探索智慧城市环境下物流无人机航路网络规划理论与方法是构建未来城市空中交通系统、开启无人机物流时代的基础性和前瞻性课题。本课题从物流无人机运输需求全时空预测分析入手，着重研究无人机航路网络数字化规划与多维度评价问题。首先，采用宏观预测与微观分析相结合的方法，通过建立物流无人机运输需求四阶段预测模型和标准无人机四维轨迹精密预测模型，实现需求的多尺度空间总量预测和细粒度时间分布分析；然后，采用多智能体机器学习、多目标协同进化、三维空间栅格化等理论与仿真技术，在综合标定物流无人机运行安全间距的基础上，建立低空空域分类划设与数字表示方法、物流无人机起降场点协同选址布局模型、多类型结构航路网络三层规划模型与动态容量评估方法；最后，采用模糊聚类、信息熵等方法，构建面向安全、效益、环境和隐私等多维视角的航路网络评价指标体系与动态综合量化评价模型。成果可为物流无人机空中运输管理与产业发展等奠定部分理论基础。

Exploring the theory and practices of urban airway planning, for logistical unmanned aerial vehicles (UAVs), in the smart city scenario is an exploratory project, for the purpose of constructing the future urban air traffic management system and building an era of UAV logistics. This project starts from predicting and analyzing the overall spatial-temporal characteristics of the delivery demand with logistical UAVs, focusing on the problem of UAV airway network planning and holistic assessment. Firstly, macroscopic predictions and microscopic analysis will be combined, in such a way to formulate a four-stage model for predicting the UAV delivery demand and to develop a precise UAV 4D trajectory predictor, which could contribute to predicting the total traffic volume in spatial domain and analyzing the distribution in temporal domain. Then, the latest theory advances and simulation technologies, such as multi-agent machine learning, multi-objective collaborative evolution, 3D spatial rasterization, just to mention some, will be used in this project. Based on the synthesis separation management for logistical UAV operations, the low-level altitude airspace organization and digitalization model will be established, along with the collaborative address choosing model for UAV taking off and landing, the three-level network planning model, and the dynamic capacity evaluation method. Finally, using some advanced methods including fuzzy clustering and entropy, a framework consisting of key performance indicators will be built, as well as a dynamic synthesis assessment model, with the objective of achieving safe, efficient, environmental and privacy operations. It is envisaged that the delivery of this project could contribute to forming the theoretical basis of logistical UAV traffic management and the industry development.