A New Approach for Accurate Path Prediction Using Multiple Prediction System

Abstract

Emergency vehicle management (EVM) is one of the highly significant tasks in the traffic control system. Accurate path prediction system can be very helpful to emergency vehicles like ambulance, fire engine, and police vehicles, military vehicles etc. In this work, multiple path emergency vehicle management using Multiple classifier with maximum voting (MP-EVM-MCMV) technique is proposed to predict the highly accurate route. The primary objective of this work is finding appropriate path and reach destination as possible using the MP-EVM-MCMV system. MP-EVM-MCMV system works on the basis of three classifiers based on maximum voting. Artificial neural network (ANN), k-nearest neighbors (KNN) and support vector machine (SVM) are used as classifiers. The analysis results show that the EVM-MCMV attains an ACC of 96.5% average for various path from different area.