Traffic congestion is a serious problem around the world and to a great extent influences
urban communities in various manners including increased stress levels, delayed deliveries,
fuel wastage, and monetary losses. Therefore, an accurate congestion prediction algorithm
to limit these misfortunes is fundamental. This paper presents a comparative study of traffic
congestion prediction systems including decision tree, logistic regression, and neural
networks. Five days of traffic information (1,231,200 samples) are utilized to drive the …

In recent years, there has been a progressive increment in traffic around the world causing
pollutions, congestions, and accidents. Traffic congestion is the most widely recognized
major issue and has been becoming a challenge for most cities and possibly causes low
transportation efficiency, significant greenhouse gas emissions, and a lower quality of life for
urban residents. For routing services and to ensure open security, timely Prediction
information is necessary to decrease ongoing congestion problems in real-time response …