Leveraging Diminishing Demonstrations in Deep Reinforcement Learning for Decision Making of Autonomous Driving at Unsignalized Intersections

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The average success rate improved by 4.9% with the LDD-TD3 compared to standard TD3 methods.
A risk assessment module measured environmental risk for enhanced safety and strategy development.
Training incorporates diminishing demonstrations to foster superior exploration processes in agents.
Autonomous vehicles benefit from this innovative approach, enhancing decision-making in complex driving scenarios.

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Simulation reveals LDD-TD3 improves decision-making in autonomous vehicles, suggesting reduced reliance on reward shaping during training.

Wu et al. (2025) studied this question.

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Simulation reveals LDD-TD3 improves decision-making in autonomous vehicles, suggesting reduced reliance on reward shaping during training.