Traffic Prediction System Using Machine Learning (ML)

Traffic has its own consequences and the congestion from the same leads to consumption of time, energy, frustration and gasoline almost every other day as a routine. On one side, the government is also affected by congestion from traffic as goods transportation should be done with easy flow, reduction of pollution should be ensured in certain places along with the safety measures. Globally congestion is considered a major problem that has the capability to impact every level persisting in the society. Every driver would know about the causes of traffic jams that happen usually in a journey. Unexpected delays happen due to road constructions and works, accidents. The speed of traffic flow goes down due to bad conditions of weather. When the timing of the traffic signal below par, the capacity is limited in smaller roads. A network of roads where the capacity is also seem to be limited is what usually leads to increasing congestion in traffic globally. The main objective is to classify the traffic state. In the first step we the data is analyzed which then is later pre-processed. Application of a machine learning algorithm is the third step here over dataset of traffic prediction and the performance and accuracy is calculated from the result after applying the suitable algorithm.