Convergence Of Day-to-day Traffic Flow Dynamics Under Tradable Bottleneck Permits
Free (open access)
579 - 588
K. Wada, T. Akamatsu & S. Kikuchi
Previously, Akamatsu et al. proposed \“tradable bottleneck permits” as a new transportation demand management scheme and proved the efficiency thereof for a general network. To implement such a scheme, we propose a multi-agent system for general transportation networks. The aim of this system is to achieve a socially optimal state in which the total transportation cost is minimized by the decentralized behaviour of agents. As a concrete step in designing the proposed system, we first define the micro behaviour of the agents. We also assume that the trading markets for bottleneck permits are described by a tâtonnement process. We then derive day-to-day dynamics of aggregated traffic flows and permit prices. By analyzing the macro dynamics, we prove that the mean dynamics of the aggregated variables (flows and permit prices) converge to a socially optimal state. Keywords: tradable bottleneck permits, multi-agent system, evolutionary game theory. 1 Introduction Before new road regulations are implemented, the road manager is normally required to have accurate information on the users’ behaviour (i.e., precise demands). For instance, in standard congestion pricing (see, for example Yang and Huang ), the manager needs to know the potential number of users, their desired arrival times and their value of time. It is, however, not always possible for such private information to be obtained completely and accurately. If the regulations are implemented with incomplete information, this will inevitably
tradable bottleneck permits, multi-agent system, evolutionary game theory.