Vehicle Speed Prediction with Convolutional Neural Networks for ITS

Accurate vehicle speed prediction is one of the important issues for achieving advanced intelligent transportation systems (ITS). There are two main methods for vehicle speed prediction, specifically, the statistical prediction and neural network-based approach. However, most existing neural network-based approaches use recurrent neural networks, which can not address the spatial characteristics of traffic flows. In this paper, we propose a convolutional neural network-based approach for a better estimation of vehicle traffics.