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Analysis and Evaluation of Information Redundancy Mitigation for V2X Collective Perception
Technische Hochschule Ingolstadt, Ingolstadt, Germany.ORCID iD: 0000-0001-6238-1628
Technische Universität Braunschweig, Braunschweig, Germany.
Technische Universität Braunschweig, Braunschweig, Germany.
Technische Universität Braunschweig, Braunschweig, Germany.
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2022 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 10, p. 47076-47093Article in journal (Refereed) Published
Abstract [en]

Sensor data sharing enables vehicles to exchange locally perceived sensor data among each other and with the roadside infrastructure to increase their environmental awareness. It is commonly regarded as a next-generation vehicular communication service beyond the exchange of highly aggregated messages in the first generation. The approach is being considered in the European standardization process, where it relies on the exchange of locally detected objects representing anything safety-relevant, such as other vehicles or pedestrians, in periodically broadcasted messages to vehicles in direct communication range. Objects filtering methods for inclusion in a message are necessary to avoid overloading a channel and provoking unnecessary data processing. Initial studies provided in a pre-standardization report about sensor data sharing elaborated a first set of rules to filter objects based on their characteristics, such as their dynamics or type. However, these rules still lack the consideration of information received by other stations to operate. Specifically, to address the problem of information redundancy, several rules have been proposed, but their performance has not been evaluated yet comprehensively. In the present work, the rules are further analyzed, assessed, and compared. Functional and operational requirements are investigated. A performance evaluation is realized by discrete-event simulations in a scenario for a representative city with realistic vehicle densities and mobility patterns. A score and other redundancy-level metrics are elaborated to ease the evaluation and comparison of the filtering rules. Finally, improvements and future works to the filtering methods are proposed. Author

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE, 2022. Vol. 10, p. 47076-47093
Keywords [en]
collective perception, information redundancy mitigation, road safety, sensor data sharing, V2X communications
National Category
Other Health Sciences
Identifiers
URN: urn:nbn:se:hh:diva-48471DOI: 10.1109/ACCESS.2022.3170029ISI: 000793781800001Scopus ID: 2-s2.0-85129644244OAI: oai:DiVA.org:hh-48471DiVA, id: diva2:1703450
Available from: 2022-10-13 Created: 2022-10-13 Last updated: 2023-08-21Bibliographically 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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Delooz, QuentinVinel, Alexey

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