IJMSS Vol.05 Issue-10, (October 2017) ISSN: 2321-1776 International Journal in IT & Engineering (Impact Factor- 6.341) A Monthly Double-Blind Peer Reviewed Refereed Open Access International Journal International Journal in IT & Engineering http://www.ijmr.net.in email id- irjmss@gmail.com Page 9 DECONGESTING TRAFFIC FLOW IN ENUGU MEGA CITY IN NIGERIA USING NEURAL NETWORK TECHNIQUE Ilo Frederick.U, Department of Electrical and Electronic Engineering, Faculty of Engineering Enugu State University of Science and Technology (ESUT) Ibekwe B.E. Department of Electrical and Electronic Engineering, Faculty of Engineering Enugu State University of Science and Technology (ESUT) Nwobodo N.H Department of computer Engineering, Faculty of Engineering Enugu State University of Science and Technology (ESUT) Abstract This work is based on improving traffic light controller using an embedded system. Neural Network was designed and programmed for the control of traffic light. The programmed Neural Network was integrated in to microcontroller for optimum performance. The main aim of this project was to control traffic light using an embedded system to monitor and control vehicular traffic flow at road intersection in Enugu Capital City. These current traffic lights in use at Enugu State Nigeria have limitations such as, poor time allocation to traffics, lack of intelligent in the control system, difficulty to manage and control traffics during pick period etc. Due to the fixed time intervals of Red, Green and amber light signals, the waiting time is more and vehicles consumes more fuel. To make traffic light more efficient, the researcher exploits the emergence of new technique known as “Intelligent Traffic Light Controller”. This makes use of Neural Networks along with embedded technology. The timing of Red, Green lights at each crossing of road will be intelligently decided based on the total traffic on all adjacent congestion. The performance of the Intelligent Traffic Light Controller was compared with the current mode Traffic Light Controller which uses microprocessors or microcontroller for its operation. From the results, it was observed that the Intelligent Traffic Light Controller is more efficient than the conventional traffic light controller in the area of time allocations to traffics. It was also observed that intelligent traffic light controller manages traffics better during pick period. The experiment was performed at Enugu State Nigeria Urban city. Keywords: Congestion. Traffic. Traffic congestion, neural network, Control.