ABSTRACT
In today’s era, roadways connect cities and even countries. It is one of the most used kinds of commute used by passengers to travel and for trade practices going in and around a city. Thus, traffic plays a vital role in judging the time estimated for travel. In the fast-moving and rapidly shifting world, we need to do things and get our work done in a split second but, due to the growing population, especially in a country like India having a plethora of vehicles and commuters who travel by road, these can be of different varieties, from four-wheelers to two-wheelers. But, due to the huge population of vehicles around us, the traffic density on roads is increasing and this leads to traffic jams which are very frequent and can extend up to even hours to get into a smooth flow again. This can be very stressful in case there is some medical emergency where the patient could even die; not only this, if there is any important consignment which has to reach any industry for production or to any client, this can lead to loss and result in depreciation of GDP to some extent. Thus, we require some specialised techniques to solve this issue which we have shown in this chapter using YOLO v3 and some statistical-based analysis using images and video file images for prediction which will help to determine instances when traffic jams are about to happen and help us alert the authorities.
