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Fundamental to many transportation network studies, traffic flow models can be used to describe traffic dynamics determined by drivers' car-following, lane-changing, merging, and diverging behaviors. In this study, we develop a…

Dynamical Systems · Mathematics 2013-07-31 Wen-Long Jin

The mathematical approaches for modeling dynamic traffic can roughly be divided into two categories: discrete packet routing models and continuous flow over time models. Despite very vital research activities on models in both categories,…

Computer Science and Game Theory · Computer Science 2022-12-09 Leon Sering , Laura Vargas Koch , Theresa Ziemke

Bifurcation phenomena in nonlinear dynamical systems often lead to multiple coexisting stable solutions, particularly in the presence of symmetry breaking. Deterministic machine learning models are unable to capture this multiplicity,…

Machine Learning · Computer Science 2026-01-26 Fleur Hendriks , Ondřej Rokoš , Martin Doškář , Marc G. D. Geers , Vlado Menkovski

We study a class of dynamical multi-commodity flow networks in transportation networks. These are modeled as dynamical systems describing the evolution of the densities of a number of different commodities across the cells of a…

Dynamical Systems · Mathematics 2025-08-26 Davide Sipione , Giacomo Como

Stable flows generalize the well-known concept of stable matchings to markets in which transactions may involve several agents, forwarding flow from one to another. An instance of the problem consists of a capacitated directed network, in…

Discrete Mathematics · Computer Science 2018-12-27 Ágnes Cseh , Jannik Matuschke

A new time discretization scheme for the numerical simulation of two-phase flow governed by a thermodynamically consistent diffuse interface model is presented. The scheme is consistent in the sense that it allows for a discrete in time…

Analysis of PDEs · Mathematics 2014-02-27 Harald Garcke , Michael Hinze , Christian Kahle

Dynamic user equilibrium (DUE) is the most widely studied form of dynamic traffic assignment, in which road travelers engage in a non-cooperative Nash-like game with departure time and route choices. DUE models describe and predict the…

Optimization and Control · Mathematics 2018-10-02 Ke Han , Gabriel Eve , Terry Friesz

This paper considers a population process on a dynamically evolving graph, which can be alternatively interpreted as a queueing network. The queues are of infinite-server type, entailing that at each node all customers present are served in…

Probability · Mathematics 2020-01-01 Michel Mandjes , Nicos Starreveld , René Bekker

When a fluid comprised of multiple phases or constituents flows through a network, non-linear phenomena such as multiple stable equilibrium states and spontaneous oscillations can occur. Such behavior has been observed or predicted in a…

Fluid Dynamics · Physics 2015-06-05 Casey M. Karst , Brian D. Storey , John B. Geddes

We propose a model of discrete time dynamic congestion games with atomic players and a single source-destination pair. The latencies of edges are composed by free-flow transit times and possible queuing time due to capacity constraints. We…

Computer Science and Game Theory · Computer Science 2019-01-03 Marco Scarsini , Marc Schröder , Tristan Tomala

Fluid models have become an important tool for the study of many-server queues with general service and patience time distributions. The equilibrium state of a fluid model has been revealed by Whitt (2006) and shown to yield reasonable…

Probability · Mathematics 2013-08-27 Zhenghua Long , Jiheng Zhang

We study dynamical transportation networks in a framework that includes extensions of the classical Cell Transmission Model to arbitrary network topologies. The dynamics are modeled as systems of ordinary differential equations describing…

Optimization and Control · Mathematics 2014-10-28 Enrico Lovisari , Giacomo Como , Anders Rantzer , Ketan Savla

We introduce temporal flows on temporal networks, i.e., networks the links of which exist only at certain moments of time. Such networks are ephemeral in the sense that no link exists after some time. Our flow model is new and differs from…

Data Structures and Algorithms · Computer Science 2017-01-23 Eleni C. Akrida , Jurek Czyzowicz , Leszek Gasieniec , Lukasz Kuszner , Paul G. Spirakis

We develop a flow renormalization approach for periodically-driven quantum systems, which reveals prethermal dynamical regimes and associated timescales via direct correspondence between real time and flow time behavior. In this formalism,…

Quantum Physics · Physics 2021-03-16 Martin Claassen

The present study is based on a recent success of the second-order stochastic fluctuation theory in describing time autocorrelations of equilibrium and nonequilibrium physical systems. In particular, it was shown to yield values of the…

Statistical Mechanics · Physics 2017-08-23 Roman Belousov , E. G. D. Cohen , Lamberto Rondoni

Increasing concerns on the security and quality of water distribution systems (WDS), call for computational tools with performance guarantees. To this end, this work revisits the physical laws governing water flow and provides a hierarchy…

Optimization and Control · Mathematics 2020-10-21 Manish K. Singh , Vassilis Kekatos

Resilience 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…

Systems and Control · Computer Science 2019-01-29 Giacomo Como

We propose a macroscopic traffic network flow model suitable for analysis as a dynamical system, and we qualitatively analyze equilibrium flows as well as convergence. Flows at a junction are determined by downstream supply of capacity as…

Systems and Control · Computer Science 2015-05-25 Samuel Coogan , Murat Arcak

Scientific data, from cellular snapshots in biology to celestial distributions in cosmology, often consists of static patterns from underlying dynamical systems. These snapshots, while lacking temporal ordering, implicitly encode the…

Machine Learning · Computer Science 2025-09-23 Yanbo Zhang , Michael Levin

Temporal interaction networks capture the history of activities between entities along a timeline. At each interaction, some quantity of data (money, information, kbytes, etc.) flows from one vertex of the network to another. Flow-based…

Databases · Computer Science 2020-03-05 Chrysanthi Kosyfaki , Nikos Mamoulis , Evaggelia Pitoura , Panayiotis Tsaparas