SIGNAL TIMING DETERMINATION USING GENETIC ALGORITHMS

The implementation of a genetic algorithm (GA) (an artificial intelligence technique) to produce optimal or near-optimal intersection traffic signal timing strategies is described. The focus is on examining this application within a simple traffic situation, giving the reader a clear understanding of how the genetic algorithm is used. The problem involves finding a signal timing strategy that produces the smoothest traffic flow with the least average automobile delay. The problem domain has many tentative solutions. Therefore, signal timing design is expected to benefit from the parallel, global, and robust search characteristics of GAs. This gain is realized on a simulated four-intersection traffic network in the current implementation. The GA, by considering how traffic moves among multiple intersections (through simulation), can find a logical, near-optimal timing configuration. When this timing configuration is used in the corresponding real-world traffic situation, minimal total automobile delay is expected.