Further We Travel the Faster We Go

Varga, Levente; Kovács, András; Tóth, Géza; Papp, István; Néda, Zoltán

doi:10.1371/journal.pone.0148913

Cited by 12 publications

(19 citation statements)

References 23 publications

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“…In general, a trip can consist of multiple connections and may in fact be multimodal (multiple components of travel) with the corresponding waiting-time distributions associated with the modes of transportation [102]. Also, it is observed that the apparent speed v increases with travel distance according to the following power-law functional form [101] v ∼ r β ,…”

Section: Physics Of Mobility 321 Distance Travel Time and Effectmentioning

confidence: 99%

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Human mobility: Models and applications

et al. 2018

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Recent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between shortrange and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.

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Section: Physics Of Mobility 321 Distance Travel Time and Effectmentioning

confidence: 99%

“…The orange dashed lines represents the best fit to | v | ∝ √ t which corresponds to a Brownian acceleration model. Figure from [103].from which the relation v ∼ √ r directly follows[101].…”

mentioning

confidence: 99%

Human mobility: Models and applications

et al. 2018

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“…Longer trips are typically taken on fast trains or planes with a small number of stops. The relation between distance and travel time is therefore not simple [12]: it has been shown that the effective speed increases with the travel distance as a square root [51], owing to the hierarchical structure of transportation systems [52] (Fig. 2).…”

Section: Mobilitymentioning

confidence: 99%

The statistical physics of cities

Barthélemy

2019

Nat Rev Phys

108

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Challenges due to the rapid urbanization of the world -especially in emerging countriesrange from an increasing dependence on energy, to air pollution, socio-spatial inequalities, environmental and sustainability issues. Modelling the structure and evolution of cities is therefore critical because policy makers need robust theories and new paradigms for mitigating these problems. Fortunately, the increased data available about urban systems opens the possibility of constructing a quantitative 'science of cities' with the aim of identifying and modelling essential phenomena. Statistical physics plays a major role in this effort by bringing tools and concepts able to bridge theory and empirical results. This Perspective illustrates this point by focusing on fundamental objects in cities: the distribution of urban population, segregation phenomena and spin like models, the polycentric transition of the activity organization, energy considerations about mobility and models inspired by gravity and radiation concepts, CO 2 emitted by transport, and finally scaling that describes how various socio-economical and infrastructures evolve when cities grow.

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“…Recently our group revealed an interesting dynamical scaling between travel time and travel distance (measured along the geodesic lines), holding on ten orders of spatial magnitudes for human traveling modes 18 . The coarse-grained result is that the estimated average travel time scales roughly proportionally with the square root of the travel distance.…”

Section: Introductionmentioning

confidence: 99%

Scaling in the space-time of the Internet

Papp

Varga

Afifi

et al. 2019

Sci Rep

Self Cite

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The Internet on the router level, is a complex network embedded in a geographical space. We provide experimental evidences suggesting that the average travel time for a message, with fixed length, increases roughly as the square root of the geographical distance. To understand this scaling law and other measurable topological properties of the Internet as a graph, we introduce and study a simple network model. The model is based on a few realistic socio-economic facts/assumptions and qualitatively reproduces the experimentally observed stylized facts.

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Further We Travel the Faster We Go

Cited by 12 publications

References 23 publications

Human mobility: Models and applications

Human mobility: Models and applications

The statistical physics of cities

Scaling in the space-time of the Internet

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