Flow based traffic congestion prediction and intelligent signalling using Markov decision process

As an advancement vehicular traffic in urban areas, traffic congestion mitigation is a serious problem. In order to reduce traffic congestion at intersections intelligent signaling mechanisms required. This work proposes the design of a system that utilizes and efficiently manages traffic light controllers according to the congestion predicted at each line using real time data. At each signal change, the optimal signal duration will be calculated by computing a congestion factor which will make use of present traffic conditions and a predicted value which is based on historic traffic conditions. The work in this paper adopts to optimize a standard traffic a junction of two roads, one with North-South orientation and other with East — West orientation stop light dynamically with queue leaning algorithm.