Planning urban underground space from urban emergency evacuation: A digital layout planning method

Abstract

In recent years, the vulnerability of cities has heightened the threat of disasters, thereby endangering the safety of urban population. To mitigate these risks, the establishment of well-planned shelter system is of utmost importance for effective emergency response. Urban underground space (UUS) stands out as a promising solution for providing shelter during times of disasters, owing to its distinct characteristics of confinement and stability. However, the majority of UUS do not function directly for emergency evacuation, leading to neglect at the planning phase. It is valuable to study an applicable planning technique to prospectively consider emergency shelter services of UUS. In this paper, based on digital tools, a method for the rapid quantitative extraction and analysis of a dynamic population distribution is proposed to quantify demand for emergency evacuation. A multi-step greedy algorithm and a social force model (SFM) with specialized parameters are constructed to realize the simulation and analysis on a digital platform with integrated urban models. A multi-criteria decision-making system for evaluating UUS layout is established using the technique for order of preference by similarity to ideal solution (TOPSIS). Finally, a case study in Nanjing built-up area is presented to demonstrate the performance of the proposed method. The proposed method can expand the research perspective and data-driven toolkit for underground space planning.