Personalizing Pedestrian Accessible way-finding with mPASS

Abstract

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.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 54 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.