including a conditional logit with deterministic consumer heterogeneity, a parametric random parameter logit, and a semi-parametric random parameter logit.
This report summarizes findings from a three-year collaboration between the World Economic Forum and The Boston Consulting Group (BCG) to explore how autonomous vehicles could reshape the future of urban mobility. The project built on the collective insights generated from the Autonomous and Urban Mobility Working Group (Working Group) of the System Initiative on Shaping the Future of Mobility, composed of roughly 35 business executives from diverse industries (including automotive, technology, logistics, insurance, utilities and infrastructure) that convened for 10 full-day workshops and numerous conference calls.
This briefing document concisely conveys the key findings of NCHRP Research Report 845: Advancing Automated and Connected Vehicles: Policy and Planning Strategies for State and Local Transportation Agencies. NCHRP Research Report 845 assesses policy and planning strategies at the state, regional, and local levels that could influence private-sector automated vehicle (AV) and connected vehicle (CV) choices to positively affect societal goals. The researchers identified and described mismatches between potential societal impacts and factors that influence private-sector decisions on CV and AV technologies. Policy and planning actions that might better align these interests were then identified. Researchers and the project oversight panel identified the promising actions and then conducted in-depth evaluations of the feasibility, applicability, and impacts of 18 strategies.
The development of self-driving, or autonomous, vehicles is accelerating. Here’s how they could affect consumers and companies.
Ford and other companies say the industry overestimated the arrival of autonomous vehicles, which still struggle to anticipate what other drivers and pedestrians will do.
To help decision-makers understand the impact of AV technology on regional plans, modeling tools should anticipate automated vehicles’ effect on transportation networks and traveler choices.This research uses the Seattle region’s activity based travel model to test a range of travel behavior impacts from AV technology development. The existing model was not originally designed with automated vehicles in mind, so some modifications to the model assumptions are described in areas of roadway capacity, user values of time, and parking costs. Larger structural model changes are not yet considered.
How safe should highly automated vehicles (HAVs) be before they are allowed on the roads for consumer use? This question underpins much of the debate around how and when to introduce and use the technology so that the potential risks from HAVs are minimized and the benefits maximized. In this report, we use the RAND Model of Automated Vehicle Safety to compare road fatalities over time under (1) a policy that allows HAVs to be deployed for consumer use when their safety performance is just 10 percent better than that of the average human driver and (2) a policy that waits to deploy HAVs only once their safety performance is 75 or 90 percent better than that of average human drivers — what some might consider nearly perfect. We find that, in the long term, under none of the conditions we explored does waiting for significant safety gains result in fewer fatalities. At best, fatalities are comparable, but, at worst, waiting has high human costs — in some cases, more than half a million lives. Moreover, the conditions that might lead to comparable fatalities — rapid improvement in HAV safety performance that can occur without widespread deployment — seem implausible. This suggests that the opportunity cost, in terms of lives saved, for waiting for better HAV performance may indeed be large. This evidence can help decisionmakers better understand the human cost of different policy choices governing HAV safety and set policies that save more lives.
One of the big promises of self-driving vehicles is the idea that autonomous vehicles will liberate people from driving. In this vision of the future, passengers will scan news reports on phones and tablets, pour-over notes and briefings for important meetings, and view videos on their handheld devices. They will reclaim the hours once wasted clinging to a steering wheel. Unless they end up developing a headache or becoming dizzy, drowsy, or nauseated.
"Cruise, the startup General Motors acquired to develop its self-driving car, will launch an autonomous taxi service on the gnarly, crowded streets of San Francisco," CEO Dan Ammann said Wednesday. It will not, however, do so by the end of this year, the deadline it set for itself in 2017. Instead, Cruise will spend the rest of 2019 expanding its tests across the city and working on the less technical aspects of running such a service, from charging its electric cars to working with regulators to soothing a public that may be wary of robots roaming the roads.
The introduction of fully autonomous vehicles will constitute perhaps the largest change to everyday transportation in living memory and is predicted to deliver a wide range of environmental, social and economic benefits. However, the route to full automation is also likely to involve significant challenges, with public attitudes playing an important role in determining the level of success with which the technology is introduced. This report outlines the results of a survey of 233 people measuring current attitudes to autonomous vehicles.
See something that should be here that isn't? Have a suggestion to make?