LTS-BikePlan : A Data-Driven Tool for Enhancing Cycling Infrastructure and Safety

This article presents LTS-BikePlan, a data-driven tool based on the Level of Traffic Stress (LTS) methodology, which we developed to improve the planning of bicycle infrastructure and assess the comfort and safety of cyclists. This application provides essential insights into the cyclability of cities (particularly in Italy, where it was developed) by integrating data from public administration sources and GIS resources, including OpenStreetMap (OSM) and the Digital Elevation Model. We showcase LTS-BikePlan use in a range of cycling situations with case studies in the Italian cities of Trento and Bolzano. This study addresses the limited integration of stress-level mapping and safety analysis in current planning tools and demonstrates that many routes and intersections have intermediate traffic stress levels (LTS 3), making it difficult for beginning cyclists to navigate dense traffic and diverse topography. In contrast, urban and residential environments tend to have lower stress levels. However, the findings show that low-stress situations are not always associated with fewer collisions, emphasizing the need of high-quality infrastructure in improving the safety of urban cycling safety. They take a novel approach to identifying critical high-risk areas with high collision potential in low-stress zones, employing predictive models for infrastructure improvement and collision risk assessment to advance urban cycling research and assist policymakers in improving cycling safety and sustainability.