Deriving incline values for street networks from voluntarily collected GPS traces

When producing optimal routes through an environment, considering the incline of surfaces can be of great benefit in a number of use cases. For instance, steep segments need to be avoided for energy-efficient routes and for routes that are suitable for mobility-restricted people. Such incline information may be derived from digital elevation models (DEMs). However, the corresponding data capturing methods (e.g. airborne LiDAR, photogrammetry, and terrestrial surveying) are expensive. Current low-cost and open-licensed DEM (e.g. Shuttle Radar Topography Mission [SRTM] and Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER]) generally do not have sufficient horizontal resolution or vertical accuracy, and lack a global coverage. Therefore, we have investigated an alternative low-cost approach which derives street incline values from GPS traces that have been voluntarily collected by the OpenStreetMap contributors. Despite the poor absolute accuracy of this data, the relative accuracy of traces seems to be sufficient enough to compute incline values with reasonable accuracy. A validation shows that the accuracy of incline values calculated from GPS traces slightly outperforms incline values derived from SRTM-1 DEM, though results depend on how many traces per street segment are used for computation.