Computation of Incline Barriers via Smartphone Sensors in the Mobile App WheelScout

Abstract

Mobility impaired people face difficulties when using navigation tools looking for barrier-free routes. Most current navigation systems provide the computation of routes for different means of transportation, but they leave out routes for users in wheelchairs or otherwise mobility impaired. Based on the GraphHopper routing engine operating on Open Street Map (OSM) data, we have developed the mobile app WheelScout, which computes barrier-free routes by matching data on barriers in any given mapsection against the personal ability profile of the user. OSM provides data for some barriers, such as stairs, but others, like narrow passages, surface conditions, temporary barriers or inclines, are either not coded at all or not included with a sufficient coverage or accuracy. In this paper, we focus on inclines as barriers, which are computed based on the altitude parameters between two coordinates. In order to reach maximal accuracy in the degree of incline, we aim at computing maximal accuracy of the altitude data of each coordinate. This paper describes an innovative solution as to how static sensor data can be optimized by dynamic input parameters, such as local temperature and the standard air pressure at the current location, and how the combination of gathered data can additionally be optimized by applying a Kalman filter in order to reduce noise and deviations. Our results show an altitude accuracy of ±1 m, which can be considered as optimal input for the computation of an incline degree.