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Predicting times of waiting on red signals using BERT
We present a method for approximating outcomes of road traffic simulations using BERT-based models, which may find applications in, e. g., optimizing traffic signal settings, especially with the presence of autonomous and connected vehicles.
Investigating performance of neural networks and gradient boosting models approximating microscopic traffic simulations in traffic optimization tasks
We analyze the accuracy of traffic simulations metamodels based on neural networks and gradient boosting models (LightGBM), applied to traffic optimization as fitness functions of genetic algorithms.
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