Implementing a Tollgate Queue Selector Based on Genetic Algorithm

Abstract

In this work, an intelligent highway tollgate selector based on genetic algorithm is explored and simulated extensively to allow vehicles to enter or exit the tollbooth as quickly and conveniently as possible. Road user convenience is measured in terms of waiting time and queue length, while infrastructure efficiency is evaluated in terms of the server utilization. Our exploratory genetic-based policy (GAQ) is compared to the shortest queue (SQ) and fuzzy logic-based (FLCQ) policies. GAQ provides an improved performance when compared to SQ, but is outperformed by FLCQ during fast service times. Given these observations, we then provided suggestions to improve the GAQ performance.