Publication

Density Flow in Dynamical Networks via Mean-Field Games

Bauso, D., Zhang, X. & Papachristodoulou, A., Mar-2017, In : IEEE Transactions on Automatic Control. 62, 3, p. 1342-1355 14 p.

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  • Xuan-Antonis-Journal13-TAC2col

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  • Density Flow in Dynamical Networks

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DOI

Current distributed routing control algorithms for dynamic networks model networks using the time evolution of density at network edges, while the routing control algorithm ensures edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We rearrange the density model to recast the problem within the framework of mean-field games. In doing that, we illustrate an extended state-space solution approach and we study the stochastic case where the density evolution is driven by a Brownian motion. Further, we investigate the case where the density evolution is perturbed by a bounded adversarial disturbance. For both the stochastic and the worst-case scenarios, we provide conditions for the density to converge to a pre-assigned set. Moreover, we analyze such conditions from two different perspectives, repeated games with vector payoffs and inclusion theory.

Original languageEnglish
Pages (from-to)1342-1355
Number of pages14
JournalIEEE Transactions on Automatic Control
Volume62
Issue number3
Publication statusPublished - Mar-2017
Externally publishedYes

    Keywords

  • Control engineering, decentralized control, intelligent transportation systems, traffic control, STOCHASTIC APPROXIMATIONS, DIFFERENTIAL-INCLUSIONS, UNKNOWN INPUTS, PART II, RESILIENCE, FAILURES, SYSTEMS

ID: 72166426