A DRL braking controller uses RNN-detected drowsiness from ECG to adjust for action delays and achieves 99.99% collision avoidance in CARLA simulation.
A real-time and lightweight driver fatigue detection model using anchor-free and visual-attention mechanisms
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Drowsiness-Aware Adaptive Autonomous Braking System based on Deep Reinforcement Learning for Enhanced Road Safety
A DRL braking controller uses RNN-detected drowsiness from ECG to adjust for action delays and achieves 99.99% collision avoidance in CARLA simulation.