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Promoting cycling in mixed-traffic environments remains a global challenge, hinging on the development of well-connected, low-stress networks. However, existing evaluation frameworks often lack comprehensiveness, overlooking the multifaceted nature of cyclists’ experiences. This study addresses this gap by proposing a novel multidimensional evaluation framework for assessing the effective connectivity of urban cycling networks. The framework integrates four critical dimensions: (1) structural connectivity of the basic road network, (2) dynamic interference from mixed traffic, (3) comfort of the cycling environment, and (4) cross-barrier connectivity. Using Nanjing, China, as a case study, we applied a hybrid Analytic Hierarchy Process (AHP)–Grey Clustering method to derive objective indicator weights and conduct a comprehensive evaluation. The results yield a composite score of 3.2568 (on a 0–4 scale), classifying Nanjing’s cycling network connectivity at the “Four-Star” level, indicating a generally positive developmental trajectory. Nevertheless, spatial disparities persist: the urban core faces intense traffic interference, while peripheral areas are hindered by network fragmentation and poor permeability. Key challenges include frequent vehicle–cyclist conflicts at intersections, inadequate nighttime illumination, suboptimal pavement conditions, and excessive detours caused by natural barriers such as the Yangtze River. This study provides urban planners and policymakers with a robust and systematic diagnostic tool to identify deficiencies and prioritize targeted interventions, ultimately contributing to sustainable urban mobility by enhancing the resilience, equity, and attractiveness of cycling networks in complex mixed-traffic settings.
Tan et al. (Sun,) studied this question.