The repository saves two sample videos and vehicle trajectories for the paper “A Novel Framework for Automatic Vehicle Trajectory Extraction and Denoising from Aerial Videos”, which was submitted to Transportation Research Part C: Emerging Technologies (trajectory special issue). If you think the video and data are useful for your work, please cite our paper as follows: Xinqiang Chen, Zhibin Li, Lei Qi and Yongsheng Yang, A Novel Framework for Vehicle Trajectory Extraction and Denoising from Aerial Videos, submitted to IEEE Transactions on Intelligent Transportation Systems. The details about video #1 was described in the paper. The video #2 was shot within 5minutes 30seconds,and the traffic state in the video evolves from free-flow to congested status, which can provide us unique high-fidelity trajectories, and help us deeply explore traffic state evolution mechanism, driver behavior prediction and analysis, traffic accident formation and prevention etc. If you want the trajectory data as an early bird, please send a request email to: chenxinqiang@stu.shmtu.edu.cn. Explanations for files listed in each repository are as follows: trajectory_dataset_1 contains videos for #1 and the corresponding trajectory data description, and trajectory_dataset_2 contains videos for #2 and the corresponding trajectory data. For each trajectory file (e.g. vehicle_1_trajectory_frenet.txt), Please open it with matlab, and then you can find the file incldues 5 columns. The 3rd column is the trajectory for the vehicle and the 5th column is time. The lane label in video.png file demonstrates vehicle lane number. lane_1_trajectory folder saves trajectories with vehicles driving on lane 1, and vehicle trajectories on other lanes (#2, 3, 4, 5) are saved in the folder with same name formats. The initial_video.avi file is the original UAV video. The vehicle_positions_in_video.avi file shows each vehicle position in each frame in aerial video. NOTE: due to file uploading limitation by github (each to-be-uploaded file should be less than 100M), video in each folder may not be so clear. If you want the high-resolution for each video, please send me an email: chenxinqiaing@stu.shmtu.edu.cn. If you have any problems, please do not hesitate to contact me too.