基于当前工作，可以聚焦于利用大数据与人工智能技术推动智慧城市的规划治理。

Building on the current work, the research can focus on leveraging big data and artificial intelligence technologies to advance the planning and governance of smart cities.

1）通过细分居民出行活动类型（通勤/休闲），区分刚性出行受阻（必要出行，如工作、就医）与弹性出行主动减少（非必要出行，如休闲娱乐）；

1）By segmenting residents’ travel activities (e.g., commuting vs. leisure), the study distinguishes between disrupted essential travel (necessary trips such as work or medical visits) and voluntarily reduced discretionary travel (non-essential trips such as recreation and entertainment).

2）从点（住区）、线（道路交通）、面（生活圈/社区发现）三个维度，对城市系统韧性进行全面研究：

2）A comprehensive investigation of urban system resilience will be conducted across three dimensions: point (residential areas), line (road traffic), and area (life circles/community detection):

• 点（住区）：目前成果，需加强理论支撑，并构建出行扰动的复合指标体系；
• 线（道路交通）：根据用户出行途径的基站点与路网进行空间拟合，得到用户出行轨迹的最可能路网节点，记录到move_rn（由于信令定位的精度限制，算法会优先与主干道路进行匹配），通过与route_node表进行关联，获取到路径经纬度信息，可以实现不同区域或者道路上出行量的统计；
• 面（生活圈/社区发现）：从OD流动网络拓扑结构的演变角度定义和量化生活圈/社区的扰动，使得规划治理措施基于实际出行需求，而不局限于传统行政边界。
• Point (Residential Areas): Current achievements need stronger theoretical support, along with the development of a composite indicator system for travel disruptions.
• Line (Road Traffic): By spatially matching users’ base stations and road networks along their travel paths, the most probable road network nodes for user trajectories are identified and recorded in move_rn. Due to the positioning accuracy limitations of mobile signaling data, the algorithm prioritizes matching with major roads. By associating with the route_node table, path latitude and longitude information can be obtained, enabling statistical analysis of travel volumes on different roads or in specific areas.
• Area (Life Circles / Community Detection): Life circles and communities are defined and quantified from the perspective of changes in the topological structure of OD (Origin-Destination) flow networks. This allows planning and governance measures to be based on actual travel demand rather than being limited to traditional administrative boundaries.

基于深圳案例研究，可以将研究扩展至其他城市，开发包括暴雨洪涝、风暴潮、高温等在内的复合灾害韧性的综合评估方法，为韧性与智慧城市的发展提供科学理论与技术支持。

Based on the Shenzhen case study, the research can be extended to other cities. A comprehensive assessment framework for compound disaster resilience, including heavy rain and flooding, storm surges, extreme heat, etc. , will be developed, providing scientific theories and technical support for the development of resilient and smart cities.