It is an interesting conjunction of events today: reading an article on sum-of-squares problems for optimal solution finding and reading an article about an indecisive car. It makes me think about what sort of algorithms, efficient or not, advanced or not, are being used in the technology to which we entrust our lives.
"Why Do They Keep Doing It?" Tesla On Autopilot Crashes Into Parked Laguna Beach Cop Car references multiple automated car accidents. One in particular is interesting:
Yesterday, video was posted showing what is allegedly a Tesla in Autopilot mode having a bout of "confusion" when the road being traveled changes from a straight road past a section on a highway that offers an exit by the road dividing. The video appears to show the car unable to determine which lane to stay in and nearly hitting the center median that divides the roadway from the exit.
In reading about minimizing polynomials in A Classical Math Problem Gets Pulled Into the Modern World, the author uses an example of an autonomous car and how it must make decisions for obstacle avoidance. The article implies that the algorithm referenced might be of value to autonomous vehicle programmers, drones, or, .. whatever.
But more strongly, the article does make a strong point that autonomous vehicles and drones are in 'continuous collision avoidance' mode, and that the solutions vary dynamically and quickly depending upon input quantity and variation. Everything works together: obstacle detection, identification, classification, and avoidance all work together. Not to mention the other parameters such as location awareness, resolution, and destination requirements, amongst others. Algorithmic decision making becomes a difficult problem to solve.
And if a vehicle becomes indecisive, what happens if the three laws of robotics get mixed in?