Spatial Signatures of Road Network Growth for Different Levels of Global Planning

2021 ◽  
Vol 30 (3) ◽  
pp. 273-296
Author(s):  
Michelle T. Cirunay ◽  
◽  
Rene C. Batac ◽  

We compare the statistical distributions of the geometrical properties of road networks for two representative datasets under different levels of planning: the cities comprising Metropolitan Manila show the conditions under bottom-up self-organized growth, while Brasilia and the Australian Capital Territory centered at Canberra represent the case of strict top-down planning. The distribution of segmented areas of the cities shows a dual power-law behavior, with the larger areas following the ∼1.9 scaling exponent observed in other cities, while the smaller areas show a lower exponent of ∼0.5, believed to be due to practical considerations. While all cities are found to favor the formation of straight road segments, the planned city roads have a preponderance of sinuous roads, with sinuosities approaching π. A simple model based on a nearest-neighbor directed branching coupled with sectional grid formations is proposed to capture the nontrivial statistical features observed.

2018 ◽  
Vol 29 (10) ◽  
pp. 1850099 ◽  
Author(s):  
Michelle T. Cirunay ◽  
Rene C. Batac

We present a statistical characterization of the morphological features emerging from the complex processes governing the growth of the road network, particularly in a mostly self-organized urban setting. Apart from the usual fractal analysis, the roads are quantified by their lengths and straightnesses, while the segmented blocks are characterized by their areas, perimeters and circularities. When applied to the Metro Manila conurbation, one of the megacities in Asia with the fastest growing populations, we observe dense space-filling and nontrivial statistical distributions of roads and blocks that can be attributed to the geographical constraints of the metropolis. The emergence of the scale-free regimes is explained using a simple rule-based model patterned after the assumed dynamical interplay between the local and global factors involved in individual street formation. By viewing road network growth from a quantitative complex systems perspective, we can gain insights into the underlying rules operating at the local scales that give rise to the global spatial patterns.


2008 ◽  
Vol 73 (6-7) ◽  
pp. 873-897 ◽  
Author(s):  
Vladimír Špirko ◽  
Ota Bludský ◽  
Wolfgang P. Kraemer

The adiabatic three-dimensional potential energy surface and the corresponding dipole moment surface describing the ground electronic state of HN2+ (Χ1Σ+) are calculated at different levels of ab initio theory. The calculations cover the entire bound part of the potential up to its lowest dissociation channel including the isomerization barrier. Energies of all bound vibrational and low-lying ro-vibrational levels are determined in a fully variational procedure using the Suttcliffe-Tennyson Hamiltonian for triatomic molecules. They are in close agreement with the available experimental numbers. From the dipole moment function effective dipoles and transition moments are obtained for all the calculated vibrational and ro-vibrational states. Statistical tools such as the density of states or the nearest-neighbor level spacing distribution (NNSD) are applied to describe and analyse general patterns and characteristics of the energy and dipole results calculated for the massively large number of states of the strongly bound HN2+ ion and its deuterated isotopomer.


2014 ◽  
Vol 2 (4) ◽  
pp. 366-371 ◽  
Author(s):  
Liangliang Zhang ◽  
Yuanhua Jia ◽  
Zhonghai Niu ◽  
Cheng Liao

AbstractThe traffic congestion often occurs in urban road network. When one of the sections becomes congested, it will lead to a series of congestions in other sections. The traffic congestion spreads rapidly until part of road network becomes congestion ultimately. In this case, the paper investigates the mechanism of the traffic congestion in urban road network and points out that subsystems of the traffic congestion always perform completive and cooperative functions in the process of traffic congestion. The process behaves in a manner of self-organized criticality, which can be forecasted. The paper also establishes synergetic predictive models based on self-organized criticality of the synergetic theory. Finally, the paper takes Beijing road network as an example to forecast the widespread traffic congestion. The result shows that the established models are accuracy, and the traffic congestion is featured of self-organized criticality.


