Traffic flow measured on different 4-way junctions [video]
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I think it would be good if the title made that clear, and didn't pretend this is some serious simulation. I mean, it's very cool and detailed for a game, but as you can tell from the video, it's far from perfect. It doesn't care about collisions, just about a rough approximation of traffic flow.
For example, roads are on average much cheaper than rail lines per lane mile of construction, but lots of roads get built in rural or depopulated areas where land is cheaper, whereas rail tends to be built in denser corridors.
Right from the start it is obvious this "simulation" is not a full realistic one. Behaviour of vehicles and amount of them is not realistic and it is not clear what the score represents.
https://captaingames.itch.io/freeways
You are a traffic engineer.
Draw freeway interchanges.
Optimize for efficency and avoid traffic jams.
https://arxiv.org/abs/1612.07888 Kurauskas, Valentas - On the genus of the complete tripartite graph Kn,n,1 [2017]
https://arxiv.org/abs/1801.03860 Kurauskas, Valentas; Šiurienė, Ugnė - Symmetric road interchanges [2018]
And slides from 2010:
http://web.archive.org/web/20101127223543/http://www.saga-ne...
In the same vein, for the few complex systems at the end, they should probably factor in human mistakes in the score because it looks like it would be incredibly time consuming to get back on the right way if you took the wrong turn (and could potentially add traffic to the equation).
It seems like, from that simulation, that the longer the curve, the higher the potential throughput. I particularly liked the Turbine.
If everything is tractor trailers, the throughput is lower based on vehicle classification. If everything is passenger cars, variation between SUV and sub-compact car provides a mid-range. If everything is motocycles only the vehicle dynamic squashes vehicle volume and boosts maneuverability to inflate apparent throughput.
Somewhere in this, driver skill level and physical fitness comes into play though, so there has to be an index for that also, based on available residential zones, and an origin/destination matrix.
If everyone is driving from the retirement home to church bingo, the throughput will be lower than tractor trailers. Tractor trailers and other commercial vehicles are expected to operate at lower speeds due to inertial lag during braking and acceleration, prolonging periods spend at lower speeds. All other vehicles can only be modeled according to legal speed limits, even though the accuracy of the simulation is threatened by the fact that in reality many vehicles will be ignoring speed limits.
Time of day, however, is usually going to model rush hour, which consequentially alters vehicle profile and driver persona.
My conclusion is that throughput is basically a function of space the intersection takes up. Also water is wet.
Sure given a fixed space you can optimize type to maximize throughput. If you really care about maximizing throughput with minimal complexity (the more rapid fire merges and lane changes you have the greater the chance of an accident that bottles up the whole system) big rotaries seem to be the way to go (above/below grade structures and traffic signals are a lot more expensive and cost more to maintain than some raised medians to divide right turn lanes).
Also, the video showed how effective getting the signaling right can be: intersections with dedicated left turn lanes (with the TPME mod) outperformed stock traffic lights by almost 50%. The 4-lane road with dedicated left turn lane outperformed a 6-lane road without protected lefts.
Modifications to roundabouts that added dedicated bypass routes for higher traffic / shorter path (merge to closest output without being part of the main queue) were inexpensive upgrades.
The same general observation also applied to higher scale variations where the core loop was either factored out entirely (every route has a dedicated path); applying more complexity (expensive) lead to better results.
Of course the real world has different needs than this over-simplified simulation.
Terrain and political situations impose limits on usable work area while use patterns can vary widely. Worse solutions that used to work in the past can be woefully incorrect as the world around them changes.
The example that comes to my mind is the pattern in urban areas, especially like Seattle with heavy geographic constraints that make alternate routes untenable, where the old "most commuters go in to the city in the morning and leave in the evening" break entirely as jobs flee the expensive urban core and leave workers trying to traverse the choke points where cross traffic was never designed in.