With the increase in traffic volume, a lack of adequate traffic management would result in significant economic and environmental losses, e.g., energy consumption, greenhouse gas emissions, and long-time delays. Many solutions have been used above ground sensors like video cameras, depth sensors, radars, and passive acoustic sensors. However, these technologies have a high cost, and they are easily affected by weather conditions. Nevertheless, it is necessary to find the optimal location of these sensors to provide the maximal field of view.

To overcome these challenges, we propose a drone-based lidar to detect and track cars and pedestrians from 3D point clouds. LiDAR sensors have proven to have great performance under poor weather conditions while drones can help to have a wide coverage while deploying a minimum number of sensors.