ABSTRACT
A B S T R A C T Understanding and modelling traveller’s decisions on public transport systems by correctly analysing their choices and being able to forecast flows on the network are essential elements in urban planning. For this, smart cards have arisen as a valuable information source in the past decade, providing massive information at low-cost. This chapter analyses how smart card data can help us understand traveller’s decisions within public transport systems, identifying the relevant factors being taken into account and quantifying the impact that different characteristics of the system have on the preferences of travellers. A case study for Santiago, Chile is presented; the study incorporates perceptions and preferences on a variety of factors (such as crowding, transferring and network topology) to enhance the explanatory and forecasting capabilities of travel demand models.
