Reinforcement Learning for Autonomous Driving

Advancing autonomous vehicle technology through cutting-edge AI.

About the Research

Reinforcement learning (RL) is transforming autonomous driving by enabling vehicles to learn from their environment and make intelligent decisions. My focus is on designing RL models for complex driving scenarios, including lane changes, obstacle avoidance, and dynamic traffic systems.

Research Highlights

Highway Scenario Simulation

Developed RL-based control algorithms for safe and efficient highway lane changes in CARLA simulation.

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End-to-End Autonomous Driving

Explored reinforcement learning approaches for fully autonomous driving in urban environments.

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Contact Me

If you'd like to collaborate or discuss ideas, feel free to reach out!

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