Parallel Parking and possibly Instrumental Convergence — LessWrong

I was taught two different ways to parallel park. I am sure there are more than just two methods. This strikes me as odd since it’s a very common part of driving. Nevertheless, 
I hate parallel parking and it was a constant source of anxiety when learning to drive. Apparently I’m not alone in this:

Over half (57%) of car owners surveyed report feeling stressed or anxious about parallel parking, with women and younger drivers reporting higher levels of anxiety.

Instrumental Convergence hypothesizes that sufficiently intelligent agents with similar to the same sub-goals will converge on those methods or instruments of achieving that. Parking your car parallel to the curb would appear to be one of those. Yet the methods it is done, and the methods of teaching it remain diverse despite possibly a century of hundreds of millions of drivers doing it. With such brute-force exploration strategies why have car drivers as a collective not converged on a single stress-free way to parallel park?

We can observe in nature convergent evolution. And there are many cases of multiple discovery: Both Leibniz and Newton independently arrived at Calculus is a common, but potentially controversial example of multiple independent discovery. 

I have long been under impression that as a domain matures, through a combination of Mathew Effects and adopting the easier or better solution – they converge. Academy Award winner Walter Murch noted that in the early days of the car they didn’t all have steering wheels, there were many different approaches to steering, braking, and acceleration until the “UI” eventually converged on three or two pedals, and a steering wheel. He made the analogy that NLE suites had converged on a single UI. Whether they converge on the best method or best UI or not is not as important as they converge on a single thing- much modern technology uses roads and wheels. A.I. research is almost certainly not at the point of convergence yet, there’s still a lot of exciting techniques and methods to discover.

In microcosm learning is often the same for an individual as a whole discipline, you try out a whole lot of different approaches to something until you hit upon techniques that provide consistently acceptable results. When I was learning parallel parking I struggled to find different means of representing space, looking for different markers, turning the wheel to different degrees. And I assume through sheer trial and error I accidentally hit upon something which was more consistent.
Ya know,