The Reports of My Death Are Greatly Exaggerated

So the problem with this blog thing is that if I go radio silent for a few daysweeks you all think I’ve been abducted by aliens.  Let me first set the record straight:

• I have not been abducted by aliens.
• Austin has not been abducted by aliens.
• Chris was abducted by aliens, and they may have done some experiments, but he seems about the same as before, so we’re not worrying about it.

So what I have been up to?  Well, first, LR closed down the Westborough office and relocated scenery development to Grafton, MA.  Here’s the new home office, ready for action:

As you can see, the move was orderly and the new office is spacious and uncluttered.

(This post is going to get really nerdy really fast – a lot of what goes into X-Plane isn’t easily observable – a lot of the work I do is engineering that goes in under the hood.  It’s a long post, but coffee will help!)

Besides reassembling my office I have been working on global scenery DSF creation.  In particular, I’ve been trying to kill off the remaining “wicked” problems – that is, the parts of DSF generation that require first-of-their-kind algorithms.

(More technically, a design problem is “wicked” if the only way to learn enough about the problem to solve it is to go through the act of solving it.  This chicken-and-egg problem is usually broken by trying to solve the problem multiple times – the first few times are “learning experiences” – that is to say, the first version of the code often has to be thrown out.)

Stuffing Your Luggage

Most of the problems with global scenery generation turn out to be “knapsack” problems.  The knapsack problem is basically this: let’s say you have one suitcase (or knapsack) and you want to fill it as much as possible with your clothes.  All of your clothing are of different sizes.  What subset of clothing do you take that leaves the minimum wasted space?

Well, it turns out that if you want the best fit, with the minimum wasted space, the only way to answer that question is to try every combination of your clothing.  Yep.  You have to pack and unpack your suitcase approximately a gajllion times and just try every packing to see which one is best.

This matters to computer programmers because often we have to “stuff” a space as optimally as possible (or find some optimal combination within a set of combinations); what we learn from the knapsack problem is that the only way to find the truly optimal solution is to try them all.  The problem is that when you have a lot of things to try packing, it takes too long (even for a fast computer) to try every combination.

Just Shove The Biggest Things In First

I’ve put “best” and “minimum” in bold above because they are key to defining knapsack problems.  If you have to have the truly best fit, you have to try packing your suitcase or knapsack with all combinations of clothing.  But if a “pretty good” fit is okay, you can do something a lot faster.  You pick a heuristic (that is, a rule of thumb) and hope it works out well.

Let’s take a look at packing in action.  When you load an airplane, X-Plane packs all of the tiny instrument overlay textures into a few big textures to optimize frame-rate.  (This is called “texture atlasing” – authors have to do this by hand for scenery.)  Packing small textures into a big texture is a knapsack problem – to find the truly optimal packing we’d have to try every combination of instruments in each texture.  That would be very slow, so X-Plane instead uses a simple rule: we pack the biggest things in first, building rows.  As you can see from these pictures, the packing isn’t very good – a human could do a lot better.  But the packing isn’t bad, and it’s fast enough (a perfect solution would take days to run for each airplane load).

Pretty Heuristics

When we have a knapsack problem, and our solution is a heuristic (that is, rather than find the most optimal solution, we’ll find a pretty good solution) there is another question: are the particular kinds of solutions that we come up with nice looking?  Do we like them?  For panel textures, this is a non-issue; the user never sees the “pack” of the panel texture while flying.

But for global scenery, the look of our heuristics matter.  Global scenery generation is riddled with problems where the ideal setup of data would be too slow to compute, so we want our approximation to look “good”.

Here’s an example from global scenery of a knapsack problem where the look of the heuristic solution matters.  The map on the left is the OSM vector data for San Francisco.  The map on the right shows the same region broken into terrain zones.  Calculating terrain zones is a knapsack problem with a heuristic solution where the look matters.  Let’s break that down and see what that means.

First: what is a terrain zone?  A terrain zone is a set of adjacent city blocks in a DSF that all have the same base terrain.  If you recall Austin’s rantdescription of the way cities are created in version 10, he said some stuff about starting with grass and building cities on top of them.  Well, it turns out that if you build every block up on the same grass, you get something that starts to look like a mini-golf course.

We have a lot of ways to cope with that, but one of them is terrain zones: several city blocks are grouped together with one base terrain – but then, at a road boundary, we change to a different base terrain to “break up” the landscape along road boundaries.  The look is a lot less monotone in the far view – at least we think; the picture on the left is San Diego (terrain only) with the urban terrain zones set to primary colors for easy examination.  (When the real artwork is in place, the terrain will be similar and color, with roads dividing the various zones.)

The packing problem is: which blocks get grouped together, and which are kept separate?  Some groupings produce a more efficient final mesh, which results in better framerates.  Like the knapsack problem, it would take too long to find the best grouping for framerate, so instead we try to come up with a pretty good grouping.

If you look at the groupings the above maps and diagram, you’ll see there is sometimes a “tooth” pattern where the boundary beteween blocks jumps up and back.  That’s not so good looking; the algorithm that produces the groupings sometimes picks ugly block combinations, and we can’t just tell it “don’t do that” because it doesn’t check every combination to find the best one.

What Have We Learned?

Putting it together, you can see why global scenery generation is tricky.

• We want to combine city blocks to make moderate sized areas of similar terrain, preferably in clumps that look nice.
• We can’t just try every combination of block groupings; that would be too slow (it’s a knapsack problem).
• Instead we have a heuristic – a simple strategy to try that produces “pretty good results”.
• That strategy is tricky to develop because it has to come close to optimal results (for fps) and we don’t want the groups of blocks to look silly (which is hard to quantify).
• Therefore, calculating the terrain zones is a “wicked” problem – only by implementing a heuristic do we get to see how it “looks” and decide if it is acceptable.
• My office looks like a bomb went off.

About Ben Supnik

Ben is a software engineer who works on X-Plane; he spends most of his days drinking coffee and swearing at the computer -- sometimes at the same time.

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