Automatic estimation of demand matrices for universities through mobile devices

Several strategies have been proposed in universities to improve the mobility of students given its high attractiveness. To promote policies, dynamic origin-destination matrices for different scenarios are required. The omnipresence of mobile devices allows daily travel logs to be automatically extracted via tracking apps in contrast to traditional trip surveys. This paper proposes a novel methodology to mine multiday mobility demand in universities, from logs generated by dedicated apps regularly used by the students. This approach was assessed on real life logs from a representative sample of students during a 5-month campaign. The suggested approach proved to be suitable for retrieving the average demand that could be used to plan mobility strategies, as long as mobility data can be continuously tracked by mobile devices.