Current navigation applications allow routes to be drawn between two different locations on a map, either within a town or among different cities. These applications offer routing services mainly for vehicles such as cars, motorcycles or public transport vehicles, but also for pedestrians. For vehicles, these applications increasingly take into account aspects such as fuel consumption or pollution. However, for pedestrians, most current applications only provide shortest distance routes, not considering other relevant aspects such as the profile of the users (age, physical condition, difficulties to walk-up stairs, wheelchair requirements, allergies, etc.) or the current traffic or weather conditions. In this line, this article presents PARApp, a mobile app that allows specifying the user’s profile and, based on it and on the contextual information available about the city, allows computing the fastest (shorter distance), flattest (less slope), safest (in terms of accident rate), less crowded or less polluted routes. PARApp also considers user-defined exclusion zones to be avoided when computing the former routes.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    PARApp Pedestrian-Aware Routing App


    Additional title:

    Lect.Notes Bioengineering



    Conference:

    International Workshop on Gerontechnology ; 2022 ; Evora, Portugal November 17, 2022 - November 18, 2022


    Published in:

    Gerontechnology V ; Chapter : 6 ; 47-52


    Publication date :

    2023-03-28


    Size :

    6 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Pedestrian-Aware Statistical Risk Assessment

    Shen, Xun / Raksincharoensak, Pongsathorn | IEEE | 2022


    Context-aware pedestrian detection using LIDAR

    Oliveira, L / Nunes, U | IEEE | 2010


    Illumination Distribution-Aware Thermal Pedestrian Detection

    Li, Songtao / Ye, Mao / Ji, Luping et al. | IEEE | 2024


    CONCEPT-AWARE ENSEMBLE SYSTEM FOR PEDESTRIAN DETECTION

    Lin, H. / Kim, K. / Choi, K. et al. | British Library Conference Proceedings | 2014


    MPC-based Pedestrian Routing for Congestion Balancing

    Menner, Marcel / Di Cairano, Stefano / Hamada, Masaki et al. | IEEE | 2023