多摄像头协同追踪车辆轨迹，实现开放无线接入网下的防碰撞预警。
Multi-Object Tracking for Collision Avoidance Using Multiple Cameras in Open RAN Networks
- 分布式智能代理结合多摄像头数据，在边缘服务融合目标信息。
- 基于开放无线接入网环境，实现车辆轨迹预测与碰撞风险评估。
- 适用于车联网场景，适合关注边缘计算与智能交通的开发者。
本文研究开放无线接入网络（Open RAN）环境下多目标检测与追踪问题，旨在实现车辆场景中的碰撞规避。为此，部署一组与摄像头共置的分布式智能代理，通过开放RAN连接将检测到的目标信息在边缘服务处进行融合，进而预测目标轨迹以实现碰撞规避。相较于已有工作，本方案采用更贴近现实的Open RAN网络架构，并集成多摄像头协同感知，提升了系统实用性与实时性。
原文摘要 · Abstract (English)
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.
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