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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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
Issue number3
Publication statusPublished - Mar-2017
Externally publishedYes


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

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