This paper describes a practical dynamic route planning method using real road maps in a wide area. The maps include traffic signals, road classes, and the number of lanes. The proposed solution is using a genetic algorithm adopting viral infection. The method is to use viruses as domain specific knowledge. A part of an arterial road is regarded as a virus. A population of viruses is generated in addition to a population of routes. Crossover and infection determine the near-optimal combination of viruses. When traffic congestion frequently changes during driving, an alternative route can be selected using viruses and other routes in the population in a real time. Experiments in dynamic environments using a real road map with 28000 cars show that the proposed method is superior to the Dijkstra algorithm for use in practical car navigation devices.
Car navigation equipment in practical use has treated a route planning problem as a single-objective problem. In this paper, we formulate the problem as a dynamic multi-objective problem and show how it can be solved using a GA. There are three objective functions to optimize simultaneously in this problem: route length, travel time that changes rapidly with time, and ease of driving. The proposed method gives the Pareto-optimal set by using both the predicted traffic and a hybrid multi-objective GA (GA + Dijkstra algorithm) so that a driver can choose a favorite route after looking at feasible ones. We give the results of experiments comparing the proposed method with the Dijkstra algorithm and the single-objective GA in applications with a real road map and real traffic data in wide-area road network.
This paper addresses the problem of selecting route to a given destination on a load map under a dynamic environment. The proposed solution is using a genetic algorithm adopting viral infection. The method is to use viruses as domain specific knowledge. A part of an arterial road is regarded as a virus. We generate a population of viruses in addition to a population of routes. Crossover and infection determine the optimal combination of viruses. When trafsic congestion changes during driving, an alternative route can be generated using viruses and other routes in the population in the shortest time. Experiments using actual road maps show the infection is effective for the problem.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.