Hello everyone!
If you write devlogs regularly irregularly, that’s still a form of regularity, right? 🙂
Okay. What is definitely not irregular is the steady development of Empluna.
And to bring you right up to speed: In June we want to release the demo for the next Steam Next Fest!
Hurray! 🎉
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Contentwise, we already have more than enough for a solid demo.
But on the technical side we still need to rework and optimize a few things, some of it mandatory, some simply because we want it to be better.
The last two weeks were all about the NPC population.
Our old, fully custom-built system did work, but it was difficult to maintain and hard to adapt to future engine versions.
On top of that, we wanted better performance.
So we threw out the entire rendering logic and replaced it with a new system that’s much closer to the engine and far better at parallelizing work.
The result:
Since yesterday the new system is up and running and delivers very good performance in stress tests with 40,000 NPCs. (Hardware dependent, of course, but that was the goal)
Here’s a little impression in front of the main station:
(Characters and behavior emulated for the stress test. Balancing comes later.)
We did the same for the wildlife, by the way: Initially with bears, beavers, wild boars, buffalo, capybaras, deer, roe deer, eagles, seagulls, foxes, geese, rats, and squirrels.
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Procedural Intersections
Up until now, intersections in the road system are placed and connected manually, with some convenience features, but still fairly time-consuming.
The plan is that roads will automatically generate intersections as soon as they overlap.
This should make the system much more intuitive.
More on that once we’ve worked on it further.
For the demo we already have a few ideas on how to get you into Empluna as quickly as possible, without requiring much prior knowledge.
More details will come once the mode takes clearer shape.
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Do you have ideas or wishes, maybe for the road system or something you think absolutely needs to be in the demo?
Let us know! See you next time! 👋