期刊名：Drones

期刊主页：https://www.mdpi.com/journal/drones

随着全球城市化进程加速，地面交通拥堵已成为制约城市可持续发展的核心瓶颈，传统二维交通网络已难以满足日益增长的出行需求，亟需向三维空间拓展以缓解交通压力。近年来，电动垂直起降飞行器（eVTOL）、自主导航与感知避障、5G/6G通信及空域数字化管理等技术取得突破性进展，为无人机在城市低空环境中的安全、高效运行提供了关键支撑。

1.Urban Air Mobility Communications and Networking: Recent Advances, Techniques, and Challenges Image

城市空中交通通信与网络：最新进展、技术和挑战

https://www.mdpi.com/2504-446X/8/12/702

Arafat, M.Y.; Pan, S. Urban Air Mobility Communications and Networking: Recent Advances, Techniques, and Challenges. Drones 2024, 8, 702.

2.Air Route Design of Multi-Rotor UAVs for Urban Air Mobility

用于城市空中交通的多旋翼无人机航线设计

http://www.mdpi.com/2306-5354/11/2/138

Li, S.; Zhang, H.; Li, Z.; Liu, H. Air Route Design of Multi-Rotor UAVs for Urban Air Mobility. Drones 2024, 8, 601.

3.Performance Analysis and Conceptual Design of Lightweight UAV for Urban Air Mobility

轻型无人机在城市空中交通中的性能分析与概念设计

https://www.mdpi.com/2504-446X/8/9/507

Mazzeo, F.; de Angelis, E.L.; Giulietti, F.; Talamelli, A.; Leali, F. Performance Analysis and Conceptual Design of Lightweight UAV for Urban Air Mobility. Drones 2024, 8, 507.

4.A Deep Learning-Based Trajectory and Collision Prediction Framework for Safe Urban Air Mobility

基于深度学习的城市空中交通安全轨迹与碰撞预测框架

https://www.mdpi.com/2504-446X/9/7/460

Kim, J.; Yoon, H.; Yoon, S.; Kwon, Y.; Lee, K. A Deep Learning-Based Trajectory and Collision Prediction Framework for Safe Urban Air Mobility. Drones 2025, 9, 460.

5.Development and Validation of a Custom Stochastic Microscale Wind Model for Urban Air Mobility Applications

针对城市空中交通应用开发和验证定制随机微尺度风模型

https://www.mdpi.com/2504-446X/9/12/863

Nithya, D.S.; Monteleone, F.; Quaranta, G.; Liang, M.; Muscarello, V. Development and Validation of a Custom Stochastic Microscale Wind Model for Urban Air Mobility Applications. Drones 2025, 9, 863. https://doi.org/10.3390/drones9120863

6.Towards Safer UAV Operations in Urban Air Mobility: 3D Automated Modelling for CFD-Based Microweather Systems

迈向更安全的城市空中交通无人机运行：基于CFD的微气象系统的三维自动化建模

https://www.mdpi.com/2504-446X/9/11/730

Aldao, E.; Veiga-Piñeiro, G.; Domínguez-Estévez, P.; Martín, E.; Veiga-López, F.; Fontenla-Carrera, G.; González-Jorge, H. Towards Safer UAV Operations in Urban Air Mobility: 3D Automated Modelling for CFD-Based Microweather Systems. Drones 2025, 9, 730.

7.UAV Operations and Vertiport Capacity Evaluation with a Mixed-Reality Digital Twin for Future Urban Air Mobility Viability

利用混合现实数字孪生技术评估无人机运行和垂直起降场容量，以评估未来城市空中交通的可行性

https://www.mdpi.com/2504-446X/9/9/621

Zhao, J.; Wen, Z.; Mohanta, K.; Subasu, S.; Fremond, R.; Su, Y.; Kallaka, R.; Tsourdos, A. UAV Operations and Vertiport Capacity Evaluation with a Mixed-Reality Digital Twin for Future Urban Air Mobility Viability. Drones 2025, 9, 621.

8.A Systematic Review of Urban Air Mobility Development: eVTOL Drones’ Technological Challenges and Low-Altitude Policies of Shenzhen

城市空中交通发展系统性综述：深圳电动垂直起降无人机的技术挑战与低空飞行政策

https://www.mdpi.com/2504-446X/9/12/842

Xu, J.; Guan, C.; Wang, Y.; Zhuang, J.; Gan, W. A Systematic Review of Urban Air Mobility Development: eVTOL Drones’ Technological Challenges and Low-Altitude Policies of Shenzhen. Drones 2025, 9, 842.

