交通参与者（TPs）的轨迹数据是评估交通状况和优化管控策略的基础资源，尤其在城市交叉口场景中至关重要。尽管无人机采集方式效率较高，但现有数据集在场景代表性、信息丰富度及数据保真度方面仍存在局限。本研究提出 FLUID，包含一个细粒度轨迹数据集，用于捕获典型城市信号控制交叉口处的密集冲突轨迹；以及一个轻量级、端到端的无人机轨迹处理框架。

The trajectory data of traffic participants (TPs) is a fundamental resource for evaluating traffic conditions and optimizing policies, especially at urban intersections. Although data acquisition using drones is efficient, existing datasets still have limitations in scene representativeness, information richness, and data fidelity. This study introduces FLUID, comprising a fine-grained trajectory dataset capturing dense conflicts at typical urban signalized intersections, and a lightweight, full-pipeline framework for drone-based trajectory processing.