Chain Branch Leaf-Gateway, a Strategy for Dynamic Clustering and Optimal Coverage of Communication for Automated Mobility - Université Gustave Eiffel Access content directly
Conference Papers Year : 2022

Chain Branch Leaf-Gateway, a Strategy for Dynamic Clustering and Optimal Coverage of Communication for Automated Mobility

Abstract

One of the main issues with embedded sensors in Automated Vehicle (AV) concerns their limited perception capabilities (limited range) and short-term reaction to only close events. However, for safer operations, AVs need to anticipate distant events. To reach this goal, it is essential to propose efficient communication architectures and strategies that guarantee a high level of Quality of Service (QoS). Therefore, cooperation among communication "nodes" is essential to establish and maintain the links between vehicles or vehicles and infrastructure. However, the communication links could be interrupted in some situations such as Vehicles leaving the area covered by the communications (vehicle alone or in low vehicle density), or the high velocity of vehicles (reduced range). This paper proposes an improvement of the Chain Branch Leaf (CBL) strategy with the implementation of a Gateway mechanism (CBL-G). The initial Vehicle-to-Vehicle (V2V) strategy is now extended with a Vehicle-to-Infrastructure (V2I) configuration in motorway areas in order to guarantee V2X architecture. CBL-G objective is to develop a dynamic communication clustering strategy with a distributed and dedicated Road Side Units (RSU) topology for optimal communication coverage. The proposed solution improves the QoS for critical functions (i.e risk assessment, accurate and distributed localization) by redirecting isolated vehicle nodes and clusters to RSUs.
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Dates and versions

hal-04095939 , version 1 (12-05-2023)

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Sabrine Belmekki, Dominique Gruyer, Charles Tatkeu. Chain Branch Leaf-Gateway, a Strategy for Dynamic Clustering and Optimal Coverage of Communication for Automated Mobility. 2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI), Oct 2022, Boston, United States. pp.1-5, ⟨10.1109/dtpi55838.2022.9998893⟩. ⟨hal-04095939⟩
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