Design and implementation of a concept for optimizing traffic systems using location-based car information (digital pheromones).
Social insects perform complex, self-organizing tasks within a collective by using pheromone-based indirect communication (swarm intelligence). Inspired by these potentials of nature, this concept is possibly also a paradigm for controlling traffic, for collectively recognizing, disintegrating and avoiding traffic congestion without central control instances. Vehicles equipped with location and communication technology act like individual insects and virtually deposit digital pheromones on the road indicating the intense of traffic and enabling other vehicles to indirectly benefit from the trail.
This research project investigates a technical implementation of swarm intelligence applied to the traffic system and evaluates different evasion strategies for vehicles. Using a micro-simulation environment capable of simulating real city networks, various traffic experiments should empirically prove the hypothesis of a self-organizing effect concerning the traffic flow in pheromone-based systems.
Taking nature as an inspiration for solving complex tasks, the ant-based pheromone principle has provided the solution pattern for investigating an alternative, decentralized approach for traffic control with self-organizing capabilities. The use of a micro-simulator has proved the validity of the concept to be applied in traffic networks with ameliorations up to 30%, which indirectly implicates a positive impact in respect to fuel consumption, air pollution and economic issues.
Contact: Wolfgang Narzt