Multi-class real-time crash risk forecasting using convolutional neural network: Istanbul case study

The performance of an artificial neural network (ANN) in forecasting crash risk is shown in this paper. To begin, some traffic and weather data are acquired as raw data. This data is then analyzed, and relevant characteristics are chosen to utilize as input data based on additional tree and Pearson correlation. Furthermore, crash and non-crash time data are separated; then, feature values for crash and non-crash events are written in three four-minute intervals prior to the crash and non-crash events …

acquired ann artificial case case study class convolutional neural network cs.lg data forecasting istanbul network neural network paper performance raw real-time risk study traffic tree weather weather data