无人机在道路交通组织管理中的研究进展

doi:10.16097/j.cnki.1009-6744.2026.05.008

摘要/Abstract

摘要： 随着低空经济与人工智能技术的快速发展，无人机逐渐从辅助感知设备演进为智慧道路交通组织管理体系中的关键技术支撑，在提升交通运行有序性，保障交通安全与改善交通畅通性方面展现出系统性价值。本文从道路交通组织管理目标导向出发，构建“有序-安全-畅通”这3类典型应用场景的分析框架，系统综述近年来无人机道路交通组织管理研究。结果表明，无人机道路交通组织管理研究整体呈现由“单一感知和局部应用”向“多模态协同和系统集成”演进的趋势。在交通有序场景中，研究重点由早期的规则驱动与人工判读，转向以深度学习为核心的目标检测和检测-跟踪一体化与轨迹分析方法，无人机在交通要素识别覆盖范围与精度方面优势显著，但对高质量数据与理想观测条件的依赖限制了其跨场景应用。在交通安全场景中，多传感器融合、异常行为识别、多无人机协同响应和三维场景重建成为研究热点，无人机在事故识别、应急支撑和风险研判中的独特价值得到验证，但现有研究缺乏对完整应急管理链条中系统协同效能的深入评估。在交通畅通场景中，无人机应用由局部拥堵监测逐步扩展至宏观交通态势感知与事故现场三维重建，多无人机协同与空地融合成为提升拥堵治理能力的关键方向，但其对通信基础设施、空域管理和运行机制提出更高要求。在此基础上，本文归纳无人机应用于3类道路交通组织管理场景的共性评估体系与数据基础，并展望其在技术泛化能力、多主体协同机制和制度化运行体系等方面的未来发展趋势。

关键词: 城市交通, 研究综述, 道路交通组织管理, 无人机, 交通有序, 交通安全, 交通畅通

Abstract: With the rapid development of the low-altitude economy and artificial intelligence technologies, Unmanned Aerial Vehicle (UAV) have gradually evolved from auxiliary sensing devices into a key technological pillar of intelligent traffic management systems, demonstrating systemic value in enhancing traffic order, ensuring traffic safety, and improving traffic operation smoothness. This paper proposes an analytical framework for three typical application scenarios—"orderly, safe, and smooth"—and provides a systematic review of recent research on UAV-based road traffic operation and management. The results indicate that research in this field is evolving from "single-modal perception and localized applications" toward "multi-modal collaboration and system integration." In traffic order scenarios, the research focus has shifted from early rule-based approaches and manual interpretation to methods centered on deep learning, such as object detection, integrated detection-tracking, and trajectory analysis. UAVs demonstrate significant advantages in the coverage and accuracy of traffic element identification; however, their reliance on high-quality data and ideal observation conditions limits their cross-scenario application. In traffic safety scenarios, multi-sensor fusion, abnormal behavior recognition, multi-UAV collaborative response, and 3D scene reconstruction have become research hotspots. The unique value of UAVs in accident identification, emergency support, and risk assessment has been validated; however, existing research lacks an in-depth evaluation of system-level collaborative effectiveness within the complete emergency management chain. In traffic smooth management scenarios, UAV applications have gradually expanded from localized congestion monitoring to macro-level traffic situation awareness and three-dimensional (3D) reconstruction of accident sites. Multi-UAV coordination and air-ground integration have emerged as key directions for enhancing congestion management capabilities; however, this places higher demands on communication infrastructure, airspace management, and operational mechanisms. Building on this, this paper summarizes a common evaluation framework and data foundation for UAV applications across three types of road traffic operation and management scenarios, and outlines future development trends on technological generalization capabilities, multi-agent coordination mechanisms, and institutionalized operational systems.

Key words: urban transportation, research review, road traffic operation and management, unmanned aerial vehicle, orderly traffic, safe traffic, smooth traffic

中图分类号:

U121

范博松 , 赵丹, 牛学军, 邵春福. 无人机在道路交通组织管理中的研究进展[J]. 交通运输系统工程与信息, 2026, 26(5): 89-111.

FAN Bosong, ZHAO Dan, NIU Xuejun, SHAO Chunfu. Research Progress of Unmanned Aerial Vehicle in Road Traffic Operation and Management[J]. Journal of Transportation Systems Engineering and Information Technology, 2026, 26(5): 89-111.

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http://www.tseit.org.cn/CN/Y2026/V26/I5/89

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