Context-Aware Bicycle Route Planning

Cycling represents a fundamental link in the sustainable urban mobility chain. Besides time and distance, cyclists consider a multitude of criteria when planning their route towards a destination, such as safety, road inclination, road surface, etc. Finding routes that properly take such criteria into account is particularly challenging. Therefore, intelligent route planning services are important to assist cyclists in scheduling routes that address their preferences. Our key research objective has been to develop a wayfinding service tailored to the specific requirements of cyclists (including delivering services) using analytical models which capture various practical aspects that affect the cycling experience. We investigate the use of OpenStreetMap (OSM) to obtain geospatial data relevant to bike routing. Those map data are combined with contextual data (such as wind speed/direction) to derive optimal multicriteria, context-aware bike routes. A preliminary qualitative evaluation has demonstrated the effectiveness and utility of our approach in realistic bike route planning scenarios in urban environments.