no code implementations • 24 Jul 2023 • Agnimitra Sengupta, S. Ilgin Guler, Vikash V. Gayah, Shannon Warchol
Signalized intersections are a major safety concern for VRUs due to their complex and dynamic nature, highlighting the need to understand how these road users interact with motor vehicles and deploy evidence-based countermeasures to improve safety performance.
no code implementations • 12 Jul 2023 • Agnimitra Sengupta, S. Ilgin Guler
Hence, the transferability of these models to different locations becomes challenging, particularly when data is unavailable at the new location for model training.
no code implementations • 12 Jul 2023 • Agnimitra Sengupta, Sudeepta Mondal, Adway Das, S. Ilgin Guler
In our paper, we have shown that normalization alters the training process of deep neural networks by controlling the model's complexity and reducing the risk of overfitting to the training data.
no code implementations • 11 Jul 2023 • Agnimitra Sengupta, Adway Das, S. Ilgin Guler
Deep learning (DL) methods have outperformed parametric models such as historical average, ARIMA and variants in predicting traffic variables into short and near-short future, that are critical for traffic management.