A survey and tutorial that classifies redundancy mitigation strategies for vehicular collective perception into object inclusion filtering, data format optimization, and frequency management, and contrasts the 2019 and 2023 ETSI specifications.
Cooperverse: A Mobile-Edge-Cloud Framework for Universal Cooperative Perception with Mixed Connectivity and Automation
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abstract
Cooperative perception (CP) is attracting increasing attention and is regarded as the core foundation to support cooperative driving automation, a potential key solution to addressing the safety, mobility, and sustainability issues of contemporary transportation systems. However, current research on CP is still at the beginning stages where a systematic problem formulation of CP is still missing, acting as the essential guideline of the system design of a CP system under real-world situations. In this paper, we formulate a universal CP system into an optimization problem and a mobile-edge-cloud framework called Cooperverse. This system addresses CP in a mixed connectivity and automation environment. A Dynamic Feature Sharing (DFS) methodology is introduced to support this CP system under certain constraints and a Random Priority Filtering (RPF) method is proposed to conduct DFS with high performance. Experiments have been conducted based on a high-fidelity CP platform, and the results show that the Cooperverse framework is effective for dynamic node engagement and the proposed DFS methodology can improve system CP performance by 14.5% and the RPF method can reduce the communication cost for mobile nodes by 90% with only 1.7% drop for average precision.
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A Survey and Tutorial of Redundancy Mitigation for Vehicular Cooperative Perception: Standards, Strategies and Open Issues
A survey and tutorial that classifies redundancy mitigation strategies for vehicular collective perception into object inclusion filtering, data format optimization, and frequency management, and contrasts the 2019 and 2023 ETSI specifications.