Huge procedurally generated subway transit map

Question

How could I generate a single transit map image , which is not based on any real map, on a massive scale? Are there algorithms or tools which could do something like this already?

Unlike conventional maps, transit maps are usually not geographically accurate—instead they use straight lines and fixed angles, and often illustrate a fixed distance between stations, compressing those in the outer area of the system and expanding those close to the center.

The scale I'm looking for is earth-like. If a line ran horizontally across it could have 40,075 stations kind of map. Ideally, It should also wrap around, like on a sphere.

I want it to look just like any local transit map (I'm basing myself on the Montreal metro map) which means I don't care about what a metro system of this scale should look like or how useless this would be.

So far, the research

• Nathan Hellinga's Processing.py subway map generator resembles what I'm looking for and looks great but the algorithm wouldn't scale well to a very large grid.

• Jannis Redmann's generating transit map theory is really interesting but bases itself on real world data. Maybe it could be used with generated data but how do you generate that data then?

• Fractal generators! But how do I make it look like a transit map?

• With Graphviz, I would still need an algorithm to generate data.

• Slime is a really interesting idea! But how do you procedurally generate that?

• Wave function collapse algorithm!!

• Generating a random heightmap, making a graph out of it, and then making it pretty

• My idea, a random walker. You all know what this is, I just don't think that's the best option there is.

Answer 1

If the end goal is creating an algorithm which will give you a data structure roughly representing a transit map, perhaps controllable via parameters to like branching vs linearity, sprawl, number of lines, frequency of inter-line transfer stations, etc, I would begin by creating a mental model of what exactly is represented by a transit map, which I have hinted at already with some of the aforementioned parameters.

In terms of actual implementation of this model, I think a transit map can be most easily implemented as a tree, graph, or other network of linked elements.

To test the suitability of your own mental model I would recommend taking an existing real world transit map and trying to manually encode it in your proposed data structure to see if it fits well. You could even do this translation of real world transit map into data representation on paper or on a whiteboard. Tweak the model as needed.

At this point, having tested the viability of your data model, you should implement the actual generation algorithm. Keep the algorithm simple at first and expand the parameters and behavior after you can generate a basic proof of concept example transit map data.

After tweaking this generation algorithm you should have some suitable representation in data of a transit map which you can render in your engine/environment of your choice and figure out how users can best interact with it in a way that satisfies your requirements.

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Overall this is a vague, procedure focused answer because the question itself has no specific code snippets or implementation details and as such I cannot comment concretely on any of these approaches. I think conceptually you have a firm grasp of the subject area and should try creating a prototype at this point. If it fails you can always go back to the drawing board and do more research, but I think you need to beware paralysis by analysis.