Autonomous Vehicle Latency Optimisation Using DRL -- 2
Budget: ₹12,500 – ₹37,500 INR
In this project, I am seeking exceptional support to enhance the performance of connected autonomous vehicles, focusing on lane change decisions. My objectives are:
- Minimization of latency, with specific focus on the efficiency of vehicular movement
- Integration of Nash equilibrium game theory
- Implementation of a soft actor critic approach
Subsequently, a comprehensive evaluation is expected, comparing this integrated approach with established ones such as TD3 (Twin delayed deep deterministic), DDPG, and DQN. The ultimate aim is to identify which method performs best in terms of latency minimization.
Skills and Experience:
- Proficiency in Matlab is crucial
- Deep understanding of Nash Equilibrium Game Theory
- Profound knowledge in Deep Reinforcement Learning, specifically Soft Actor Critic Approach, TD3, DDPG, and DQN
- Solid background in Autonomous Vehicle Systems and latency optimization.
- Minimization of latency, with specific focus on the efficiency of vehicular movement
- Integration of Nash equilibrium game theory
- Implementation of a soft actor critic approach
Subsequently, a comprehensive evaluation is expected, comparing this integrated approach with established ones such as TD3 (Twin delayed deep deterministic), DDPG, and DQN. The ultimate aim is to identify which method performs best in terms of latency minimization.
Skills and Experience:
- Proficiency in Matlab is crucial
- Deep understanding of Nash Equilibrium Game Theory
- Profound knowledge in Deep Reinforcement Learning, specifically Soft Actor Critic Approach, TD3, DDPG, and DQN
- Solid background in Autonomous Vehicle Systems and latency optimization.