Evaluating Pedestrian and Cyclist Friendliness in Urban Neighborhoods Using an Active Travel Index System: Application in 52 Chinese City Sub-Districts

Active transportation plays a critical role in promoting sustainable, healthy, and equitable urban mobility, yet comprehensive tools for evaluating pedestrian and cyclist environments remain limited. This study develops an Active Travel Index to assess the walkability and cyclability of urban neighborhoods by integrating objective infrastructure measures with subjective user perceptions. To determine key indicators of the Active Travel Index, we analyzed multi-source data collected from four districts in three Chinese cities. The data included a customized geographic information system database of sidewalks and bicycle lanes of the five urban districts, panoramic video-based streetscape mapping covering 697 km road segments and 86 intersections, and 2,520 user surveys. This analysis resulted in an Active Travel Index framework composed of 13 indicators across three dimensions: network completeness, facility quality, and active travel vitality. Indicators reflect conditions such as path density, surface quality, crossing convenience, ride disturbances, accessibility to destinations, travel mode share, and user satisfaction. Indicator weights were determined through the analytic hierarchy process with expert input. In the application, the Active Travel Index was used to produce ranked evaluations of 52 subdistricts of the three cities, highlighting specific deficiencies and guiding policy recommendations. Results revealed substantial intra- and inter-city disparities in active travel infrastructure, particularly in surface continuity, vehicle intrusions, and design consistency. This index offers a replicable tool for diagnosing urban travel environments and informing infrastructure investments. By bridging technical assessments with user experiences, the Active Travel Index supports more inclusive and data-driven decision-making in transportation planning and performance monitoring.