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Non-motorized lanes are crucial infrastructure for cycling; however, numerous cities worldwide lack adequate provisions in this regard, with Dalian serving as a representative example. To address this challenge, this study develops a priority assessment model for non-motorized lane planning in Zhongshan District, Dalian. The methodology combines street view image analysis with a pre-trained Mask2Former model to quantify lane demand intensity, road openness, and sidewalk openness, alongside GIS-based computations of road gradient and Points of Interest (POI) kernel density. The Analytic Hierarchy Process (AHP) was used to assign indicator weights, and a Multi-Criteria Decision Analysis (MCDA) model was created to evaluate priority. Results reveal a strong link between cycling demand and POI density. High-priority areas are mainly in the urban core, where roads are flat and wide and POIs are dense, including Zhongshan Square, Erqi Square, and Nanshan Tourism Street. They also include Donggang, where POI density is relatively low but road conditions are excellent. Low-priority zones are found in the southern coastal mountains and the central hills, such as Binhai Middle Road and Dongshan. The model provides a data-driven approach for planning non-motorized lanes in environments with limited space and high density of built structures.
Li et al. (Wed,) studied this question.