YHK - yet another hacker news clone

One difference from the OpenAP/scikit-decide setup: my router doesn't search a fixed grid with A*. It runs a continuous isochrone search that expands a fan of headings against the live forecast each step. That's closer to how routing is actually done for this problem, and it's what both the live product and the backtest above use.

But why would you want to use AI to control planes?

Aviation is one of the few industries where the largest regular (non-capital) expense is something other than labour, namely fuel. Anything that reduces fuel costs even a little is of obvious interest to every airline.

There are still the issues of coordinating flight paths to avoid collisions, and regulation (including international regulation). The former seems like a technical problem amenable to increasingly accurate approximations over time. I don't know about the latter, but I doubt it's as insurmountable as you imply. International air travel has been around longer than ILP solvers, meaning that at some point flight schedules were created by people. Now they're created by ILP solvers, and the regulatory environment successfully adapted to that change.

During the day they have a cooling effect by reflecting/blocking some light.

The optimal is not to eliminate them entirely, but to create them only early in the day so that they dissipate by sunset.

It seems like there should be a solution to this though, either battery-electric or fuel-cell auxiliary thrust for ground operations and taxiing, or utilising tractors more to do the full aircraft ground movement, not just pushing back from the gate. Unfortunately it's impossible to suggest such changes without getting a horde of aviation nerds thinking of reasons to tell you why something isn't possible, instead of imagining how it _could_ be possible.

So it's exciting to see companies like Heart Aerospace innovating in this area.

Also worth noting, tangentially, though - the reason planes are fueled as they are is because if you run out of fuel in a car, you're just stranded. In an airplane, you're quite possibly dead. If you only load the plane with exactly as much fuel as it needs to get to its destination, you run the risk of not having enough to safely divert.

On the other hand, planes also have maximum landing weights, so a plane which must divert or land in an emergency often has to dump fuel for a while first. That's more unusual and not something you can easily plan for, but it's part of the problem too.

The truth is that given the legal and ethical constraints available, routing is already relatively well-optimized in many places. (There are some places, like China's hybrid civilian-military airspace, where those constraints are extremely nasty and basically make the problem impossible to solve better than it is.)

Aviation tries to solve the fuel consumption problem by designing planes to use less fuel, rather than by flying more optimal routes. There is a massive effort in aviation pretty much all the time to try to use less fuel, for every reason from cost to environmental impact to the relative accessibility of jet fuel now and into the future. It's the reason engines have gotten physically larger; it's a big part of why we don't use supersonic jets anymore as well.

The efforts have been pretty sucessful: https://theicct.org/maximizing-aircraft-fuel-efficiency-desi...

There's no hubris in identifying a problem, and fairly little in thinking you might be able to help solve it, but there's a good bit in imagining nobody else has done it.

(Also, Scikit-decide seems to be on the Github account of Airbus, so I assume they have at least some basic knowledge of how aviation works.)

> To give you an idea of data complexity, all airliners come with hundreds or thousands of pages of closely printed tables giving performance at specified weight, temperature, altitude, etc.

Make you wonder about who comes up with the theory on how to write those performance tables..

Scikit-decide, hosted by Airbus.