9.UTUAV: A Drone Dataset for Urban Traffic Analysis

UTUAV：用于城市交通分析的无人机数据集

https://www.mdpi.com/2504-446X/10/1/15

Lepin, F.; Velastin, S.A.; León, R.; García-Herrero, J.; Rojas-Martínez, G.; Espinosa-Oviedo, J.E. UTUAV: A Drone Dataset for Urban Traffic Analysis. Drones 2026, 10, 15.

10.Federated Twin Delayed Deep Deterministic Policy Gradient for Delay and Energy Consumption Optimization in Urban Air Mobility with UAV-Assisted MEC

基于联邦双延迟深度确定性策略梯度算法的城市空中交通延误和能耗优化：无人机辅助移动均衡

https://www.mdpi.com/2504-446X/9/2/137

Pan, C.; Luo, Z.; Zhang, J.; Shi, L.; Yi, J.; Yang, Z. Federated Twin Delayed Deep Deterministic Policy Gradient for Delay and Energy Consumption Optimization in Urban Air Mobility with UAV-Assisted MEC. Drones 2025, 9, 137.

11.BiDGCNLLM: A Graph–Language Model for Drone State Forecasting and Separation in Urban Air Mobility Using Digital Twin-Augmented Remote ID Data

BiDGCNLLM：一种基于数字孪生增强型远程ID数据的城市空中交通无人机状态预测与分离的图语言模型

https://www.mdpi.com/2504-446X/9/7/508

Wen, Z.; Zhao, J.; Zhang, A.; Bi, W.; Kuang, B.; Su, Y.; Wang, R. BiDGCNLLM: A Graph–Language Model for Drone State Forecasting and Separation in Urban Air Mobility Using Digital Twin-Augmented Remote ID Data. Drones 2025, 9, 508.

12.Mid-Air Collision Risk for Urban Air Mobility: A Review

城市空中交通的空中碰撞风险：一项综述

https://www.mdpi.com/2504-446X/10/3/211

MDPI引用格式: Li, J.; Jiang, R.; Fu, R.; Gao, Y.; Liu, Y.; Cai, K.; Quan, Q. Mid-Air Collision Risk for Urban Air Mobility: A Review. Drones 2026, 10, 211.

13.Sustainability of Drone-Based Urban Air Mobility: A Systematic Review of Consensus and Controversies

基于无人机的城市空中交通的可持续性：共识与争议的系统性综述

https://www.mdpi.com/2504-446X/10/5/334

Guo, Y.; Zhao, J.; Wu, M.; Peng, X.; Xia, Y.; Yu, Y. Sustainability of Drone-Based Urban Air Mobility: A Systematic Review of Consensus and Controversies. Drones 2026, 10, 334.

14.Enhancing Operational Safety for Urban Air Mobility: A Wind-Resilient Energy Estimation Framework for Unmanned Aerial Vehicles

提升城市空中交通运行安全性：一种适用于无人机的抗风能能量估算框架

https://www.mdpi.com/2504-446X/10/5/337

Pang, J.; Liang, X.; Liang, Z. Enhancing Operational Safety for Urban Air Mobility: A Wind-Resilient Energy Estimation Framework for Unmanned Aerial Vehicles. Drones 2026, 10, 337.

15.Urban Air Mobility Risk Assessment and Safety Control over Large-Scale Public Events: A City Marathon Case Study

城市空中交通风险评估及大型公共活动安全管控：以城市马拉松为例

https://www.mdpi.com/2504-446X/10/1/46

Hu, X.; Zhang, H.; Li, H. Urban Air Mobility Risk Assessment and Safety Control over Large-Scale Public Events: A City Marathon Case Study. Drones 2026, 10, 46.

期刊介绍

主编：Prof. Dr. Diego González-Aguilera, University of Salamanca, Spain

Drones是一个国际性的、同行评审的开放获取期刊，专注于无人机（包括无人飞行器（UAV）、无人飞行器系统（UAS）、遥控驾驶飞行器系统（RPAS）等）的设计和应用，以及无人海洋/水上/水下无人机、无人地面车辆、全自动驾驶和空间无人机，由MDPI出版社每月在线出版。目前期刊已被EI、Scopus和SCIE (Web of Science)等数据库收录。英国遥控驾驶飞行器系统协会（ARPAS-UK）和国际无人机系统协会（ICUAS）均与Drones期刊有合作关系，其会员可享受文章处理费折扣。

2025 Impact Factor：5.2

2025 CiteScore：10.0

Time to First Decision：21.1Days

Acceptance to Publication：2.9Days