Short Term Predictions of Traffic Flow Characteristics using ML Techniques

This research article proposes a new model for traffic volume prediction, where it can be effectively used for transportation domain particularly in safety planning, management and assessment at any time. Various prediction methods are proposed for predicting the traffic flow, by including historical method, real-time method, time series analysis, but the precision and efficiency of time in forecasting are a couple of difficult contradictions. Real-time traffic information prediction with ANN and SVR are applied for developing an effective and efficient traffic prediction. This study develops the model for prediction of traffic volume for Nizampet road stretch, an urban area by analyzing the measured data in city of Hyderabad. In this study the artificial neural network model is best suited to Nizampet road stretch as the R-square value is 0.89 and performance measures are less compared with SVR model.