Open this publication in new window or tab >>2023 (English)In: 2023 IEEE Intelligent Vehicles Symposium (IV), Piscataway, NJ: IEEE, 2023Conference paper, Published paper (Refereed)
Abstract [en]
V2X Collective Perception is the principle of exchanging sensor data among V2X-capable stations, such as vehicles or roadside units, by exchanging lists of perceived objects in the 5.9 GHz frequency band for road safety and traffic efficiency. An object can be anything relevant to traffic safety, e.g.,vehicles or pedestrians. The current standardization of Collective Perception in Europe considers filtering objects for transmission based on their locally perceived dynamics and freshness to preserve channel resources. However, two remaining problems of object filtering are: information redundancy and adapting object filtering to the available channel resources. In this paper, we combine redundancy mitigation and congestion control-aware filtering. We evaluate the performance of the resulting object filtering techniques by realizing realistic, large-scale simulations of a mid-size city in Germany. We assess the performance using ascoring metric. The results show better information redundancy control and adjustable channel usage for object filtering. © Copyright 2023 IEEE
Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2023
Keywords
V2X, sensor data sharing, vehicular communications, Collective Perception, message generation
National Category
Communication Systems
Identifiers
urn:nbn:se:hh:diva-50448 (URN)10.1109/IV55152.2023.10186788 (DOI)001042247300237 ()2-s2.0-85167986317 (Scopus ID)979-8-3503-4691-6 (ISBN)979-8-3503-4692-3 (ISBN)
Conference
The 35th IEEE Intelligent Vehicles Symposium (IV 2023), Anchorage, Alaska, USA, 4-7 June, 2023
Note
As manuscript in thesis.
Funding text: This work was gratefully supported by the German Science Foundation (DFG) in project KOALA2 under number 273374642 within the priority program Cooperatively Interacting Automobiles (CoIn-Car, SPP 1835). Karlsruhe Institute of Technology also acknowledges the support from Helmholtz Program “Engineering Digital Futures”.
2023-05-152023-05-152023-11-22Bibliographically approved