Watch this clip of a traffic intersection.
As you were watching it, what did you think was going to happen?
When I first saw this clip, it reminded me of the T-bone accident I was in as a child. I don’t really remember much around the way it happened, or what I was doing when it happened, but as a child, I flew right into the windshield of our car.
It happened when we were on our way home from the airport after picking up my mom. She had just returned after visiting family in Korea. Someone ran a stop sign and boom. Just like that, my hopes of ever becoming a doctor or rocket scientist flew right out the window…or should I stay straight into the window?
Alright, so back to the traffic intersection.
This is a video from a computer simulation that the Autonomous Intersection Management project at the University of Texas at Austin was conducting. When Peter Stone, the professor heading up this project, discovered that “25 percent of accidents and 33 percent of the thirty-three thousand auto deaths each year in America occur at intersections, and 95 percent are attributable to ‘human error,’” he and his team wanted to do something about it.
But how is this chaos better? Doesn’t this seem like a T-Bone accident just waiting to happen, rather than a way to prevent it from happening?
The interesting thing about this simulation is that every car you see here is being driven autonomously. In other words, they’re all self-driving cars.
This being the case, you can actually plot the trajectories of each car long before they arrive at the intersection, which means there’s no need for the typical breaking, stopping, and accelerating that normally characterizes four way intersections. This also means that you can get rid of traffic lights and stop signs, since every self-driving car would be communicating, sensing, and noticing the other.
To self-driving cars full of sensors and cameras, this simulation makes complete sense. To us, it doesn’t—it seems like utter chaos.
And here’s the reason.
It’s because of a thing called, “mental models.”
[Read more…] about Adaptive Decision Making, Change, and Leadership – Part 1
