ABSTRACT
Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.
Acknowledgment
The authors would like to acknowledge Dawn Herring for her editorial review as well as two anonymous reviewers and the editor for their insightful feedback.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 Another commercial vendor providing crowdsourced data products for active modes of travel is Street Light Data (Citation2019). It combines multiple sources collected from multi-app LBSs, fitness tracking apps, counters, and traditional surveys, which is likely to improve data quality, but its applications have lagged behind Strava Metro due to its recent launch in 2019.