Effect of Anticipatory Stigmergy on Decentralized Traffic Congestion Control

Abstract

In this paper, we propose an anticipatory stigmergy model for decentralized traffic congestion management. Managing traffic congestion is one of the main issues for smart cities, and many works have been trying to address it from the IT and Transportation research perspectives. In the literature, there are a lot of studies and practices for observing traffic flow and providing stochastic estimation about traffic congestion. Recently, dynamic coordination methods are becoming possible using the more short-term traffic information that can be provided by probe-vehicle information or smart phones. Some approaches have been trying to handle short-term traffic information in which a stigmergy-based approach is employed as an indirect communication method for cooperation among distributed agents and for managing traffic congestion. One drawback of these approaches is that handling near-future congestion remains problematic because stigmergies are basically past information. In this paper, we propose anticipatory stigmergy for sharing information on near-future traffic. In this model, all vehicles submit their near-future intention as anticipatory stigmergy to reschedule their plans. Our preliminary results demonstrate that anticipatory stigmergy works well and robust even when road construction dynamically change the road network.