An Approach of Short Term Road Traffic Flow Forecasting Using Artificial Neural Network

An Approach of Short Term Road Traffic Flow Forecasting Using Artificial Neural Network

In recent days, road traffic management and congestion control has become major problems in any busy junction in Hyderabad city. Hence short term traffic flow forecasting has gained greater importance in Intelligent Transport System (ITS). Artificial Neural Network (ANN) models have been fruitfully applied for classification and prediction of time series. In this chapter, an attempt has been made to model and forecast short-term traffic flow at 6.no. junction in Amberpet, Hyderabad, Telangana state, India applying Neural Network models. The traffic data has been considered for peak hours in the morning for 8A.M to 12 Noon, for 5 days. Multilayer Perceptron (MLP) network model is used in this study. These results can be considered to monitor traffic signals and explore methods to avoid congestion at that junction.

Author(s) Details

V. Sumalatha
Department of Statistics, OSMANIA University, Hyderabad, India.

Manohar Dingari
Department of Mathematics School of Technology, GITAM University, Hyderabad 502329, India.

Prof. C. Jayalakshmi
Department of Statistics, OSMANIA University, Hyderabad, India.

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