High-optimized crash severity prediction: a calibrated, leakage-aware ensemble stacking framework for deployment-ready decision making
Predicting traffic crash severity is essential for emergency management, roadside infrastructure deployment and safety policy. The current machine learning (ML) approaches concentrate on accuracy, while overlooking the operational costs of false negatives (severe crash incidents missed) versus false positives (false...