This post will cover some of the examples I have worked on in terms of simulating urban phenomena in Processing as part of my MRes coursework.
For a city to exist people must have proximity to one another. New entrants to the city will need to connect to those already there. However, individual values dictate their locational choice. This model holds these values as seeking as much personal space as possible – so that they wish to live as far away from others as possible but still remain connected and within the city’s area. Here a diffusion-limited aggregation (DLA) rule has the particles (here, individuals) undertaking a random walk until they connect with a static particle. The simulation begins with one static particle in the centre and you can see the pattern begins to form dendritic structure similar to those seen in some settlements and transportation networks.
As touched on in my other post, agent-based models can be used to describe system behaviours from the bottom-up, where simple behavioural rules work together to create a phenomena more, or different, to the sum of their parts. Here the agents are performing basic behaviours of avoiding each other and moving towards a goal. One can see the effect the agents have on eachother reaching their goal. One can start to observe how these models can be used to simulate the effects of congestion and crowding.