Many have heard the rumblings that the 4th industrial revolution is upon us. Automation is spreading across industries from finance, to transportation, to healthcare and beyond. It appears no industry is off limits to the power of automation. It seems inevitable that machines will one day replace all human workers. After all, they will one day be able to do everything we can do and better, right? Well, not necessarily. Despite what the latest sci-fi film has told you, in many roles’ humans run circles around machines. Figuring out what work humans are good at (or perhaps what work is good for humans) remains an open challenge.
Amid change, history suggests a few constants. One, automation is winning: in aggregate and at scale. Two, people are exceptional. We are diverse, immensely adaptable, and extraordinary in mundane and grand ways. I’m a recent transplant to the greater Boston area, and I am constantly struck by how bad traffic gets at rush hour. On the road leading away from our office, wait times at the traffic light can exceed 20 minutes on a late weekday afternoon. That light got me thinking. In the Midwest where I grew up, driving was a necessity and a rite of passage for teenagers. Most of the routes I drove were punctuated by four-way-stop intersections. When you saw a traffic light, it meant you were in town. I now realize that town’s traffic light and all of the other ones on our roads were one of our first steps towards an automated future.
I take pride in the fact that traffic lights were a Midwest invention, a simple piece of automation formed in response to the chaos created with the rise of the automobile. Cars were bigger and faster than horses or bicycles or pedestrians, and it was hard and hazardous for this mix of parties to navigate through the limited real estate of an intersection. The introduction of the first automatic traffic signal in 1914 imposed order on this chaos, improved safety, and spread from concept to necessity in every major American city in under 15 years. A century of research and development has made traffic lights better, of course. Intersections now have sensors that monitor traffic, control systems and algorithms that adjust timing with demand, intervention systems that give priority to emergency vehicles, and even networked means to coordinate with other traffic signals.
So, it might come as a surprise that on the really busy afternoons, the Cambridge police department sends a traffic officer to our automated intersection. Compared to today’s most sophisticated, sensor-riddled, algorithm-driven traffic light, a good traffic officer sometimes delivers superior results because he or she has a better sense of context, a human touch for motivating drivers, and a more innate understanding of overall traffic flows in the city.
However, deploying human traffic officers to take over the automated duty of traffic lights at every rush hour everywhere is impossible. Furthermore, when traffic is regular and evenly distributed, or when the human traffic director isn’t highly skilled, even a simple four-way stop wins out. If you are skeptical about that, I recommend watching a humorous but convincing demonstration of this performance principle in a 2014 episode of MythBusters.
Today traffic lights are a natural part of our landscape, but they haven’t always been. It took time for human drivers to adapt to the traffic light. When they were first introduced, motorists ignored them in selfish attempts to cut down their individual travel time. Indeed, a prescient Cleveland teacher introduced the game “Red Light, Green Light” to teach the youngest generation how to cooperate with this new automation and grow towards a safer, more collectivist driving environment.
It seems so simple — a three color switched light to get city traffic moving smoothly — but it really is monstrously complex. The needs and impatience of any given driver must be balanced with the good of the city as a whole. With perfect knowledge of car positions and destinations, it is possible to compute optimal traffic-signal timing for a single intersection. However, as soon as you are dealing with multiple intersections finding the traffic light timing that best balances waiting for any given car while maximizing citywide throughput becomes computationally intractable — it is what a computer scientist would call a deterministic, exponential time-complete problem. Even so, researchers have managed to come up with clever signal-timing algorithms to approximate an ideal, balanced solution and they theorize that a truly smart urban system of traffic lights could improve throughput by 20% by combining information from the traffic of one intersection locally with citywide.
As a technologist, it’s tempting to focus on advancing automation and algorithms as powerful tools to tackle tough problems like traffic. It takes some creativity and reflection to realize that the most powerful means to improve intersection performance approach the same throughput problem from entirely different angles and can blow away even the smartest algorithm. Carpooling, bicycling, and walking provide an immediate integer-factor throughput increase. Roundabouts are superior in many scenarios, especially in coupled networks. Perhaps the best solution of all is to eliminate the contested terrain of the intersection entirely, with the magnificent if expensive cloverleaf interchange. These ideas are all driven by insight — by viewing the problem from another direction, and human ingenuity.
In the decades that come, our relationship with automation will evolve, and humanity will adapt rapidly, within and across generations. We will see new and powerful algorithms emerge and a rapid adoption of new forms of automation. However, much like the engineer — James Hoge — behind the original traffic light, exceptional and clever entrepreneurs will continue to innovate and find ways to make the intersection even more efficient. But my bet is that in 20 years there still will be a handful of talented traffic officers who will stand at these crossroads exceptionally orchestrating traffic like no machine ever could.