Stability and optimality of multi-scale transportation networks with distributed dynamic tolls

TL;DR

This paper demonstrates that decentralized dynamic tolls can stabilize multi-scale transportation networks around equilibrium points and social optima without requiring global network information, using local computations and feedback control.

Contribution

The study introduces a class of decentralized feedback toll policies that guarantee stability and optimality in complex transportation networks without global data.

Findings

Decentralized tolls stabilize the network around Wardrop equilibrium.

Dynamic marginal cost tolls ensure stability at the social optimum.

Feedback toll policies perform well both asymptotically and during transients.

Abstract

We study transportation networks controlled by dynamical feedback tolls. We consider a multiscale transportation network model whereby the dynamics of the traffic flows are intertwined with those of the drivers' route choices. The latter are influenced by the congestion status on the whole network as well as dynamic tolls set by the system operator. Our main result shows that a broad class of decentralized congestion-dependent tolls globally stabilise the transportation network around a Wardrop equilibrium. Moreover, using dynamic marginal cost tolls, stability of the transportation network can be guaranteed around the social optimum traffic assignment. This is particularly remarkable as the considered decentralized feedback toll policies do not require any global information about the network structure or the exogenous traffic load on the network or state and can be computed in a fully local way. We also evaluate the performance of these feedback toll policies both in the asymptotic and during the transient regime, through numerical simulations.