1,721,199 research outputs found
On resilient control of dynamical flow networks
Full text linkResilience has become a key aspect in the design of contemporary infrastructure networks. This comes as a result of ever-increasing loads, limited physical capacity, and fast-growing levels of interconnectedness and complexity due to the recent technological advancements. The problem has motivated a considerable amount of research within the last few years, particularly focused on the dynamical aspects of network flows, complementing more classical static network flow optimization approaches.In this tutorial paper, a class of single-commodity first-order models of dynamical flow networks is considered. A few results recently appeared in the literature and dealing with stability and robustness of dynamical flow networks are gathered and originally presented in a unified framework. In particular, (differential) stability properties of monotone dynamical flow networks are treated in some detail, and the notion of margin of resilience is introduced as a quantitative measure of their robustness. While emphasizing methodological aspects -including structural properties, such as monotonicity, that enable tractability and scalability- over the specific applications, connections to well-established road traffic flow models are made
Evaluation of Decentralized Feedback Traffic Light Control with Dynamic Cycle Length
Full text linkAn established rule of thumb in the field of traffic light control prescribes that, during periods of higher demand, it is convenient to have longer cycles. This is in order to reduce the fraction of the cycle length when no incoming lanes receive green light. In this paper, we simulate a novel, provably stable, decentralized feedback traffic light control policy with variable cycle length. The proposed control strategy is fully decentralized and does not require any information about the network structure or the turning rates. Through simulations on a micro simulator, we compare the performance of our variable cycle length policy to a similar feedback policy with fixed cycle length and with a fixed-time control policy. The simulations show that having dynamic cycle lengths allows one to significantly reduce the overall queue lengths in the network, in both medium and low demands
From local averaging to emergent global behaviors : The fundamental role of network interconnections
Full text linkDistributed averaging is one of the simplest and most widely studied network dynamics. Its applications range from cooperative inference in sensor networks, to robot formation, to opinion dynamics. A number of fundamental results and examples scattered through the literature are gathered here and some original approaches and generalizations are presented, emphasizing the deep interplay between the network interconnection structure and the emergent global behavior
Average spectra and minimum distances of low density parity check codes over cyclic groups
No full textA Micro-Simulation Study of the Generalized Proportional Allocation Traffic Signal Control
Full text linkIn this paper, we study the problem of determining phase activations for signalized junctions by utilizing feedback, more specifically, by measure the queue-lengths on the incoming lanes to each junction. The controller we are investigating is the Generalized Proportional Allocation (GPA) controller, which has previously been shown to have desired stability and throughput properties in a continuous averaged dynamical model for queueing networks. In this paper, we provide and implement two discretized versions of the GPA controller in the SUMO micro simulator. We also compare the GPA controllers with the MaxPressure controller, a controller that requires more information than the GPA, in an artificial Manhattan-like grid. To show that the GPA controller is easy to implement in a real scenario, we also implement it in a previously published realistic traffic scenario for the city of Luxembourg and compare its performance with the static controller provided with the scenario. The simulations show that the GPA performs better than a static controller for the Luxembourg scenario, and better than the MaxPressure pressure controller in the Manhattan-grid when the demands are low
Convexity and robustness of dynamic traffic assignment and freeway network control
Full text linkWe study the use of the System Optimum (SO) Dynamic Traffic Assignment (DTA) problem to design optimal traffic flow controls for freeway networks as modeled by the Cell Transmission Model, using variable speed limit, ramp metering, and routing. We consider two optimal control problems: the DTA problem, where turning ratios are part of the control inputs, and the Freeway Network Control (FNC), where turning ratios are instead assigned exogenous parameters. It is known that relaxation of the supply and demand constraints in the cell-based formulations of the DTA problem results in a linear program. However, solutions to the relaxed problem can be infeasible with respect to traffic dynamics. Previous work has shown that such solutions can be made feasible by proper choice of ramp metering and variable speed limit control for specific traffic networks. We extend this procedure to arbitrary networks and provide insight into the structure and robustness of the proposed optimal controllers. For a network consisting only of ordinary, merge, and diverge junctions, where the cells have linear demand functions and affine supply functions with identical slopes, and the cost is the total traffic volume, we show, using the Pontryagin maximum principle, that variable speed limits are not needed in order to achieve optimality in the FNC problem, and ramp metering is sufficient. We also prove bounds on perturbation of the controlled system trajectory in terms of perturbations in initial traffic volume and exogenous inflows. These bounds, which leverage monotonicity properties of the controlled trajectory, are shown to be in close agreement with numerical simulation results
A Lyapunov Approach to Stochastic Interaction Dynamics Over Large-Scale Networks
No full textWe study stochastic interaction network models whereby a finite population of agents, identified with the nodes of a graph, update their states in response to pairwise interactions with their neighbors as well as spontaneous mutations. These include the main epidemic models, such as the Susceptible-Infected -Susceptible, the Susceptible-Infected-Recovered, and the Susceptible-Infected-Recovered-Susceptible models. We analyze the asymptotic behavior of such systems on Erdös-Rényi random graphs, in the limit as the population size grows large. Our approach is based on the use of (approximate) Lyapunov functions for Markov chains through which we can obtain stability results in terms of the corresponding invariant probabilities and on specific concentration results for Erdos-Renyi random graphs
Controlling network coordination games
Full text linkWe study a novel control problem in the context of network coordination games: the individuation of the smallest set of players capable of driving the system, globally, from one Nash equilibrium to another one. Our main contribution is the design of a randomized algorithm based on a time-reversible Markov chain with provable convergence guarantees
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