Springer Nature OA
open access
Near-Real-Time Traffic Risk Assessment via Deep Learning and Simulation Inference
Improving road safety requires anticipating risks rather than reacting to events after they occur. This paper proposes a meta-model-based framework for near-real-time forecasting of surrogate safety indicators within a digital twin. Using Post-Encroachment Time (PET), deep learning models approximat
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