Demand Modeling for Responsive Transport Systems Using Digital Footprints

Abstract

Regular public road transportation usually uses fixed routes and schedules, which may impair the mobility of potential users in rural areas and certain periods of the day in urban areas due to low and unpredictable demand. Demand Responsive Transport (DRT) tries to address these problems and improve community welfare, by using flexible routes and frequencies that vary with the actual observed demand, possibly adopting route solutions in real-time. These systems try to fill in the gap between traditional transportation service and the individual transportation. DRT services must try to be sustainable, make an efficient use of vehicles and respond to users mobility needs. Given the expected low number of requests, the application of traditional demand modeling methods is not adequate: usually, demand modeling for DRT requires a higher resolution zoning when compared to traditional transportation systems. We will need to analyze user’s short term land use patterns, with a careful analysis of available data, coming from collaborative platforms like Twitter and Foursquare.