Says the human. To a computer driving is much more difficult than flying.
You could equally say adding up big numbers is much harder for you than walking across the street. To a computer the former is trivial, the latter no walking robot has yet done.
As I've mentioned elsewhere, I'm directly involved in the test and evaluation of one of the current attempts at "sense and avoid" technology. It is a long way from being safe for fully autonomous use. It is my understanding that the DARPA autonomous land vehicle contest required autonomous collision avoidance, and that more than one of the entrants did so effectively. Their budgets were a pittance compared to what is being spent on "sense and avoid" for UAVs, and yet they had much greater success. That tells me that urban traffic avoidance is easier for computers than air traffic avoidance.
I think that two big reasons for this are probably:
1: For land vehicles, simply stopping in place is almost always an effective collision avoidance tactic (unless the other vehicle is deliberately seeking a collision). This simple solution is not available to airplanes.
2: Tracking objects thar are moving in three dimensions with a sensor that is also moving in three dimensions is an immensely more complex problem than tracking objects that are constrained to move on a fixed surface in two dimensions with a sensor that is also constrained to move on a fixed surface in two dimensions.
Circular reasoning? They solved the land-nav problem because its easier. Its easier because they solved it.
My point was, there is another wrinkle. The land-nav problem was opened up, made a competition with a big marketing budget. It was also intractable, unsolved, too hard. Until lots of smart people started brainstorming and trying crazy things and cooperating.
Airplanes can change speed drastically, which is at high speeds about as effective as stopping. And no, you don't get to say collisions are hard to avoid because 3 dimensions are hard to calculate, making that not a solution.
I think I begin to see why the problem hasn't been solved yet.
It's not circular reasoning: it's a conclusion based on observation. Several groups tried to solve each problem. All of the groups that tried to solve problem A have thus far failed (although some have made measurable progress) while some of the groups that tried to solve problem B succeeded despite having considerably less resources at their disposal. "Hard to solve" can be a somewhat difficult label to define, but those results are a strong indicator that problem A is harder to solve.
By your logic, every "impossible" problem could be solved easily if just DARPA would offer a small prize to whoever solves it. Unfortunately, the real world doesn't work that way. There's a reason why DARPA chooses the tasks they do for their challenges: they spend a lot of time and effort identifying tasks that are highly likely to be amenable to novel solutions.
>Airplanes can change speed drastically, which is at high speeds about as effective as stopping.
Incorrect, on two counts. First, not all airplanes can change speed "drastically." Second, it is not as effective at preventing a collision as stopping. If both cars in an impending collision stop (and in many cases, even if only one of them stops), a collision becomes impossible. On the other hand, there are a lot of situations where deceleration merely delays, but does not prevent collision. That has value, but it's not as good.
>And no, you don't get to say collisions are hard to avoid because 3 dimensions are hard to calculate, making that not a solution.
I never said it was "not a solution," but I definitely do get to say that it's a much harder problem to solve. Here's the steps you have to perform to avoid a collision:
1: Detect an object.
2: Track the object to determine it's course and speed.
3: Compare the object's course and speed to yours to determine how likely a collision is.
4: If the probability of a collision is unacceptably high, determine a change of course and/or speed which will reduce the probability of collision to an acceptable level. If the probability of collision is already acceptably low, return to step 2.
5: Maneuver to change course and speed accordingly, then return to step 2.
If you are moving in three dimensions and the objects with which you might collide are moving in three dimensions, step 2 is hard to do accurately. (Unless you've studied radar tracking, you probably don't appreciate exactly how hard, but if you're genuinely interested, Skolnik's Radar Handbook is a good place to start.) The less accurate you are at step 2, the harder steps 3, 4, and 5 become, because you have to deal with more uncertainty. Is that really where the other object is? Is that really where it will be in twenty seconds? How certain are you of that? How certain are you that there really is something even there at all? If you're wrong in one direction, you'll have a midair; if you're wrong in the other direction, you'll perform some extreme maneuver for absolutely no good reason.
I've seen government contracting many times before. You put out rfp's, a whole bunch of second rate people reply, you pick the ones who "look" most competent. Then, surprise, surprise, it fails. This is not how hard things get done. Those most able at securing grants are almost certainly not those most able at delivering technical success.
