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Jeffrey Redondo

5 papers hereh-index 319 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.NI3
  • cs.AI1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedMulti-agent Assessment with QoS Enhancement for HD Map Updates in a Vehicular Network

6 citations · 10 across the 5 of their papers we have counts for

collaborators
Showing cs.NIShow all

3 papers · 1 filter

cs.NI2024

Optimizing QoS in HD Map Updates: Cross-Layer Multi-Agent with Hierarchical and Independent Learning

Jeffrey Redondo, Nauman Aslam, Juan Zhang +1

The data collected by autonomous vehicle (AV) sensors such as LiDAR and cameras is crucial for creating high-definition (HD) maps to provide higher accuracy and enable a higher lev…

cs.NI2024★ 1 cited

Coverage-aware and Reinforcement Learning Using Multi-agent Approach for HD Map QoS in a Realistic Environment

Jeffrey Redondo, Zhenhui Yuan, Nauman Aslam +1

One effective way to optimize the offloading process is by minimizing the transmission time. This is particularly true in a Vehicular Adhoc Network (VANET) where vehicles frequentl…

cs.NI2024★ 3 cited

Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning

Jeffrey Redondo, Zhenhui Yuan, Nauman Aslam

High-definition (HD) Map systems will play a pivotal role in advancing autonomous driving to a higher level, thanks to the significant improvement over traditional two-dimensional…

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