Leveraging gis data and topological information to infer trip chaining behaviour at macroscopic level
One of the open challenges in transport modelling is to estimate within-day demand flows that reflect the complexity of individual activity-Travel behaviour. While disaggregate (Activity-Based) demand models can recreate realistic daily mobility patterns at an individual level, they usually require an accurate knowledge of individual user behaviour (i.e. via travel surveys), which is not always available.