With its steep hills, narrow alleys and twisting roads that lead into harrowing five-way intersections, the street layout of Pittsburgh, Pennsylvania, is a car-insurer’s nightmare. For innovators trying to develop self-driving vehicles, however, such conditions are irresistible.

Walk through the city’s Strip district shortly before dusk, and you will behold a steady stream of self-driving Audis, Fords and other cars, rigged up with sensors on their rooftops. All are doing their best to blend into traffic.

Not only have the testing teams come to Pittsburgh, top-tier startups are putting down roots here, too. California giants such as Tesla, Google and Uber remain the best-known players in autonomous driving, but this year's LinkedIn Top Startups list shows a wider geographic spread. Four self-driving startups make the list, including two anchored in Pittsburgh. One is Argo AI; the other is Aurora Innovation. Both were founded in late 2016.

Why Pittsburgh?

In the 1980s, Pittsburgh embodied the decline of America’s Rust Belt. Most of the city’s once-famous steel mills were shuttered and disbanded. Unemployment ranged as high as 17.1% and the city’s population shrank dramatically. Today, with 305,000 residents within city limits, Pittsburgh is the 63rd largest city in the United States, less than half its size in 1950. In the past 20 years, however, Pittsburgh has quietly remade itself into a white-collar talent magnet, with the research hubs, cultural delights and manageable housing costs that startups cherish.

At Pittsburgh’s Carnegie Mellon University, researchers have been probing the intersection of robotics, artificial intelligence and autonomous driving for decades, going back to a primitive effort to build the first self-driving car in 1984. (Timid to a fault, the machine’s top speed was a few centimeters a second.) Carnegie Mellon now has a bevy of research teams that focus on self-driving technology, with as many as 100 graduate students a year exploring such work. “We want to be the leading place in this space,” says faculty member Raj Rajkumar, who leads Carnegie Mellon’s autonomous-driving initiatives.

Over the years, as Pittsburgh bottomed out, cheap real estate and other factors started attracting artists and artisans, whose creations help make the city alluring to in-demand engineers. “We have outdoor activities that are as good as Boulder, Colorado, and a craft-beer scene that’s as good as Asheville, North Carolina,” says city booster Sean Luther, head of InnovatePGH, a city/private-sector alliance. “We have more restaurants recognized as semifinalists for James Beard culinary excellence awards than any other Tier 2 city.”

Tech-sector recruits may be skeptical at first, but often are won over. Lee Morris, a cloud-computing specialist, had been working for years in Manhattan before Argo approached him in late 2017 about moving to Pittsburgh. On a house-hunting trip, he and his wife decided that parts of Pittsburgh reminded them of New York City’s eclectic Williamsburg neighborhood. It didn’t hurt that $450,000 could buy them a 3,400-square-foot home in Pittsburgh. A New York apartment less than half that size might cost $1.2 million or more.

For economic development experts in growth-challenged cities, the dream of copying — or surpassing — Pittsburgh’s success is endlessly enticing. Last year, the Brookings Institution published a 74-page analysis of Pittsburgh’s approach to innovation. Brookings analysts applauded Pittsburgh universities’ intense R&D spending, which, on a per-capita basis, is nearly as high as Boston’s and ahead of Seattle’s. (Nashville and Raleigh are close.) Overall, according to Brookings, “Pittsburgh is among several dozen global cities that have the institutions, innovative capacity and core science and technology competencies to compete for leadership in some of these next-generation technologies.”

A heavy commitment to academic R&D isn’t enough, the Brookings experts cautioned. Healthy startup ecosystems also are nourished by abundant venture funding, flexible workspaces, and strong ties to large companies that can become first customers. It also helps to have a growing metro-area population and prominent global recognition as a hub for startup talent. While Pittsburgh is putting many key elements in place, it isn’t there yet. Future success is plausible but not guaranteed, Brookings wrote.

Pittsburgh’s slow, stubborn efforts to become a startup haven can be seen in the career journeys of Argo chief executive Bryan Salesky and Aurora CEO Chris Urmson. The two men are rivals today, but they have repeatedly worked together in previous jobs — and still chat on the phone once a month or so about non-competitive topics.

In 2007, Urmson served as Carnegie Mellon's technical director in a bid to create the first self-driving car that could handle 60 miles of urban traffic, while Salesky directed the project’s software. “We went to war together,” Salesky recalls. “It was the most magical time in my life.” The challenge was hosted by the U.S. Defense Department’s advanced-research agency, which initially tapped Carnegie Mellon as the fifth seed, behind the likes of Stanford and M.I.T. After weeks of secret preparations in the California desert, the Carnegie Mellon crew dominated the ultimate six-hour test, beating all comers.

To commercialize this new technology, Urmson headed west in 2009 to join Google’s self-driving car business in California — and Salesky followed a few years later. The work was exciting, but living in Silicon Valley “just wasn’t affordable,” Salesky recalls. What’s more, he says, “most of my family is in the Detroit and Pittsburgh area. I wanted to be closer to them.”

So, when the idea of Argo began to take shape, Salesky and his co-founders decided to give Pittsburgh a try. Today, Argo has 350 employees, and $1 billion in backing from Ford Motor. Ford owns a majority stake in Argo but holds only two of the company’s five board seats. In a sign of how briskly Argo has been snapping up talent from its larger rivals, LinkedIn data shows that 22 of Argo’s employees — including Salesky — previously worked at Google.

