Predicting driver adaptability: a computational rationality model for attention allocation in lateral vehicle control

PRACTITIONER SUMMARY: Using computational rationality with reinforcement learning, the model predicts when drivers sample visual information and how they steer under occlusion. Adjustable parameters (steering skill and internal cautiousness) enable individualised fits capturing inter-driver variability. This informs early-stage driver-attention monitoring and assistance design, strengthening safety systems and reducing reliance on laboratory testing.