Khouloud Zouaidia
Papers
1
Total Citations
16
H-Index
1
About
Khouloud Zouaidia is a researcher advancing the field of autonomous vehicle decision-making through reinforcement learning. Her work focuses on developing intelligent control systems for highway scenarios, where safe and efficient navigation remains a critical challenge. In her most-cited paper, "Decision making for autonomous vehicles in highway scenarios using Harmonic SK Deep SARSA" (2022, 16 citations), she introduces a novel deep reinforcement learning approach that integrates harmonic functions with the SARSA algorithm to improve decision-making under uncertainty. This contribution addresses key limitations in traditional methods, such as poor convergence and suboptimal lane-changing behaviors, by enabling more adaptive and real-time responses in dynamic traffic environments. Her research bridges the gap between theoretical reinforcement learning and practical autonomous driving applications, offering scalable solutions for complex, multi-agent scenarios. With her work gaining traction in the autonomous systems community, Zouaidia is establishing herself as an emerging voice in safe and intelligent vehicle control, with potential implications for reducing accidents and enhancing traffic flow in future smart cities.
Research Focus
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Top Papers
- 1