Crowd-Sourced Data and Cycling
Friday, 2:00pm – 5 min
The aim of this lightening talk to is to present methods and data fusion techniques to better model commuter cycling flows.
San Francisco, California will serve as the case study for this presentation. OpenStreetMap data is crucial for this project as it provides information on street and cycling infrastructure, which have both been found to significantly affect cycling commute volumes.
OSM is not the only crowd-sourced data used in this project, data from the cycling app Strava will also be used, and integrated with OSM data. Additionally manual bike count survey data, bike share trip data, and automated count cycling data will be incorporated. This research illustrates how OSM data can be used to facilitate insights into cycling safety, and sustainable transportation planning.