Road-Intersec-Traffic

This paper is released with our paper titled “Annotated 3D Point Cloud Dataset for TrafficManagement 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 supports 3D object detection and instance segmentation tasks. We trained object detection and instance segmentation models to evaluate them on our dataset for scene understanding and road user information extraction compared to the SOTA. We show that our methodology achieved a good performance in both tasks showing the advantage of the proposed approach. This dataset is also released with the paper “AI-driven Traffic Scene Understanding Using Static LiDAR Sensors”. Links to the papers will be provided upon publication