This is the third part of the MATSim explainer series. The first two parts focused on how MATSim works and the inputs of a MATSim model. If you have read these two sections you will have seen how rich and detailed the input data is. Equally, although the data is very detailed, it is very understandable. Through the visualisations it is easy to see what is being put into the model - pick up errors, see where the model needs improving.
We learnt that MATSim models are based around entities called agents. Each agent has a plan of daily activities and the agents receive a score for how efficiently they accomplish their plan. The model is run over 100+ iterations, and each agent tries to optimise their score over the course of these iterations by modifying their plan.
In this section you will see the data that is produced from a model run and you will see some how this can be turned into really useful analytical tools with great practical uses for transport planning.