Dynamics of Decentralized Multi-Agent Systems for Implementing Tradable Network Permits

Abstract

This paper proposes a multi-agent system for implementing tradable bottleneck permits for general transportation networks. The aim of the proposed system is to achieve the socially optimal state in which total transportation cost is minimized by decentralized behavior of agents. As a concrete step of designing the proposed system, we first define some micro behavior rules of the agents. We then derive day-to-day dynamics of aggregated (macroscopic) variables (i. e. flows and permits prices) from the micro behavior rules. By analyzing the macro dynamics, we prove that the mean dynamics of aggregated variables converges to the socially optimal state.