TriCoD is a cooperative decision-making framework using twin-world deduction and adaptive switching between DRL and model-driven methods to enable safe, dynamic AV platooning in hybrid traffic.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
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Towards Safe and Robust Autonomous Vehicle Platooning: A Self-Organizing Cooperative Control Framework
TriCoD is a cooperative decision-making framework using twin-world deduction and adaptive switching between DRL and model-driven methods to enable safe, dynamic AV platooning in hybrid traffic.