| Abstract |
Highlights: What are the main findings? This research introduced a new analytical bikeability index framework integrating micro-level indicators based on five internationally recognized bicycle infrastructure design principles: safety, comfort, attractiveness, directness, and coherence. The proposed framework was applied in Hasselt, Belgium, successfully identifying low and high-bikeable areas. What are the implications of the main findings? The BI framework provides urban planners with a practical tool to identify low bikeability areas and suggests improvements in cycling infrastructure. This tool’s scalable and adaptable nature makes it relevant for cities committed to enhancing cycling environments and promoting a sustainable mode of transport by making cycling-friendly cities. Modern and smart cities prioritize providing sufficient facilities for inclusive and bicycle-friendly streets. Several methods have been developed to assess city bicycle environments at street, neighborhood, and city levels. However, the importance of micro-level indicators and bicyclists’ perceptions cannot be neglected when developing a bikeability index (BI). Therefore, this paper proposes a new BI method for evaluating and providing suggestions for improving city streets, focusing on bicycle infrastructure facilities. The proposed BI is an analytical system aggregating multiple bikeability indicators into a structured index using weighed coefficients and scores. In addition, the study introduces bicycle infrastructure indicators using five bicycle design principles acknowledged in the literature, experts, and city authorities worldwide. A questionnaire was used to collect data from cyclists to find the weights and scores of the indicators. The survey of 383 participants showed a balanced gender distribution and a predominantly younger population, with most respondents holding bachelor’s or master’s degrees and 57.4% being students. Most participants travel 2–5 km per day and cycle 3 to 5 days per week. Among the criteria, respondents graded safety as the most important, followed by comfort on bicycle paths. Confirmatory factor analysis (CFA) is used to estimate weights of the bikeability indicators, with the values of the resultant factor loadings used as their weights. The highest-weight indicator was the presence of bicycle infrastructure (0.753), while the lowest-weight indicator was slope (0.302). The proposed BI was applied to various bike lanes and streets in Hasselt, Belgium. The developed BI is a useful tool for urban planners to identify existing problems in bicycle streets and provide potential improvements. © 2025 by the authors. |
