2015
DOI: 10.1088/1742-5468/2015/06/p06013
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Taming macroscopic jamming in transportation networks

Abstract: In transportation networks, a spontaneous jamming transition is often observed, e.g. in urban road networks and airport networks. Because of this instability, flow distribution is significantly imbalanced on a macroscopic level. To mitigate the congestion, we consider a simple control method, in which congested nodes are closed temporarily, and investigate how it influences the overall system. Depending on the timing of the node closure and opening, and congestion level of a network, the system displays three … Show more

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Cited by 16 publications
(11 citation statements)
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References 48 publications
(69 reference statements)
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“…Some information systems, such as telecommunication [10] and computing networks [11,12], as well as trunked mobile radio systems and air traffic [13][14][15] are also amenable to the channel description.…”
Section: Introductionmentioning
confidence: 99%
“…Some information systems, such as telecommunication [10] and computing networks [11,12], as well as trunked mobile radio systems and air traffic [13][14][15] are also amenable to the channel description.…”
Section: Introductionmentioning
confidence: 99%
“…, they found the system with 1 < p and 2 > p is stable for p <̄(= ( 1 + 2 )∕2) < 1∕2 . Therefore, MFD q D (̄) is continuous and given by Meanwhile, Ezaki and his coworkers extended the model to arbitrary strongly connected directed graphs [13,14]. Note that FD q( ) in their model is parabola like and symmetric, that is, p = 1∕2 .…”
Section: Previous Studiesmentioning
confidence: 99%
“…Such theoretical studies have elucidated the emergence mechanisms of congestion in computer networks (Ohira and Sawatari, 1998), road networks (Biham et al, 1992), airport networks (Ezaki and Nishinari, 2014), production networks (Ezaki, Yanagisawa and Nishinari, 2015), etc. Past studies have found critical determinants of transport performance, such as network topology (Guimerà et al, 2002;Zhao et al, 2005), capacity distribution (Zhao et al, 2005;Wu et al, 2008), routing algorithm (Echenique et al, 2004;Zhang et al, 2007;Ling et al, 2010;Ezaki, Nishi and Nishinari, 2015). These factors were taken into consideration in this study.…”
Section: Introductionmentioning
confidence: 97%