Agent-based mesoscopic traffic flow simulation model (Mesa + UXsim)

[EwoutH]

I'm developing a hybrid Agent-based mesoscopic traffic flow simulation model, using Mesa and UXsim. It's based on a real-world road network extracted and processed with OSMnx. It's in early stages, but development can be followed here:

• https://github.com/EwoutH/urban-self-driving-effects/tree/main/model

Core features from Mesa used are the AgentSet and the experimental DEVS simulator.

Once it's in further stages I will describe it more extensively, and maybe open a PR to add (a simplified version) as an example. But for now a quick share for anyone interested to follow.

Early conceptual model

[EwoutH]

Quick update: Model is running and has reached minimal-viable product status, with a latest interaction bug between Mesa and UXsim resolved (correct bookkeeping of time in both is important): EwoutH/urban-self-driving-effects@2a702c3. It was an interesting case in using DEVS to schedule things for another simulation model.

The modal is simulating traffic in a ~half a million city during a full day, represented by 120.000 agents which each represent 5 people in the traffic model. UXsim is running with up to 50 thousand vehicles simultaneously. Each 900 seconds the model recalculates all travel times between all nodes on which allows Agents to take new mode choice decisions.

First traffic patterns are following expectations. Lot's of "magic numbers" of course, tomorrow is data collection, aggregation, plotting and validation day. Goal is to determine where to refine more.

Then it's taking a step back to the original research goals to see which questions we can exactly answer, what we need to be able to do that, which are unfeasible.