A Noval Approach for predicting on road Traffic using Hybrid approach of K Nearest Approach and Euclidean distance

Abstract

Adverse situations creep in as traffic enhances on road. This leads to significant problems for users. These problems include delay and accidents. Traffic problem is difficult to address but users can be given prior information about on road traffic so that user can take appropriate action in terms of choosing path. This research paper deals with traffic prediction to predict on road traffic using KNN and Euclidean distance mechanism. The mechanism is implied on dataset derived from online source (UCI). For demonstration three lanes are considered for prediction. Implementation is done within MATLAB. The obtained accuracy of prediction is high and mean square error is low through the proposed literature. Keywords: Traffic, Prediction, KNN, Euclidean Distance, Accuracy, Mean Square Error