Multi-Object Tracking for Collision Avoidance Using Multiple Cameras in Open RAN Networks
This addresses collision avoidance in vehicular scenarios for improved safety, but it appears incremental as it focuses on a more realistic network implementation.
The paper tackles multi-object detection and tracking for collision avoidance in vehicular scenarios using multiple cameras and Open RAN networks, implementing a more realistic network setup compared to prior work.
This paper deals with the multi-object detection and tracking problem, within the scope of open Radio Access Network (RAN), for collision avoidance in vehicular scenarios. To this end, a set of distributed intelligent agents collocated with cameras are considered. The fusion of detected objects is done at an edge service, considering Open RAN connectivity. Then, the edge service predicts the objects trajectories for collision avoidance. Compared to the related work a more realistic Open RAN network is implemented and multiple cameras are used.