Fair Use for Academic Research: If you use this dataset, please cite the following paper to ensure proper attribution
M. A. Onsu, P. Lohan, B. Kantarci, A. Syed, M. Andrews, S. Kennedy, "Leveraging Multimodal-LLMs Assisted by Instance Segmentation for Intelligent Traffic Monitoring," 30th IEEE Symposium on Computers and Communications (ISCC), July 2025, Bologna, Italy.
Preprint available here: https://arxiv.org/pdf/2502.11304
This paper is released with our paper titled “Annotated 3D Point Cloud Dataset for Traffic Management in Simulated Urban Intersections”. This paper proposed a 3D simulation based approach for generating an elevated LiDAR based 3D point cloud dataset simulating traffic in road intersections using Blender. We generated randomized and controlled traffic scenarios of vehicles and pedestrians movement around and within the intersection area, representing various scenarios. The dataset has been annotated to support 3D object detection and instance segmentation tasks.
