Automatic estimation of demand matrices for universities through mobile devices


Abstract:

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.

Año de publicación:

2020

Keywords:

  • Trip segmentation
  • Smartphone tracking apps
  • Origin-destination matrix estimation
  • DataMining

Fuente:

googlegoogle
scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Educación superior
  • Análisis de datos

Áreas temáticas:

  • Educación superior