Modélisation des interactions entre les modes de transport aux abords des stations de métro

Demand modeling is typically based on an average working day, since it often uses data from travel surveys that aggregate multiple days of observation. Also, travel surveys are often performed for a limited time frame rather than a continuous period and neglect low usage transportation modes. Survey data do not allow to capture the effect of occasional events on ridership. Instead, this study proposes using continuous data flows to model travel demand. The data allows not only to analyze demand variations in time, but also in space. Unlike most research that focus on one mode of transportation only, this study proposes a simultaneous analysis of several modes to compare their demand.