Marginal cost pricing and multi-criteria routing in a distributed swarm-intelligence approach for online vehicle guidance

In this paper we investigate the effects of marginal cost pricing and multi-criteria routing as an addition of our distributed real-time vehicle guidance protocol BeeJamA. BeeJamA is is honey bee-inspired swarm intelligence approach for minimizing individual travel times based on a vehicle-to-infrastructure architecture. We propose changes to the swarm behavior allowing for efficient dissemination of marginal costs and multi-criteria routing information. In literature, marginal cost pricing is known as a possibility for reducing global travel times, potentially to the disadvantage of individual travel times. Although we can confirm an improvement over the plain BeeJamA protocol for a microscopic simulation setup, marginal cost pricing could not outperform a path reservation variant of BeeJamA. Distributed routing protocols for computer networks and particularly for vehicle routing often do not provide for multi-criteria decisions and BeeJamA was no exception so far. So, as a second contribution of this paper, the protocol is complemented by multi-criteria routing concepts.