2015 ◽  
Vol 32 (1) ◽  
Author(s):  
Ricard V. Solé ◽  
Luís F. Seoane

AbstractHuman language defines the most complex outcomes of evolution. The emergence of such an elaborated form of communication allowed humans to create extremely structured societies and manage symbols at different levels including, among others, semantics. All linguistic levels have to deal with an astronomic combinatorial potential that stems from the recursive nature of languages. This recursiveness is indeed a key defining trait. However, not all words are equally combined nor frequent. In breaking the symmetry between less and more often used and between less and more meaning-bearing units, universal scaling laws arise. Such laws, common to all human languages, appear on different stages from word inventories to networks of interacting words. Among these seemingly universal traits exhibited by language networks, ambiguity appears to be a specially relevant component. Ambiguity is avoided in most computational approaches to language processing, and yet it seems to be a crucial element of language architecture. Here we review the evidence both from language network architecture and from theoretical reasonings based on a least effort argument. Ambiguity is shown to play an essential role in providing a source of language efficiency, and is likely to be an inevitable byproduct of network growth.


1994 ◽  
Vol 49 (9) ◽  
pp. 856-860
Author(s):  
Barbara Drossel ◽  
Siegfried Clar ◽  
Franz Schwabl

Abstract We modify the rules of the self-organized critical forest-fire model in one dimension by allowing the fire to jum p over holes of ≤ k sites. An analytic calculation shows that not only the size distribution of forest clusters but also the size distribution of fires is characterized by the same critical exponent as in the nearest-neighbor model, i.e. the critical behavior of the model is universal. Computer simulations confirm the analytic results.


1979 ◽  
Vol 101 (4) ◽  
pp. 409-417 ◽  
Author(s):  
R. S. Sayles ◽  
T. R. Thomas

Surface and profile measurements and their resulting statistics, based on samples of up to half a million heights, are compared and their interrelationship examined for several common engineering surfaces. The measurements are employed to check the applicability of the spectral moment approach to random surface specification. This technique relates many important geometrical properties of a surface to those of its constituent profiles. A relationship is found to exist between the sampling interval and the spatial size of features accommodated by this form of approach. This explains, for example, why 4 and 8 nearest neighbor summit-density analyses based on the same square grid sampling interval reveal very different results. Having established this basic relationship, good agreement is found between theory and measurement over a large range of sampling intervals. In particular, summit densities and distributions are shown to agree well with theory even for non-Gaussian height distributions. It is shown how the isotropic analysis can be extended to cover directionally anisotropic structures such as ground surfaces by defining equivalent movements based on two profiles at right angles. Here again measurements are in good agreement with theory.


2007 ◽  
Vol 10 (01) ◽  
pp. 29-51 ◽  
Author(s):  
STEFANO BATTISTON ◽  
JOAO F. RODRIGUES ◽  
HAMZA ZEYTINOGLU

We present an analysis of inter-regional investment stocks within Europe from a complex networks perspective. We consider two different levels: first, we compute the inward–outward investment stocks at the level of firms, based on ownership shares and number of employees; then we estimate the inward–outward investment stock at the level of regions in Europe, by aggregating the ownership network of firms, based on their headquarter location. To our knowledge, there is no similar approach in the literature so far, and we believe that it may lead to important applications for policy making. In the present paper, we focus on the statistical distributions and the scaling laws, while in further studies we will analyze the structure of the network and its relation to geographical space. We find that while outward investment and activity of firms are power law distributed with a similar exponent, for regions these quantities are better described by a log-normal distribution. At both levels we also find scaling laws relating investment to activity and connectivity. In particular, we find that investment stock scales as a power law of the connectivity, as previously found for stock market data.


2017 ◽  
Vol 26 (05) ◽  
pp. 1750071 ◽  
Author(s):  
Kamil Zeberga ◽  
Rize Jin ◽  
Hyung-Ju Cho ◽  
Tae-Sun Chung

In road networks, [Formula: see text]-range nearest neighbor ([Formula: see text]-RNN) queries locate the [Formula: see text]-closest neighbors for every point on the road segments, within a given query region defined by the user, based on the network distance. This is an important task because the user's location information may be inaccurate; furthermore, users may be unwilling to reveal their exact location for privacy reasons. Therefore, under this type of specific situation, the server returns candidate objects for every point on the road segments and the client evaluates and chooses exact [Formula: see text] nearest objects from the candidate objects. Evaluating the query results at each timestamp to keep the freshness of the query answer, while the query object is moving, will create significant computation burden for the client. We therefore propose an efficient approach called a safe-region-based approach (SRA) for computing a safe segment region and the safe exit points of a moving nearest neighbor (NN) query in a road network. SRA avoids evaluation of candidate answers returned by the location-based server since it will have high computation cost in the query side. Additionally, we applied SRA for a directed road network, where each road network has a particular orientation and the network distances are not symmetric. Our experimental results demonstrate that SRA significantly outperforms a conventional solution in terms of both computational and communication costs.


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