Autonomous Driving’s Future: Convenient and Connected

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.)

FOREFRONT: Securing Pittsburgh’s Break-out Position in Autonomous Mobile Systems.

Prepared by: TEConomy Partners, LLC

Performed for: Regional Industrial Development Corporation and the Greater Pittsburgh Chamber of Commerce, with funding support provided by the Richard King Mellon Foundation

Advancements in technology and the forces of convergence are impacting almost every industry and creating significant emerging growth opportunities. Some legacy industries are facing significant change as a result of new business models enabled by convergence of multiple technologies, while other entirely new industries are emerging. In one such area, multiple technology domains are converging to enable the development of Autonomous Vehicles (AVs) which have the potential to not only impact the characteristics of the vehicles themselves but create fundamental shifts in the future of mobility and the infrastructure that vehicles use and interface with. In recent years, major investments and prototyping efforts have focused public attention on this applications area and captured the imagination of industry and policymakers seeking to advance the next generation of technology-based industries.

While autonomous on-road vehicles are one of most publicized applications of autonomy (the ability of a machine to make decisions without the intervention of a human), they are only a part of a much wider landscape for autonomous mobile systems applications. Enabled by new technology convergence areas, significant change is coming to physical devices of any scale that both move and may be equipped with some form of sensing and decision-making system to intelligently perform tasks and navigate their environment. Many tasks that require human or machine spatial movement are potential prospects for automated mobile systems approaches, and this opens up vast and diverse market potentials for disruptive industries. There is a large-scale economic development opportunity for regions of the country that have a distinctive position in the technologies and talent required to research, develop, and build complex integrated autonomous mobile systems products. It is a very specialized space, however, and as Figure ES1 illustrates, the “full stack” of technologies needed to advance such products to prototyping and end market applications is quite complex.

To bring autonomous mobile systems solutions to market, it is not sufficient to build capacity in any one component of the technology stack. Rather, the goal of full deployment of autonomous end market solutions requires capabilities (or the ability to reliably source those capabilities) across the entire technology stack, as well as the means of linking the capabilities in each layer of the stack so that a system can perform as a fully integrated platform rather than a partial solution that requires further commercialization by others. Regions who are able to build out their technology ecosystems to support this type of integration will be poised to realize major economic growth. Triangulating results from multiple recent market research reports places the terrestrial autonomous mobile systems market alone at an estimated $802 billion global market by 2025-26. When adding aerial, marine, and defense autonomous systems to capture the broader autonomous mobile systems market space context, the total likely climbs above $1 trillion in total market size during the mid- to late-period of the present decade. If a region with a robust and well-supported technology ecosystem were to capture even 1% of the $1 trillion global autonomous mobile systems market, it would equate to a $10 billion growth opportunity developing within the next decade.

The implications for potential economic growth around a rapidly scaling multi-billion dollar autonomous mobile systems industry, in conjunction with the readily apparent base of expertise and assets relevant to these technologies in Pittsburgh, have been recognized by key regional stakeholders. While those engaged in advanced economic development for the Pittsburgh region have observed the organic growth of the autonomy sector to date, the opportunity presenting itself to the region and the Commonwealth of Pennsylvania today is of such a scale and importance that a detailed examination of the opportunity is required that includes an evaluation of existing industry activity, current regional innovation assets that can be leveraged towards this opportunity, any gaps in the ecosystem that need to be addressed, and a resulting strategy and action plan developed to guide realization of the full economic opportunity as it unfolds.

Bridging the Divide: Autonomous Vehicles and the Automobile Industry

Jack Caporal – Former Fellow, Scholl Chair in International Business
William O’Neil – Intern, Scholl Chair in International Business
Sean Arrieta-Kenna – Intern, Scholl Chair in International Business

The automobile industry is in the midst of a technology-driven revolution. The industry transition to autonomous, connected, electrified, and shared (ACES) vehicles has the potential to boost technological development and economic activity in the traditional manufacturing cities of the United States, bridging the divide between high-tech innovation hubs and regions historically known for industrial economies.

With the right policy environment, important investments, and effective retooling of existing advantages and relationships, traditional automotive manufacturing clusters can be at the forefront of the technological revolution within the auto industry and seize the growth and employment opportunities that it brings. The Mahoning Valley in northeast Ohio offers a useful case study of economic revitalization through coordinated investment to transform an existing local infrastructure and workforce to the growing electric vehicle (EV) and autonomous vehicle (AV) sectors. Once a hub for steel production, the Mahoning Valley has rebranded itself as “Voltage Valley,” now home to hundreds of new-energy tech startups and one of the largest electric vehicle battery plants in the country.

