22 citations · 82 across the 13 of their papers we have counts for
4 papers · 1 filter
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…
Multi-agent Assessment with QoS Enhancement for HD Map Updates in a Vehicular Network
Jeffrey Redondo, Nauman Aslam, Juan Zhang +1
Reinforcement Learning (RL) algorithms have been used to address the challenging problems in the offloading process of vehicular ad hoc networks (VANET). More recently, they have b…
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…
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…