无人机采集城市交通数据，支持多尺度分析
DRIFT open dataset: A drone-derived intelligence for traffic analysis in urban environment
- 从250米高空同步拍摄9个路口的航拍视频
- 生成81,699条带方向信息的高分辨率车辆轨迹
- 开源数据与模型，可直接用于交通研究
可靠的交通数据对理解城市出行模式和制定有效管理策略至关重要。本研究提出无人机交通分析智能数据集（DRIFT），通过在约250米高度同步采集大田市9个相连路口的航拍视频构建，涵盖高分辨率车辆轨迹数据，经视频同步与正射校准处理，共获得81,699条车辆轨迹。该数据集支持多尺度交通分析，包括个体车辆行为（如变道）与安全指标（如碰撞时间），以及互联路口的网络级流量动态。数据集结构化设计，无需额外预处理，配套开源目标检测与轨迹提取模型及分析工具。资源已公开，网址：https://github.com/AIxMobility/The-DRIFT，可广泛应用于交通流分析与仿真研究。
原文摘要 · Abstract (English)
Reliable traffic data are essential for understanding urban mobility and developing effective traffic management strategies. This study introduces the DRone-derived Intelligence For Traffic analysis (DRIFT) dataset, a large-scale urban traffic dataset collected systematically from synchronized drone videos at approximately 250 meters altitude, covering nine interconnected intersections in Daejeon, South Korea. DRIFT provides high-resolution vehicle trajectories that include directional information, processed through video synchronization and orthomap alignment, resulting in a comprehensive dataset of 81,699 vehicle trajectories. Through our DRIFT dataset, researchers can simultaneously analyze traffic at multiple scales - from individual vehicle maneuvers like lane-changes and safety metrics such as time-to-collision to aggregate network flow dynamics across interconnected urban intersections. The DRIFT dataset is structured to enable immediate use without additional preprocessing, complemented by open-source models for object detection and trajectory extraction, as well as associated analytical tools. DRIFT is expected to significantly contribute to academic research and practical applications, such as traffic flow analysis and simulation studies. The dataset and related resources are publicly accessible at https://github.com/AIxMobility/The-DRIFT.
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