Aurora, with 160 employees, has plucked talent from big-name rivals just as boldly. One co-founder Sterling Anderson, came from Tesla, where he was director of autopilot programs. Another, chief technology officer Drew Bagnell, is an Uber alumnus. (Aurora’s board of directors includes Reid Hoffman, a co-founder of LinkedIn.) CEO Urmson has chosen to stay in California, but the company operates with co-equal headquarters in Palo Alto, Calif., Pittsburgh and San Francisco. The Pittsburgh operations are growing so rapidly that just a few months after moving into bigger facilities, Aurora is looking for extra space to house its car fleet.

City driving accounts for only a modest share of the 3 trillion miles driven each year, but it’s grossly overrepresented in the number of accidents that take place during that time. Cars can bump into bikes; a van speeding through a red light can smash into another vehicle; cars can even clip a construction worker who unexpectedly rises from a manhole cover. There are “literally thousands of things that can go wrong” in an intersection, Argo’s Salesky notes. The key to self-driving success involves mastering a chaotic city — and Pittsburgh presents a lot of chaotic opportunities.

Aurora’s CTO, Drew Bagnell, has a 20-year academic background in machine learning. In an interview, he pointed out that in some situations, machine learning is the only way to solve a problem. When traditional engineering or machine learning both might work, Bagnell is encouraging his Aurora colleagues to “choose the right tool for the job.”

One of the challenges that Aurora confronts is the notorious “Pittsburgh left.” This maneuver — often encountered at Pittsburgh intersections — involves a sudden, hasty left turn in the face of oncoming traffic, the moment a traffic light turns from red to green. “You don’t see this in California,” Bagnell dryly notes. In Pittsburgh, however, drivers looking to make a left turn use it all the time. Motorists intending to go straight in the oncoming lane have learned to enter the intersection slowly, so the first left-turner can slip through without creating a crash.

Aurora is working in partnership with Germany’s Volkswagen AG, South Korea’s Hyundai Motor Co. and China’s Byton. With that wide a global reach, Aurora executives and engineers are highly attuned to regional variations in what’s considered good driving. Even so, Bagnell says, “Our goal is to build a single system for use throughout the world. We aren’t building n driving systems for n partners.”

Bloomberg News recently reported that Volkswagen had sought to buy Aurora but was turned down. Bagnell won’t comment directly on that report, but says Aurora evaluates all its business relationships on the basis of what will best foster the company’s mission of “bringing the benefits of self-driving as safely, quickly and broadly as possible. At this moment in time, we intend to be independent.”

Uber, which had been testing self-driving on Pittsburgh streets, pulled them off public roads after an Uber autonomous vehicle in Arizona hit and killed a pedestrian in May. Public opinion polls show that the Arizona crash, and other self-driving collisions, have led to heightened public anxiety about the mass introduction of such cars.

Even so, Bagnell contends that self-driving cars have the potential to be vastly safer than today’s human-operated vehicles. As autonomous vehicle advocates note, software-based systems don’t fall asleep at the wheel; they also don’t succumb to road rage or drunk driving. “It would be a tragic mistake if we allowed rare errors to lead to the continuing loss of life that we have now,” Bagnell argues.

(Aurora founders Sterling Anderson, Chris Urmstad and Drew Bagnell)

Argo is determined to solve all the city challenges, too. Its approach starts with the usual triad of sensing technologies mounted to each self-driving car. Video cameras pointing in all directions provide high-resolution images at 30 frames a second. Radar devices, mounted lower on the car, help the car “see” vehicles and people that might be obscured by signs, shrubs or trees. A light-based variant of radar, called Lidar, provides extra help with depth perception and nighttime vision.

Inside each of Argo’s vehicles, an array of computers performs billions of calculations a second, turning data into knowledge. Argo software categorizes images into known items such as “pedestrians,” “parked cars,” and “moving vehicles.” Other software steers the car along a pre-set route, adjusting if other cars crowd a road’s center line or if jaywalkers enter the roadway unexpectedly. During current testing, two human operators sit in each car. One operator is ready to take control of the car right away if the self-driving systems need help; the other takes notes on everything “interesting” that warrants further review after the run is done.

It could take a decade or more until self-driving cars can handle every possible scenario, experts say. But Ford (and Argo) have committed to having some form of autonomous driving available for consumers in 2021. To meet that goal, Argo’s engineers are building perception and prediction systems into autonomous driving via a variety of methods.

Good predictive systems help make for smoother, more naturalistic driving, says Peter Carr, an Argo senior staff engineer. When humans (or software) think about the way a situation might unfold, Carr explains, “you’re getting yourself into a good place where you don’t have to make sudden reactions. You realize that the car in front of you probably will be slowing down soon, and you can start to give yourself more space, instead of just slamming on the brakes.”

Argo CEO Salesky is especially intrigued by the idea that machine learning can help autonomous cars identify pedestrians most likely to enter a crosswalk before they start moving. It’s anyone’s guess what mix of eye movement, tiny shoulder rolls or the like might be associated with an “intent to cross.” With machine learning, software engineers don’t need to write the rules themselves.

What all these companies need is the raw engineering talent to develop smarter cars and the data that comes from many hours of driving in snow, handling hills and bridges, maneuvering through traffic, and cohabitating all the while with bikers and walkers. Mastering all these challenges could mean the sunset of human driving — and maybe even the Pittsburgh Left.