Petraki V., Kanakis A., Koliou P., Yannis G., “Investigating Urban Cycling Demand Utilising Crowd sourced Data”, Proceedings of the 13th International Cycling Safety Conference, Oslo, 4-6 November 2025.

This research focuses on “Strava Metro” cycling trips data and aims to demonstrate a framework to utilize these data to understand and model spatiotemporal aspects of cycling trips. The objective is to develop a mathematical model using open data to identify key factors influencing cycling demand, identifying environments that support both higher demand and should be prioritized by policymakers and transport engineers for targeted cycling safety improvements. The study collected cycling activity data from “Strava Metro” platform recorded for the years 2021 and 2022, on 11,446 road segments of two municipalities in Athens, Greece, namely Chalandri and Vrillisia. The findings are strongly aligned with international literature, confirming that infrastructure quality, connectivity, and proximity to cycling-supportive amenities significantly influence cycling behavior. The analysis reveals that higher average cycling speeds on road segments are associated significantly with increased cycling activity. A 1% increase in the recorded cycling speed resulted in a 2.7% increase in cycling trips. However, high cycling speed, is a key indicator of cycling risk. This suggests that segments with increased cycling trips may also be those where safety interventions are most urgently needed. These insights show how cycling demand data can guide infrastructure and safety priorities. Future research could apply this method to other cities, include seasonal or real-time data, and combine demand modeling with crash records to support safer cycling networks.