An Adaptive Controller of Traffic Lights using Genetic Algorithms

Abstract

In this modern era of technology, time and energy are the most valuable assets of current civil societies. Due to the growing population and number of vehicles on the roads, traffic congestion is becoming an escalating complex problem, and this problem has now grown into a major issue for the urban planning authorities. Therefore, many researchers continue investigating this problem and exploiting modern science to develop reliable mathematical models, simulation scenarios and solution approaches for the traffic light control system that could optimally coordinate the traffic signals to time and reduce traffic congestion. In this paper, we propose a dynamic application that simulates many traffic light models using a Genetic algorithm. We have used the Genetic algorithm for traffic signal's time management and to compute optimal solutions for cycle times, offset times and green times according to the sequence orders of a set of traffic lights. We employed the fitness function in order to minimize the time waste on the model. The experimental prototype delivers sound results and adequate optimal solutions.