Publication
This paper develops a framework for understanding pedestrian mobility pattern from WiFi traces and other data sources. It can be used to forecast demand for pedestrian facilities such as railway stations, music festivals, campus, airports, supermarkets or even pedestrian area in city centers. Scenarios regarding the walkable infrastructure and connectors, the scheduling (trains in stations, classes on campus, concerts in festivals) or the proposed services in the facility may then be evaluated. It is inspired by activity-based approach. We assume that pedestrian demand is driven by a willingness to perform activities. Activity scheduling decision is explicitly taken into account. Activity-based approach for urban areas is adapted for pedestrian facilities, with similarities (scheduling behavior) and differences (no ``home'' in pedestrian facilities, thus no tours). This is a first attempt to define a integrated system of choice models in the context of pedestrian facilities.