| Popis: |
Cooperative Perception is an emergent technology that profits from the exchanged perception information between vehicles. However, the inconsistency resulting from the reuse of the same information is a main issue that arises. In this paper, we focus on the study of the Split Covariance Intersection Filter (SCIF), a method capable of handling both independent and arbitrarily correlated estimates and observation errors. We are interested in its use in a Cooperative Perception application to incorporate information coming from other vehicles, which may or may not have been tracked, in a generic tracking solution. A simple case study is first presented to build a deep understanding of the filter tuning, then real experiments carried out with three vehicles equipped with GNSS, camera, LiDAR and High Definition (HD) map features are reported to study how a full tracking architecture relying on SCIF behaves in a real-world situation. |
