mlsanityData to 14 Oct 2026

Bridge to Real Environment with Hardware-in-the-loop for Wireless Artificial Intelligence Paradigms

arXiv 2409.16968 ↗First posted 25 Sep 2024cs.LG cs.NI eess.SPcited by 0

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Abstract (arXiv)

Nowadays, many machine learning (ML) solutions to improve the wireless standard IEEE802.11p for Vehicular Adhoc Network (VANET) are commonly evaluated in the simulated world. At the same time, this approach could be cost-effective compared to real-world testing due to the high cost of vehicles. There is a risk of unexpected outcomes when these solutions are implemented in the real world, potentially leading to wasted resources. To mitigate this challenge, the hardware-in-the-loop is the way to move forward as it enables the opportunity to test in the real world and simulated worlds together. Therefore, we have developed what we believe is the pioneering hardware-in-the-loop for testing artificial intelligence, multiple services, and HD map data (LiDAR), in both simulated and real-world settings.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 21 references that are in the map. First posted on arXiv 25 Sep 2024.

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References · 1

  1. 2024Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learningcited by 3

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