Sensors and Sensor Fusion in Autonomous Vehicles

In this paper, we are presenting a short overview of the sensors and sensor fusion in autonomous vehicles. We focused on the sensor fusion from the key sensors in autonomous vehicles: camera, radar, and lidar. The current state-of-the-art in this area will be presented, such as 3D object detection method for leveraging both image and 3D point cloud information, moving object detection and tracking system, and occupancy grid mapping used for navigation and localization in dynamic environments. It is shown that including more sensors into sensor fusion system benefits with better performance and the robustness of the solution. Moreover, usage of camera data in localization and mapping, that is traditionally solved by radar and lidar data, improves the perceived model of the environment. Sensor fusion has a crucial role in autonomous systems overall, therefore this is one of the fastest developing areas in the autonomous vehicles domain.