Prepared by Robert Shapiro and Isaac Yoder for the U.S. Chamber of Commerce Technology Engagement Center

Executive Summary

This report examines the potential social and economic benefits of autonomous vehicles (AVs). The U.S. and global markets for AVs will be extensive, and companies in the United States, China, Japan, and elsewhere are competing to develop and market them. The appeal and benefits of AVs rest on their potential to sharply reduce traffic accidents, enhance people’s mobility and access (especially for those who have physical or visual limitations), reduce greenhouse gas emissions, and provide substantial economic benefits for the public. This report presents econometric models to estimate those potential benefits.

Estimates of when AVs will be widespread vary, depending on one’s views about the pace of technological progress, consumer acceptance, the development of a conducive regulatory framework, and other factors. Most analysts expect high-level AVs (Levels 4 and 5) to enter the market in the next decade, and forecasts for widespread sale and adoption of these vehicles range from 2035 to the 2050s. Today, numerous companies across the United States are testing and deploying AVs on public roads. Because we cannot know precisely when and to what extent Americans will adopt AVs, our models project the likely effects when AVs constitute 25% or 50% of the U.S. motor vehicle fleet. We focus mainly on the nearest-term scenario, a 25% adoption rate. Because we also do not know the precise technologies of those AVs, our models project the likely effects for three stages of AV operations and technology based on the multimodal traffic flow model developed by the European Union’s AV project.

1. Basic AVs: Programmed to take a safe approach on braking distances, maintain sizable gaps for lane changes, and travel through intersections without signals.

2. Standard AVs: Programmed to follow traffic laws and operate like an unimpaired human driver with sensors to determine distances and speeds of other vehicles.

3. Advanced AVs: Programmed with high levels of sensor awareness and predictive capacity and the capability to cooperate with other AVs, resulting in smaller gaps in all maneuvers.

Safety and Health Benefits:

We found that accident rates would fall sharply (compared with accident rates in 2021) if AVs represented 25 percent of U.S. motor vehicles.

• With Basic AVs, we estimate 571,000 fewer accidents with 5,000 fewer fatalities and economic savings of $38 billion. With Standard AVs, we estimate 1,145,000 fewer accidents with 9,000 fewer fatalities and economic savings of $75 billion. With Advanced AVs, we estimate 1,442,000 fewer accidents, 12,000 fewer fatalities, and $94 billion in savings.

Mobility and Access Benefits:

We found that at a 25% adoption rate, Standard and Advanced AVs should markedly enhance mobility and access for elderly people and nondrivers, and Advanced AVs should also greatly enhance mobility for persons with disabilities.

• Although Basic AVs would not significantly enhance mobility, Standard AVs should increase annual vehicle miles traveled (VMT) by older people by a total of 2.5 billion miles and the VMT of nondrivers by 1.3 billion miles. Advanced AVs should increase the annual VMT of persons with disabilities by 4.6 billion miles, the annual VMT of older people by 4.9 billion miles, and the annual VMT of nondrivers by 2.4 billion miles.

Climate and Environmental Benefits:
We found that a 25% adoption of electric Advanced AVs should significantly reduce CO2 and NOx emissions, while also accounting for emissions associated with generating the electric power for AVs. Because electric vehicles produce no exhaust, the net benefits depend on those associated gains and the traffic and fuel efficiency of AV operations, less the emissions from the grid generating the electric power of AVs. We estimate the net benefits using three possible configurations for the grid based on the continued use of fossil fuels with greater or lesser use of substitutes:

1. Climate+: Grid with enhanced use of sustainable fuels and less use of fossil fuels.

2. Climate Neutral: Fossil fuels continue to dominate the grid without an enhanced role for sustainable energy.

3. Median Grid: The median between these alternatives.

We use motor vehicle CO2 and NOx emissions in 2021 as a baseline to estimate the net changes in emissions with a 25% adoption rate of electric-powered Advanced AVs. (Notably, emission reductions would be greater with Standard AVs or Basic AVs because Advanced AV operations require more electrical power than Standard or Basic AV operations).