Due to the massive digitization of today’s cars, vehicle manufacturing should be considered a process that takes place in the physical and digital world. Imaging, robotics, navigation, connectivity, data processing, and artificial intelligence broadly are the building blocks of AVs. The importance of software development, which is increasingly recognized by automakers transitioning to producing smarter vehicles, will lead to the formation of economic clusters in cities like Pittsburgh which focus on critical technology development. Pittsburgh is the home of multiple successful AV startups, many of which are well connected to Carnegie Mellon University, demonstrating the role that higher education can play as a pipeline for emerging industry talent outside of traditional manufacturing hubs.

The clustering effects evidenced by the Mahoning Valley and Pittsburgh case studies demonstrate how policymakers can incentivize the scaling of AV development to unlock social benefits. AVs would benefit the general population by improving road safety, ameliorating traffic congestion, and reducing the emission of greenhouse gases and other pollutants. For individuals, AVs offer significant efficiency benefits: increasing access to ridesharing and public transportation, as well as reducing costs and travel time due to the route optimization and traffic management functions of artificial intelligence (AI). While improvements in traffic management and road safety would be immediately tangible, some benefits, like the reduction in emissions and average vehicle miles traveled, would likely become apparent only after a longer period of time.

The benefits of ACES vehicles are broad, especially for cities not traditionally considered technology hubs. However, to fully realize these benefits, the auto industry must work with policymakers and the general public to establish a favorable regulatory environment and build consumer confidence in artificial intelligence and AVs. Full-scale deployment will facilitate the potential of ACES vehicles to bridge the gap between the high-tech hubs and the rest of the United States. Obstacles to broader AV deployment and how to overcome them will be addressed in a forthcoming paper.

Joint Center for Political and Economic Studies: Racial Differences on the Future of Work

Technological innovations are rapidly changing the American workplace. As robots and computers streamline the production process, many American workers are discovering new ways to be more productive. They are also finding that technological innovations are creating new opportunities for advancement within the workplace. However, despite increasing productivity and workplace opportunities, technological efficiencies have displaced American workers or have required American workers to develop new skills.

In addition to those changes in the workplace, people of color are estimated to become the majority of the United States population by sometime between 2040 and 2050. Therefore, the perspectives of people of color today about technology, job-readiness, employability, the acquisition of skills, benefits, and education for children are even more critical to understanding the future of work.

These perceptions by people of color are important in developing solutions to ensure that Americans from all backgrounds are prepared to participate in the economy in the future and that the U.S. economy remains competitive. For example, if children of color are currently becoming the majority of children in the United States, policymakers should pay attention to data that shows significant populations of African Americans, Asian Americans, and Latinos believe schools should teach computer programming. Current workforce trends—such as a large number of Latinos who report shifting from salaried to hourly work or having an interest in a GED or community college— can affect Latino workers, their children, and all of us who may depend on the productivity and tax dollars of those workers and their children over the next 50 to 75 years.

Considering racial perceptions about the future of work is also essential in addressing longstanding challenges that have plagued America since its founding and ensuring that well-intentioned proposals do not exacerbate existing disparities over the next 50 to 75 years. For example, policymakers and employers designing tuition-assistance programs should know that significant racial disparities may emerge among employees who take advantage of those programs once employees are required to spend more than $500 of their own money on training.

In this report, the Joint Center seeks to better understand how different racial groups perceive the changing nature of work. We commissioned and analyzed a nationally representative survey of 1115 Whites and nationally representative oversamples of 667 Blacks, 619 Latinos, and 611 Asian Americans. The sample was re-weighted to a 2000-person sample with 500 interviewees from each racial group. The survey, which was conducted by Nielsen Scarborough, seeks to understand differences and similarities across these different communities in perceptions regarding changes in the workplace, the effect of technology on work, job security and other workplace benefits, training to acquire new skills, and preparing children for a changing economy.

Securing America’s Future Energy: America’s Workforce and the Self-Driving Future

As the U.S. stands on the precipice of a transportation technology revolution, now is the time to explore both the benefits and impacts of AVs on the economy, consumers and the workforce. Will AV technology result in labor displacement? What will be the magnitude of these impacts? How can we measure the economic benefits, and what can be done now to maximize these gains while mitigating dislocations?

SAFE’s report, developed in collaboration with leading transportation and labor economists, examines some of the most important questions that have been raised as AVs move from concept to reality.


Download Report


Future of Work: Truckers on the Road to Automation

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.

Heavy-Duty Innovation: Energy, Automation, and Technology in the Trucking Sector

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.

Automated trucking’s rapid rise overlooks the need for skilled labor

by Joseph Kane and Adie Tomer, from

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.