Personalizing Pedestrian Accessible way-finding with mPASS

This work presents users evaluation of mPASS (mobile Pervasive Accessibility Social Sensing), a system to provide citizens with personalized accessible way finding. mPASS collects data both from crowdsourcing and from crowdsensing, in order to obtain a detailed georeferenced description of the urban environment accessibility. It combines these data with a user profile, with the aim of tailoring paths and maps to users' preferences and needs. To drive the design of our application, we assessed our first proposal through a preliminary questionnaire, showing mPASS mockups to 60 uses with disability and elderly users. On the basis of the results of such questionnaire, we developed a prototype and we tested it with a small group of pilot users. This paper presents results of both the assessments.