Browsing by Author "Matteo Matteucci"

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    Accessible urban by modeling the explicit data using fuzzy logic
    (ACM, 2017) Daniel Sinkonde; Leonard Mselle; Nima Shidende; Sara Comai; Matteo Matteucci
    The paper explores the level of accessibility for people with specific mobility problems in an urban setting. The work is part on the polisocial Maps for Easy Path (MEP) project [1]. The project aiming at developing a set of innovative tools and solutions for the enrichment of geographical maps with information about accessibility of urban pedestrian areas for people with mobility challenges. This paper builds a FuzzyMEP predictive model that accounts for uncertainty in the real world using fuzzy logic to predict the quality and the condition of the accessibility of a path. The FuzzyMEP model has been developed for mapping two explicit data sets, namely the coordinates where a picture of an obstacle on the sidewalk has been taken and the comment. The current urban city accessibility tool uses spatial data and focuses mainly on the accessibility of a path. We present a novel MEP tool by using a fuzzy logic model for pedestrian path prediction of the condition of the accessibility of a path. In this paper, the FuzzyMEP model has been developed by applying a fuzzy logic rule which can be adapted to other contexts.