NDLI: Distributed optimal equilibrium selection for traffic flow over networks

Content Provider	IEEE Xplore Digital Library
Author	Ba, Qin Savla, Ketan Como, Giacomo
Copyright Year	2015
Description	Author affiliation: Sonny Astani Department of Civil and Environmental Engineering at the University of Southern California, Los Angeles, USA (Ba, Qin; Savla, Ketan) \|\| Department of Automatic Control, Lund University, Sweden (Como, Giacomo)
Abstract	In this paper, we present two distributed algorithms to compute an equilibrium, that is optimal with respect to strictly convex and separable cost functions, for controlled traffic flow dynamics over networks under constant exogenous inflows. The dynamics is modeled in continuous time by the Cell Transmission Model and a non-FIFO Dynamic Network Loading Model, with traffic control. The two algorithms are adaptations of the alternating direct method of multipliers (ADMM) and the accelerated dual descent (ADD) method from network flow optimization literature. When the demand and supply inequality constraints in the uncontrolled dynamics are relaxed to be independent over links, the resulting feasible set is convex if the demand and supply functions are concave, thereby imparting convexity to the optimal equilibrium selection problem. Each point in the feasible set is an equilibrium for the original dynamics under appropriately designed control. For the ADMM method, explicit expressions for the primal update show that no auxiliary variables are necessary. Convergence analysis for the primal variables is also provided. The standard ADD method is extended to also incorporate non-negativity constraints on the density and flow variables, and demand and supply inequality constraints. Illustrative simulation results are also presented.
Starting Page	6942
Ending Page	6947
File Size	367580
Page Count	6
File Format	PDF
e-ISBN	9781479978861
DOI	10.1109/CDC.2015.7403313
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-15
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Load modeling Adaptation models Bismuth Heuristic algorithms Cost function Computational modeling Loading
Content Type	Text
Resource Type	Article

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