Self-Organization in Trafric Networks by Digital Pheromones

Nature often provides excellent patterns for the solution of technical problems and challenges: The principle of swarm intelligence e.g., is imitated by a manifold of optimization algorithms, where organisms mark their local environment in order to indirectly communicate with their conspecifics and to consequently solve complex problems in the collective. Emerging positioning and communication technologies allow extending swarm intelligence to the traffic system. Vehicles equipped with sensors, actuators and wireless communication technology virtually annotate their local environment for indirect communication and therefore form a smart collective with self-organizing capabilities following the example of nature. This paper presents and empirically verifies a decentralized self-organizing traffic flow model using a complex micro simulator capable of simulating real city networks based on authentic data acquisitions.