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Micro-Level Bicycle Infrastructure Design Elements: A Framework for Developing a Bikeability Index for Urban Areas
Micro-Level Bicycle Infrastructure Design Elements: A Framework for Developing a Bikeability Index for Urban Areas
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Micro-Level Bicycle Infrastructure Design Elements: A Framework for Developing a Bikeability Index for Urban Areas
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Micro-Level Bicycle Infrastructure Design Elements: A Framework for Developing a Bikeability Index for Urban Areas
Micro-Level Bicycle Infrastructure Design Elements: A Framework for Developing a Bikeability Index for Urban Areas

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Micro-Level Bicycle Infrastructure Design Elements: A Framework for Developing a Bikeability Index for Urban Areas
Micro-Level Bicycle Infrastructure Design Elements: A Framework for Developing a Bikeability Index for Urban Areas
Journal Article

Micro-Level Bicycle Infrastructure Design Elements: A Framework for Developing a Bikeability Index for Urban Areas

2025
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Overview
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.