| Abstract: |
This report presents a first estimation of the volume of bicycles and scooters moving through Barcelona, street by street. Using advanced modeling techniques, we estimate the Average Annual Daily Bicycle Traffic (AADBT) at the street segment level for over 20,000 road segments. We rely on data from automatic counters managed by the city council as well as data collected by volunteers and civil society. The most accurate model, XGBoost, allows visualization of bicycle flows across the entire city and is a valuable tool for urban planning, infrastructure improvement, and road safety studies. One of the study's main achievements has been to demonstrate how citizen participation improves the quality and representativeness of the estimates: thanks to the work of 43 volunteers, it was possible to cover street typologies and areas outside the reach of automatic counters. Despite these improvements, the model still presents some overestimations, especially on streets without cycling infrastructure. Nevertheless, this beta version offers a solid foundation for future developments. This project illustrates the potential of citizen science and interdisciplinary collaboration to advance towards more sustainable, equitable, and evidencebased mobility in Barcelona. |
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