Distance-Time Conversion Factor

This study proposes a novel approach to smart regional planning to address challenges in public service accessibility. We advocate for a tailored strategy based on regional characteristics, focusing on a city-level conversion factor for intuitive travel time and distance estimation in public service planning. Our analysis considers road network distance, Euclidean straight-line distance, and minimum travel time factors based on speed limits and real-time speeds. The introduced distance-time conversion factor (DCF), calculated from the circuity factor (CF) and delay factor (DF). This calculation identifies areas with a high DCF, particularly around major metropolitan centers. The findings serve as crucial indicators for densely populated regions, marking a significant step towards a realistic public infrastructure plan that surpasses traditional uniform location planning limitations. By comprehensively diagnosing issues related to underdevelopment and population overcrowding, our study emphasizes the need for dynamic planning strategies. The DCF provides valuable insights that can guide effective public infrastructure development of regions with heightened demand for improved accessibility. This research contributes a dynamic distance-time conversion factor, refining the landscape of smart public service planning by leveraging real-time traffic big data. The findings underscore the significance of tailoring planning strategies to regional nuances and ultimately paving the way for more effective and responsive public infrastructure development.