•  With a 25% adoption of Advanced AVs and a Climate + grid, CO2 emissions related to motor vehicles would be 8.2% lower, and NOx emissions would be 8.9% lower.
• With a 25% adoption of Advanced AVs and a Climate Neutral grid, CO2 emissions should fall 5.9%, and NOx emissions should fall 6.4%.
• With a 25% adoption of Advanced AVs and a median grid, CO2 emissions should be 7.1% lower, and NOx emissions should be 7.7% lower.

Economic Competitiveness:

The report also examines the economic importance of U.S. competitiveness in the production and adoption of AVs. The U.S. motor vehicle industry is a vital source of jobs for Americans. In 2021, American motor vehicle and parts manufacturers and dealers directly employed 2,922,000 people. In addition, their suppliers employed 1,270,000 people creating the industry’s intermediate inputs, for a total 4,192,000 jobs. With the introduction of AVs, these employment numbers will increase.

We also expect the composition of that employment to shift toward more highly paid, technologically related jobs in software, computers, and telecom equipment and services.

The adoption of AVs will have other economic benefits. At a 25% adoption rate, annual savings from fewer accidents should total up to $94 billion (in 2021 dollars). The mobility benefits of AVs include gains in jobs and income for nondrivers, people with disabilities, and people living in areas with little access to public transit.

Further, many technologies developed for AVs can be used in other areas, from mining to spacecraft, creating jobs to support those activities.

As U.S. and global markets for AVs grow, American producers will face strong competition from state-subsidized Chinese manufacturers and other foreign competitors. In this rivalry, the United States has a technological edge because U.S. companies dominate the world’s top producers of software, computers, and telecom equipment and services. China’s advantage comes from its extensive state subsidies for Chinese AV makers. U.S. policymakers can level the playing field by actively promoting the safe and secure deployment of AVs in the United States.

Prepared by Sarah Kaufman, NYU Wagner

The promises of autonomous vehicles in cities are clear – but so are the challenges. While they show incredible potential for moving both people and goods – from providing mobility for populations underserved by public transit to creating safer traffic conditions – without incentives, regulations, and proper preparation, cities may not reap these benefits.

This document, developed with stakeholders in the public, private, and advocacy sectors, aims to outline how policymakers, industry, and stakeholders can mitigate challenges and pursue opportunities to collectively unlock the positive benefits of AVs for cities. To identify specific principles that are applicable to a range of U.S. cities, Nuro and the NYU Rudin Center for Transportation brought together five working groups of practitioners, policymakers, advocates, and industry leaders between September 2022 and January 2023. These participants hailed from cities large and small, as well as from suburbs and state authorities, representing public, private, and non-profit sectors. Taken together, the discussions produced a set of ten principles that can be applied to cities of all sizes when introducing autonomous vehicles.

Ten Principles for Autonomous Urbanism:

1. Engage early and often.
2. AV companies should work with cities to help improve urban infrastructure to serve all residents and users.
3. Communication with first responders is critical.
4. AV deployment should lead to safer streets, not stranded assets.
5. Rigorous safety standards must be met.
6. Data-driven decision-making is valued.
7. AVs should lead the conversion to zero-emission vehicles and support public transit.
8. AVs should be efficient users of space.
9. Workforce gains should be maximized through public-private collaboration.
10. Economic opportunities and access to services should be equitable.

These principles are intended to inform urban plans in advance of the introduction of new transportation modes. They should assist cities in strategically aligning with their needs and goals of safety, sustainability, accessibility, equity and livability – while also fostering innovation. Furthermore, these principles should offer a framework for public-private partnerships that will help to increase availability of safer, cleaner, and more efficient transportation options, and the infrastructure to support them.

This work was sponsored by Nuro, an autonomous, electric vehicle company focused on providing a convenient, eco-friendly alternative for last-mile goods delivery.

