Análisis de viajes con la aplicación de teléfonos inteligentes

Abstract

Abstract: Previous research has developed several promising models for digital data capture mobility, which can be applied in urban planning, transportation and land use planning models. Therefore the aim of this work is to develop a methodology to produce information mobility on Origin-Destination (OD) and travel time matrices, identification of travel modes, points of interest (POIs) and frequent routes through the development and implementation of an application for Android mobile devices. Methodology: There was an application for mobile devices with Android operating system, based on existing models. This application obtained mobility data from sensors embedded in mobile location (GPS). Data was subsequent migration to a cloud database. Post process analysis was conducted with tools such as KNIME, Python and QuantumGIS. The application was tested by 68 students volunteer from the University of Cuenca, for 14 days in January 2016. Results: We obtained data from 44 volunteers for create OD matrices and travel times matrices for different periods of the day. These matrices helped to identify variations of interaction between areas, number and time of travel. They were identified modes of transport such as cycling and motorized. POIs House (91%), Work (74%) and intermediate stops (20% of total POIs) were detected. A mobility atypical behaviors were observed. Finally the compared of routes frequented vs theoretical optimal routes finding that 63.6% of users agreed with total of travel of the latter. Conclusions: The proposed method of analysis and recollection of data presents consistent with previous studies showing comparable levels of confidence. The biggest challenge is the massive deployment model for the collection of useful data mobility plans.