Go to DBLP homepageTime-Dependent Ant Colony Optimization Algorithm for Solving The Fastest Traffic Path Finding Problem in a Dynamic Environment
Abstract: The goal of our project is to help drivers to preplan their trips and overcome the traffic congestion on roads. Unlike the traditional systems which provided the shortest path, travellers and salespersons need a reliable system to guide them to visit several cities or deliver merchandises in different locations in the shortest possible duration. Our system should deal with the different selected locations and get information about the congested roads and the travel time in a dynamic environment to estimate the fastest path.In this paper, we developed a system based on a time-dependent Ant Colony Optimization (ACO) algorithm to solve the problem of finding the fastest traffic path instead of the shortest path. In addition, we implemented a dynamic real tests generator based on big Global Positioning System (GPS) datasets to get information about the traffic states in roads and generate dynamic problem instances. A mobile application has been developed to provide the drivers with accurate details of the path to visit the selected locations as well as the best time to begin the trip to avoid congestion and reach their destination as fast as possible. The exhaustive experimentations have shown the capabilities of the modified time-dependent ACO in solving dynamic optimization problems.
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