Additional support was provided by NYU C2SMART, a USDOT Tier 1 University Transportation Center.

Prepared by McKinsey Center for Future Mobility

This report is a collaborative effort by Johannes Deichmann, Eike Ebel, Kersten Heineke, Ruth Heuss, Martin Kellner, and Fabian Steiner, representing views from the McKinsey Center for Future Mobility.

By 2035, autonomous driving could create $300 billion to $400 billion in revenue. New research reveals what’s needed to win in the fast-changing passenger car market. 

The dream of seeing fleets of driverless cars efficiently delivering people to their destinations has captured consumers’ imaginations and fueled billions of dollars in investment in recent years. But even after some setbacks that have pushed out timelines for autonomous-vehicle (AV) launches and delayed customer adoption, the mobility community still broadly agrees that autonomous driving (AD) has the potential to transform transportation, consumer behavior, and society at large. 

Because of this, AD could create massive value for the auto industry, generating hundreds of billions of dollars before the end of this decade, McKinsey research shows.1 To realize the consumer and commercial benefits of autonomous driving, however, auto OEMs and suppliers may need to develop new sales and business strategies, acquire new technological capabilities, and address concerns about safety. 

This report, which focuses on the private-passenger-car segment of the AD market, examines the potential for autonomous technologies to disrupt the passenger car market. It also outlines critical success factors that every auto OEM, supplier, and tech provider should know in order to win in the AD passenger car market. (Other McKinsey publications explore the potential of shared AVs such as robo-taxis and robo-shuttles, as well as autonomous trucks and autonomous last-mile delivery.)

From CMU and Aspen Institute

This research project grew out of a desire to explore the impacts of emerging technologies on work. Specifically, the Carnegie Mellon University H. John Heinz III College (CMU) research team and the Aspen Institute Future of Work Initiative partnered together to explore potential impacts to long-haul truckers and policy responses to automation in the trucking industry.

The project began with a literature review to better understand possible workforce and industry impacts, as well as potential policy responses to the issue of automation in long-haul trucking. Our CMU research team was most interested in exploring likely workforce impacts on truckers’ wages, displacement, changes in job duties/skills, and any changes to demographics. Our team was also interested in understanding impacts of automation on the trucking industry.

After completing the introductory literature review, our team concluded that there was a lack of comprehensive publicly available policy analysis regarding the impacts of automation on the trucking workforce and industry. As a result, our team decided to implement the Delphi method, a systematic way to analyze expert opinion and make predictions, to gather primary data from stakeholders in the trucking industry, as well as policy and academic worlds.

As part of the Delphi method, our team administered a non-representative three-round survey to uncover several themes on workforce, industry, and potential policy responses. Our team received 40 responses from the first survey round, 30 from the second, and 26 from the third.

Survey participants were allowed to select multiple professional areas of expertise, and the most commonly selected areas across all three surveys were legislative policy and academia. Survey participants had the most consensus when predicting impacts to the long-haul trucking industry, with over 90% of survey two participants (28 out of 30) being optimistic about the impact of automation on the trucking industry. Expected improvements to the industry were a key driver of this optimism as the majority of participants believed automation would increase efficiency and reduce costs within the industry.

There was much more variation amongst survey participants’ answers when asked to predict potential workforce impacts from automation. There was a nearly even split when survey two participants were asked about their overall attitude towards the impact of autonomous technology on the long-haul trucking workforce, with 46.7% (14 out of 30 respondents) optimistic and 36.7% (11) pessimistic. Participants identified existing workforce trends such as the aging workforce, the current driver shortage, the adoption rate of autonomous technology, and increasing demand in the industry, as factors that would likely impact workforce issues.

