Novel traffic signal timing adjustment strategy based on Genetic Algorithm
Journal
Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
Pages
2353-2360
Date Issued
2014
Author(s)
Abstract
Traffic signal timing optimization problem aims at alleviating traffic congestion and shortening the average traffic time. However, most existing research considered only the information of one or few intersections at a time. Those local optimization methods may experience a decrease in performance when facing large-scale traffic networks. In this paper, we propose a cellular automaton traffic simulation system and conduct tests on two different optimization schemes. We use Genetic Algorithm (GA) for global optimization and Expectation Maximization (EM) as well as car flow for local optimization. Empirical results show that the GA method outperforms the EM method. Then, we use linear regression to learn from the global optimal solution obtained by GA and propose a new adjustment strategy that outperforms recent optimization methods. © 2014 IEEE.
Other Subjects
Genetic algorithms; Global optimization; Maximum principle; Timing circuits; Traffic congestion; Expectation Maximization; Global optimal solutions; Local optimization methods; Local optimizations; Optimization method; Optimization scheme; Traffic signal timings; Traffic simulations; Traffic signals
Type
conference paper