Crowdsourcing Bicycle Volumes: Exploring the role of volunteered geographic information and established monitoring methods

Abstract

The recent interest in performance measures and new bicycle infrastructure development has triggered rapid advancements in monitoring methods for active transportation, but comprehensive monitoring programs for the bicycle mode are far from ubiquitous. This study evaluates the use of GPS survey data and a new crowdsourced volume dataset that may offer promise to extend the reach of limited counting programs. The authors integrated count data from 5 separate trail locations in Austin, Texas, with a previous survey using the CycleTracks smartphone app, and a new data product derived from a larger-scale use of the Strava fitness app. New crowdsourced methods offer prospect to expand the relative time and geography of bicycle traffic monitoring, but do not currently offer many other attributes about trips obtainable from other methods. Further studies involving the combination of high-accuracy monitoring points with crowdsourced datasets may improve the efficiency of monitoring programs over large areas.