With regards to potential policy responses, a majority of survey participants identified a limited role of government to handle the disruption of autonomous technology. The majority of participants believed government will enact performance and safety standards with respect to autonomous technology. But, when asked what government should do, the majority felt that government should not be primarily responsible for supporting displaced long-haul truckers as a result of automation. Many of these participants who did not believe government was responsible clarified that government intervention was not necessary beyond existing retraining and welfare options.

Results from our survey research suggest that there will be time for regulators and the larger government to prepare for the disruption of automation in the long-haul trucking industry. For the next 15 years, our survey participants largely agreed that the job of a truck driver will remain relatively the same. Autonomous technology, however, does promise to change future truck driving jobs. Given the uncertainty around the timing of potential impacts, we conclude that regulators and policymakers should focus in the near-term on better understanding how autonomous technology will be used in the long-haul trucking industry. Having a better sense of how the technology will be used will allow for more informed policy development on performance and safety standards, as well as workforce issues.

From Securing America’s Future Energy

Trucking forms the backbone of the U.S. economy, currently moving more than $725 billion in annual revenue across the country. Yet as freight deliveries are set to grow 40 percent by 2040, smart policy is required to meet this demand while also improving roadway safety and fuel efficiency. A new report released today by SAFE identifies new technologies and policy recommendations that could lead to a safer, more efficient trucking industry.

SAFE’s analysis found:

• At only 4 percent of the U.S. fleet, long-haul trucks account for 13 percent of daily petroleum consumption.
• The adoption of linked 33-foot trailers, known as twin-33s, will result in an estimated 23 billion gallons of diesel saved by 2050.
• The widespread use of existing platooning technologies could save up to 20 billion gallons of diesel fuel through 2050.
• The trucking industry is likely to be an early implementer of autonomous vehicle technology because freight transportation presents a more predictable and less complex driving environment than urban roads. However, these efforts are being threatened by Congress, which has omitted heavy duty trucks from current autonomous vehicle legislation.

To encourage the adoption of these technologies and grasp these potential savings, SAFE proposes a range of potential policy recommendations that can provide the necessary clarity and flexibility for the trucking industry. These recommendations include:

• Truck platooning should be exempted from existing following distance laws.
• The federal government should pre-empt the ability of states to set their own autonomous standards.
• Congress should transition to performance-based standards for commercial vehicles and, in the interim, authorize the use of twin 33-foot trailers.
• The federal government should quantify the fuel efficiency implications of ADAS technologies.
• The federal government should preserve the 5.9 GHz spectrum band for V2X communication.

by Joseph Kane and Adie Tomer, from Brookings.edu

Automation has become one of the major ongoing stories regarding the future of the American economy. What began with the rise of robots—and loss of jobs—across manufacturing industries is now a full blown threat to traditional jobs across all industries, salary bands, and education requirements. The effects are wide-reaching, no job may be safe.

On the surface, trucking seems to fit perfectly into this national narrative. Autonomous vehicles are one of the hottest developments in technology across the country, and an automated truck already delivered 50,000 cans of beer within Colorado last fall. Meanwhile, truckers hold the most common occupation in 29 different states. This map quickly spread around the internet. Unsurprisingly, analysts expect automated trucks to proliferate in the next five to ten years, leading to significant job losses in the process.

The only problem? The numbers do not clearly back up the predictions.

In addition to the numerous regulatory and logistical hurdles that automated trucks still need to clear, generalizing the skilled work undertaken by millions of truck drivers and their peers overlooks how this industry functions. In many ways, the current national conversation on the trucking industry tends to overemphasize the technology and oversimplify the complex set of labor concerns, where many jobs are not likely to disappear anytime soon.

Similar to most infrastructure jobs, truck drivers depend on a wide range of skills to carry out their jobs every day. Just as there are different types of doctors, there are different types of truck drivers – from heavy and tractor-trailer truck drivers who focus on long-haul journeys to delivery truck drivers who carry lighter loads and navigate local streets. Not surprisingly, many of these drivers are not simply sitting behind the wheel all day on auto drive. They also inspect their freight loads, fix equipment, make deliveries, and perform other non-routinized tasks.

