NIAIMay 28

Network Optimization Aspects of Autonomous Vehicles: Challenges and Future Directions

arXiv:2605.2951811.22 citationsh-index: 6
Predicted impact top 79% in NI · last 90 daysOriginality Synthesis-oriented
AI Analysis

It provides a comprehensive review and future directions for researchers and practitioners working on network optimization in CAVs.

This paper reviews network optimization challenges for connected and autonomous vehicles, presenting multidisciplinary methods like cooperative perception and sharing insights from experiments.

Global megatrends, such as urbanization, population growth, and emerging network solutions are accelerating the development of the Connected and Autonomous Vehicles (CAVs) industry. There are many truths, some misconceptions, and even some excitement about CAVs in the public's opinion. The main objective of the current article is to provide a comprehensive review, eliminate misconceptions, and outline the future of the network optimization aspects of autonomous vehicles by presenting various multidisciplinary methods, such as cooperative perception. Given our extensive experience with CAVs, we are aiming to share some of the insights and knowledge we have gained, along with relevant use-cases and experiment results.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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