Towards Design Principles for Optimal Transport Networks

Li, G.; Reis, Saulo D. S.; Moreira, André A.; Havlin, Shlomo; Stanley, H. Eugene; Andrade, José S.

doi:10.1103/physrevlett.104.018701

Cited by 164 publications

(153 citation statements)

References 21 publications

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“…The allocation procedure is finished when the pool of available cities is exhausted. We must note that a comparison with a socially optimal network (Li et al 2010) is also useful here; further work is needed to establish norms for optimality and generate a meaningful optimum.…”

Section: Population Distribution Network Speeds and Network Ownershipmentioning

confidence: 99%

“…This is presumably because of limited data availability, computational limitations and difficulties in reproducing topologically realistic links or 'shortcuts' (Li et al 2010). The aim of this paper is to introduce transport link scanner (TLS), an agent-based model that simulates the overall geographic diffusion of a transport network through the individual investment decisions that drive network expansion, and to demonstrate that it is able to reproduce a historical network expansion process reasonably accurate.…”

Section: Introductionmentioning

confidence: 99%

“…In the 1960s, conceptual and empirical modelling efforts have been undertaken by quantitative geographers (Taaffe et al 1963;Warntz 1966;Kolars and Malin 1970). More recently, network optimality and bi-level optimization methods (Patriksson 2008;Youn et al 2008;Li et al 2010), the role of selforganization and the role of ownership (Xie and Levinson 2007) have been investigated in controlled conditions. This has been followed by empirically based exercises to test heuristic network design optimization methods (Vitins and Axhausen 2009), to understand the driving forces of network growth (Rietveld and Bruinsma 1998) and the role of first mover advantages and to forecast future network investments in a fairly mature transport system (Levinson et al 2012).…”

Section: Introductionmentioning

confidence: 99%

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Transport link scanner: simulating geographic transport network expansion through individual investments

Jacobs‐Crisioni

Koopmans²

2016

J Geogr Syst

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This paper introduces a GIS-based model that simulates the geographic expansion of transport networks by several decision-makers with varying objectives. The model progressively adds extensions to a growing network by choosing the most attractive investments from a limited choice set. Attractiveness is defined as a function of variables in which revenue and broader societal benefits may play a role and can be based on empirically underpinned parameters that may differ according to private or public interests. The choice set is selected from an exhaustive set of links and presumably contains those investment options that best meet private operator's objectives by balancing the revenues of additional fare against construction costs. The investment options consist of geographically plausible routes with potential detours. These routes are generated using a fine-meshed regularly latticed network and shortest path finding methods. Additionally, two indicators of the geographic accuracy of the simulated networks are introduced. A historical case study is presented to demonstrate the model's first results. These results show that the modelled networks reproduce relevant results of the historically built network with reasonable accuracy.

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Section: Population Distribution Network Speeds and Network Ownershipmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Transport link scanner: simulating geographic transport network expansion through individual investments

Jacobs‐Crisioni

Koopmans²

2016

J Geogr Syst

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“…It has been shown that the design and development of optimal navigation can be achieved exploiting shortest paths, either with local knowledge and the presence of long-range connections in a lattice network (25) or by imposing cost constraints, regardless of the available (global or local) information (26). However, in the presence of random failures it is not possible to have real-time information about the subsequent congestion.…”

mentioning

confidence: 99%

Navigability of interconnected networks under random failures

Domenico

Solé-Ribalta

Gómez

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

431

391

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Assessing the navigability of interconnected networks (transporting information, people, or goods) under eventual random failures is of utmost importance to design and protect critical infrastructures. Random walks are a good proxy to determine this navigability, specifically the coverage time of random walks, which is a measure of the dynamical functionality of the network. Here, we introduce the theoretical tools required to describe random walks in interconnected networks accounting for structure and dynamics inherent to real systems. We develop an analytical approach for the covering time of random walks in interconnected networks and compare it with extensive Monte Carlo simulations. Generally speaking, interconnected networks are more resilient to random failures than their individual layers per se, and we are able to quantify this effect. As an application--which we illustrate by considering the public transport of London--we show how the efficiency in exploring the multiplex critically depends on layers' topology, interconnection strengths, and walk strategy. Our findings are corroborated by data-driven simulations, where the empirical distribution of check-ins and checksout is considered and passengers travel along fastest paths in a network affected by real disruptions. These findings are fundamental for further development of searching and navigability strategies in real interconnected systems.N etwork theory has been revealed to be a perfect instrument to model the structure of complex systems and the dynamical process in which they are involved. However, the classical approach does not take into account the possibility that agents can be networked in different ways, and with different intensity, on multiple layers simultaneously. As an example, in the case of social sciences the same user might choose to subscribe to two or more online social networks and to build different social relationships with different users on each social platform (e.g., LinkedIn for the network of professional contacts, Facebook for the network of friends, etc.). Another example is represented by transportation networks in a city: the network of bus stops, the first layer, is different from the tube network, the second layer, but people make use of both by combining paths to move from one place to another within the city. The cases where one vertex is not present in the full multiplex can be accounted for by including it as an isolated vertex in the layers where it is missing, without altering either topological or dynamical properties of the interconnected network.The existence of such multiple connections on different layers invites a generalization of the theory of complex networks to cope with multilayer interconnected networked systems. More specifically, very recent studies focused on a particular type of multilayer network, the multiplex, where each agent participates in different layers simultaneously, like our previous example in the case of online social networks. Indeed, the actors (vertices) in every layer are t...

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“…In recent years, several public transport systems (PTS) have been investigated using various concepts of the statistical physics of complex networks [10][11][12][13][14][15][16][17][18][19][20]. Among them, many studies have focused on the complexity of urban public transport systems.…”

mentioning

confidence: 99%

Power law and small world properties in a comparison of traffic city networks

Wang

Jian

et al. 2011

Chin. Sci. Bull.

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We analyze the statistical properties of the urban public bus networks of two cities (Beijing and Chengdu) in China. To this end, we present a comprehensive survey of the degree distribution, average path length, and clustering of both networks. It is shown that both networks exhibit small world behavior and are hierarchically organized. We also discuss the differences between the statistical properties displayed by the two networks. In addition, we propose a weight distribution approach to study the passenger flow through the public bus networks we considered. A hierarchical structure is observed here also. public transport network, complex network, power-law distribution, small-world Citation:Ma K, Wang Z W, Jiang J, et al. Power law and small world properties in a comparison of traffic city networks.

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Towards Design Principles for Optimal Transport Networks

Cited by 164 publications

References 21 publications

Transport link scanner: simulating geographic transport network expansion through individual investments

Transport link scanner: simulating geographic transport network expansion through individual investments

Navigability of interconnected networks under random failures

Power law and small world properties in a comparison of traffic city networks

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