Standardized data verify this non-routinized conception of truck-driving. The Department of Labor’s O*NET database shows how truck drivers have a lower “degree of automation” compared to most occupations nationally. On a scale of 0 (not at all automated) to 100 (completely automated), O*NET surveys workers across all types of occupations, where those with simpler, repeated tasks are often better suited for automated technologies, such as telephone operators and travel agents. The average degree of automation, however, remains quite low (29.6) for all occupations, and heavy and tractor-trailer truck drivers (22) and delivery drivers (24) rate even lower than that. Significantly, they also rate lower than some of the country’s other largest occupations, including office clerks (32), cashiers (37), and receptionists (47).

Lower automation scores by themselves, of course, do not necessarily mean that trucks may not ultimately drive themselves. And when these trucks hit the market—and they will—they very well may have an empty front seat. Yet, it also seems likely that many new complementary jobs may emerge over time too, requiring new skillsets to oversee these new trucks and complete other non-automated tasks to support them. While it can be difficult to predict the exact positions needed, it is possible that new types of material movers and inspectors may appear within major shipping industries, or there may even be a new form of on-call trucking repair jobs. At the same time, local retailers, from restaurants to clothing stores, may need extra staff hours to unload trucks.

Whatever happens, it is crucial to not confuse truck drivers themselves with their entire industry, which depends on many different types of workers who carry out tasks that are not always easily automated.

The trucking industry as a whole relies on a variety of workers who are also less susceptible to automation according to O*NET. Truck drivers only make up 60 percent of the nearly 1.5 million workers in this industry. Other support workers fill roles across more than 150 different occupations, from truck mechanics to cargo agents to accountants, who have a relatively low degree of automation (25.5) on average. In this way, even as automated trucks may alter the actual shipment of goods, these technologies are unlikely to supplant all of the various technical, financial, and logistical work activities in support of that movement.

Indeed, regardless of how these automated technologies play out, truck drivers and their fellow support workers are going to still carry out several specialized tasks, which will require continued on-the-job training and familiarity with precise sets of tools. O*NET tracks the particular types of tools used by individual occupations to better understand the technical skills and familiarity required to fill a given job, ranging from utility knives and two-way radios to personal computers and GPS receivers. On average, workers across all occupations nationally use about six tools to perform their jobs; however, workers in the trucking industry use about 27 tools on average, requiring a greater depth of knowledge and training that make it more difficult to automate their activities. Some workers use considerably more tools, including automotive service technicians (173), compliance officers (108), and truck mechanics (97).

Finally, there are some overarching regulations that could stall the automation impacts from driverless technologies. States currently maintain oversight for whether driverless trucks can operate within their borders—and those regulations are inconsistent from state to state. Those inconsistencies will likely limit interstate shippers from using these vehicles to easily move goods across different states until certain regulatory thresholds are consistent. You can apply the same thinking to local regulations. Without approvals for driverless trucks to operate along specific rights of way—say a busy pedestrian corridor—municipalities and counties could make it difficult for trucking firms to use the technology.

With the rise of new automated vehicle technologies, policymakers and planners must prepare for a self-driving future. And for good reason. These technologies hold promise in improving transportation across the country, including reductions in energy use, pollution, and significant safety benefits. But they also raise questions over land use impacts and economic access, among a host of other concerns.

Frequently lost in this conversation, though, is talk on where workers stand. Truck drivers and Silicon Valley are at odds of how, when, and where any potential labor market effects will take place, with many running under the assumption that some changes are bound to happen nationally in the next decade, especially given the enormous geographic reach of the industry.

Rather than glossing over the potential labor impacts, policymakers, employers, educators, and others should closely monitor these developments over time and link them to relevant workforce development efforts. Automated trucks are likely to change how the industry moves its goods and relies on particular workers, but they will still require workers in general and should not shift the focus away from sustaining economic opportunity.