人类移动行为的研究是近年来统计物理学、地理学、计算机科学、城市规划与管理、流行病学等学科共同关注的热点问题。已有研究侧重于从统计物理角度进行人类移动模型的构建，难以揭示复杂城市空间中居民移动行为的深层机理。本研究以城市居民日常活动与出行日志、手机轨迹数据、POI等多源数据为基础，从活动-移动的角度分析城市居民移动行为决策的影响因素；研究个体-群体-城市地理环境因素联合决策的城市居民活动-移动行为决策模型，理解城市居民活动-移动行为的成因及变化机制，为复杂城市环境中居民个体移动模型的构建奠定理论基础；基于多智能体模型模拟城市居民移动轨迹及人群动态；构建多情景模拟系统，评价不同的城市设施布局及空间管理方案对居民移动时空过程的适应度，为城市空间规划及管理提供科学的决策指导。

The research on human mobility is a hot topic in the fields of physics, geography, computer science, urban planning and management, and epidemiology in recent years. The previous research has focused on the the modeling of the law of human mobility from the perspective of statistical physics, which makes it difficult to reveal reveal the deep mechanism of residents' travel behavior in complex urban spaces. Based on the travel dairies of urban residents, mobile phone trajectory data, POI and other multi-source data, this study analyzes the influencing factors of decision-making of the travel behavior of urban residents from the perspective of activity-and-travel. Then, the urban resident activity-travel behavior decision model based on integrating individual-group-urban geographical environment factors is studied, to understand the causes and changing mechanisms of urban residents' activity-travel behavior. It lays the theoretical foundation for the of urban residents' mobility model. The multi-agent model is used to simulate the travel behavior of residents and their spatial-temporal evolution in complex urban environments. Finally, a multi-scenario simulation system is developed to evaluate the adaptability of different urban facility layout schemes and space management plans to the space-time movement process of residents, which can provide scientific decision guidance for urban space optimization.