Unraveling reaction-diffusion-like dynamics in urban congestion propagation: Insights from a large-scale road network

Bellocchi, Leonardo; Geroliminis, Nikolas

doi:10.1038/s41598-020-61486-1

Cited by 34 publications

(22 citation statements)

References 54 publications

(67 reference statements)

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“…As in [19], we build the cluster of congested links, which percolates the network during rush hours. We identify roads appearing in this congested cluster during the majority of days and roads less prone to congestion and show that these results can be interpreted with a simple diffusion-based model in agreement with previous studies [15,16,22].…”

Section: Introductionsupporting

confidence: 89%

“…Rather than building a reaction-diffusion process (like has been done by Bellocchi & Geroliminis [15]), we follow the results of refs [16,22]) to build a much simpler model. In particular, it has been shown in [22] that the probability for two links to belong to the same functional cluster decays exponentially with distance and that the probability of a link to become congested decays linearly with the distance to a congestion 'seed' [16].…”

Section: Spatial Contagion Processmentioning

confidence: 99%

“…At a theoretical level, studies in [13,14] have proposed arguments to understand the emergence of congestion on the network, based on its topology. In [15], based on previous work [16], Bellocchi & Geroliminis proposed an application of reaction-diffusion equations to the case of traffic congestion, where the congestion tends to spread from a link to its neighbours. At the other end of the spectrum, Saberi et al [17] proposed a model inspired by epidemiological studies to describe the evolution of the number of congested links, regardless of the actual structure of the network.…”

Section: Introductionmentioning

confidence: 99%

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Empirical evidence for a jamming transition in urban traffic

Taillanter

Barthélemy

2021

J. R. Soc. Interface.

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Understanding the mechanisms leading to the formation and the propagation of traffic jams in large cities is of crucial importance for urban planning and traffic management. Many studies have already considered the emergence of traffic jams from the point of view of phase transitions, but mostly in simple geometries such as highways for example or in the framework of percolation where an external parameter is driving the transition. More generally, empirical evidence and characterization for a congestion transition in complex road networks are scarce, and here, we use traffic measures for Paris (France) during the period 2014–2018 for testing the existence of a jamming transition at the urban level. In particular, we show that the correlation function of delays due to congestion is a power law (with exponent η ≈ 0.4) combined with an exponential cut-off ξ . This correlation length is shown to diverge during rush hours, pointing to a jamming transition in urban traffic. We also discuss the spatial structure of congestion and identify a core of congested links that participate in most traffic jams and whose structure is specific during rush hours. Finally, we show that the spatial structure of congestion is consistent with a reaction–diffusion picture proposed previously.

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Section: Introductionsupporting

confidence: 89%

Section: Spatial Contagion Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Empirical evidence for a jamming transition in urban traffic

Taillanter

Barthélemy

2021

J. R. Soc. Interface.

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“…As shown in very recent works 4 , 5 , the congestion tends to propagate from some distributed seeds to adjacent links through diffusion-like process. Moreover, it has been observed that close links influence each others traffic state: that is, a link adjacent to a congested link has high probability to become congested later on.…”

Section: Discussionmentioning

confidence: 89%

Dynamical efficiency for multimodal time-varying transportation networks

Bellocchi

Latora

Geroliminis

2021

Sci Rep

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Spatial systems that experience congestion can be modeled as weighted networks whose weights dynamically change over time with the redistribution of flows. This is particularly true for urban transportation networks. The aim of this work is to find appropriate network measures that are able to detect critical zones for traffic congestion and bottlenecks in a transportation system. We propose for both single and multi-layered networks a path-based measure, called dynamical efficiency, which computes the travel time differences under congested and free-flow conditions. The dynamical efficiency quantifies the reachability of a location embedded in the whole urban traffic condition, in lieu of a myopic description based on the average speed of single road segments. In this way, we are able to detect the formation of congestion seeds and visualize their evolution in time as well-defined clusters. Moreover, the extension to multilayer networks allows us to introduce a novel measure of centrality, which estimates the expected usage of inter-modal junctions between two different transportation means. Finally, we define the so-called dilemma factor in terms of number of alternatives that an interconnected transportation system offers to the travelers in exchange for a small increase in travel time. We find macroscopic relations between the percentage of extra-time, number of alternatives and level of congestion, useful to quantify the richness of trip choices that a city offers. As an illustrative example, we show how our methods work to study the real network of a megacity with probe traffic data.

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“…We introduce a discrete modeling framework for simulating gradient-driven advection-dispersion-reaction physics of multispecies transport. Graph-theoretic approaches that have been proven successful in examining flow of information through large-scale real-world networks are applied (Kumar et al, 2019;Bellocchi and Geroliminis, 2020;Besse and Faye, 2021) in this study. We resort to discrete-vector calculus and use the operators defined on a finite-graph to spatially discretize and formulate the transport dynamics in the vascular domain as a "tank-in-series" model.…”

mentioning

confidence: 99%

A Graph-Based Framework for Multiscale Modeling of Physiological Transport

Maheshvare

Raha

Pal

2022

Front. Netw. Physiol.

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Trillions of chemical reactions occur in the human body every second, where the generated products are not only consumed locally but also transported to various locations in a systematic manner to sustain homeostasis. Current solutions to model these biological phenomena are restricted in computability and scalability due to the use of continuum approaches in which it is practically impossible to encapsulate the complexity of the physiological processes occurring at diverse scales. Here, we present a discrete modeling framework defined on an interacting graph that offers the flexibility to model multiscale systems by translating the physical space into a metamodel. We discretize the graph-based metamodel into functional units composed of well-mixed volumes with vascular and cellular subdomains; the operators defined over these volumes define the transport dynamics. We predict glucose drift governed by advective–dispersive transport in the vascular subdomains of an islet vasculature and cross-validate the flow and concentration fields with finite-element–based COMSOL simulations. Vascular and cellular subdomains are coupled to model the nutrient exchange occurring in response to the gradient arising out of reaction and perfusion dynamics. The application of our framework for modeling biologically relevant test systems shows how our approach can assimilate both multi-omics data from in vitro–in vivo studies and vascular topology from imaging studies for examining the structure–function relationship of complex vasculatures. The framework can advance simulation of whole-body networks at user-defined levels and is expected to find major use in personalized medicine and drug discovery.

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Unraveling reaction-diffusion-like dynamics in urban congestion propagation: Insights from a large-scale road network

Cited by 34 publications

References 54 publications

Empirical evidence for a jamming transition in urban traffic

Empirical evidence for a jamming transition in urban traffic

Dynamical efficiency for multimodal time-varying transportation networks

A Graph-Based Framework for Multiscale Modeling of Physiological Transport

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