TRAFFIC SIGNAL CONTROL MANAGEMENT USING AI & ML TECHNIQUES

Traffic congestion has been a problem affecting various metropolitan areas. This can result in various problems such as untimely delays to commuters, increase in carbon dioxide emissions and increase in travel time. The current traffic control systems fail to consider the volume of traffic in a particular junction i.e. the duration of the green or red signal is fixed and does not depend on the density of vehicles. Here we are reviewing the paper which provides the solution to the current traffic control systems with the help of Haar Cascade algorithm. This paper also compares the solution with the current traffic control systems as well as another solution which uses the concept of q learning.