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Simulation-based Performance Optimization of V2X Collective Perception by Adaptive Object Filtering
Halmstad University, School of Information Technology. Technische Hochschule Ingolstadt, CARISSMA, Ingolstadt, Germany.ORCID iD: 0000-0001-6238-1628
Technische Hochschule Ingolstadt, CARISSMA, Ingolstadt, Germany; Fraunhofer IVI, Technische Universität Dresden, Dresden, Germany.
Halmstad University, School of Information Technology. Karlsruhe Institute of Technology, Universität Karlsruhe, Karlsruhe, Germany.ORCID iD: 0000-0003-4894-4134
Technische Hochschule Ingolstadt, CARISSMA, Ingolstadt, Germany.
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 [en]
V2X, sensor data sharing, vehicular communications, Collective Perception, message generation
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:hh:diva-50448DOI: 10.1109/IV55152.2023.10186788ISI: 001042247300237Scopus ID: 2-s2.0-85167986317ISBN: 979-8-3503-4691-6 (electronic)ISBN: 979-8-3503-4692-3 (print)OAI: oai:DiVA.org:hh-50448DiVA, id: diva2:1757138
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”.

Available from: 2023-05-15 Created: 2023-05-15 Last updated: 2023-11-22Bibliographically approved
In thesis
1. Sensor Data Sharing in V2X Communications: Protocol Design and Performance Optimization of Collective Perception
Open this publication in new window or tab >>Sensor Data Sharing in V2X Communications: Protocol Design and Performance Optimization of Collective Perception
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Sensor data sharing involves exchanging sensor data among multiple devices, systems, or platforms through various means, such as wired or wireless communication, cloud storage, and distributed computing. In Vehicle-to-Everything (V2X) communication, sensor data sharing is known as Collective Perception (CP). V2X Collective Perception is the principle of exchanging sensor data among V2X-capable stations, such as vehicles, vulnerable road users, or roadside units, by exchanging lists of perceived objects in the allocated 5.9 GHz frequency band for road safety and traffic efficiency. An object can be anything relevant to traffic safety and is described using its characteristics such as position, heading, and velocity. Objects are detected thanks to sensors such as cameras, LiDARs, and radars mounted on V2X stations. This thesis investigates the message generation rule for CP, specifically how often and with which objects a Collective Perception Message (CPM) should be generated for transmission. The contained studies focus on the challenges posed by the limited bandwidth available in the 5.9 GHz channel against the object selection for inclusion in CPMs. In the first part of the realized studies, the protocol design and the requirements of CP are comprehended from the network and application-related aspects, concluding that the process of filtering objects is necessary to control the channel usage of CP. Moreover, results show that object filtering is only beneficial in high-traffic density scenarios and should not be applied when channel resources are plenty available. In the second part, methods are developed and assessed to adapt the object filtering mechanism to the available channel resources and control information redundancy, i.e., controlling the number of vehicles transmitting updates about the same objects. Through a combination of theoretical analysis, large-scale simulations, and experimental evaluation, this thesis provides a better understanding of the requirements of CP for object filtering and shows the benefits of a developed novel algorithm to adapt object filtering to the available channel resources. Additionally, it elaborates on new metrics and provides a requirements analysis and performance assessment of selected information redundancy reduction techniques. Finally, the results show that combining both approaches enables efficient control of information redundancy while allowing efficient channel resource usage.

Place, publisher, year, edition, pages
Halmstad: Halmstad University Press, 2023. p. 43
Series
Halmstad University Dissertations ; 97
Keywords
V2X, sensor data sharing, vehicular communications, Collective Perception, data congestion, Decentralized Congestion Control
National Category
Communication Systems
Identifiers
urn:nbn:se:hh:diva-50463 (URN)978-91-89587-06-9 (ISBN)978-91-89587-07-6 (ISBN)
Public defence
2023-06-09, Wigforssalen, Kristian IV:s väg 3, Halmstad, 13:15 (English)
Opponent
Supervisors
Projects
KOALA2 under number 273374642 within the priority program Cooperatively Interacting Automobiles (CoIn-Car, SPP 1835).
Available from: 2023-05-23 Created: 2023-05-18 Last updated: 2023-05-23Bibliographically approved

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