Spatial analysis of bus transport networks using network theory

2018 ◽  
Vol 502 ◽  
pp. 295-314 ◽  
Author(s):  
Tanuja Shanmukhappa ◽  
Ivan Wang-Hei Ho ◽  
Chi Kong Tse
2007 ◽  
Vol 376 ◽  
pp. 747-754 ◽  
Author(s):  
Yong-Zhou Chen ◽  
Nan Li ◽  
Da-Ren He

2008 ◽  
Vol 22 (17) ◽  
pp. 3349-3360 ◽  
Author(s):  
L. J. Manning ◽  
J. W. Hall ◽  
C. G. Kilsby ◽  
S. Glendinning ◽  
M. G. Anderson

2012 ◽  
Vol 391 (3) ◽  
pp. 917-924 ◽  
Author(s):  
Xu-Hua Yang ◽  
Bo Wang ◽  
Sheng-Yong Chen ◽  
Wan-Liang Wang

2007 ◽  
Vol 21 (16) ◽  
pp. 1027-1040 ◽  
Author(s):  
YONG-ZHOU CHEN ◽  
NAN LI

We conjecture that the evolution process with self-avoiding random walks is the origin for the properties of urban ground bus-transport networks (BTN). In order to verify our conjecture, a toy model, which simulates the growth of urban bus-transport systems, is proposed after empirical investigation on the BTNs of four major cities in China. In current empirical and simulation research, our method combining weight and geographical topology of the BTN together allows us to study the coupling relations among the BTN's weighted quantities and underlying topological structure. Finally, the simulating results reveal that the model can reproduce most phenomena observed in real-life urban ground BTNs.


2018 ◽  
Vol 32 (21) ◽  
pp. 1850228 ◽  
Author(s):  
Baoyu Hu ◽  
Yulong Pei ◽  
Jinjun Tang ◽  
Wei Gao

The space P and space L representation models are often adopted together in the empirical analysis of bus transport networks (BTNs). In this paper, we develop a new representation model for BTNs using double edge weights and node weights, namely perfect space P. The model incorporates the number and lengths of directed routes between the two stations and the number of routes that connect to each station. Based on the model, we develop an empirical study on four large BTNs in Northeast China. Some common network characteristics of the BTNs are revealed and discussed in detail. The results show that several empirical distributions follow an exponential law. Moreover, the unweighted path length distributions can be fitted by a Gaussian function, while the weighted path length distributions can be fitted by a composite Gaussian function. Specifically, we introduce the weighted-degree distribution with different lengths and the special edge weight distribution, given the new evidence for the random behavior during the expansion of BTNs, including new stations and routes.


2021 ◽  
Vol 24 (2) ◽  
pp. 106-119
Author(s):  
Ariel Ciechański

W artykule autor powraca do klasycznych niegdyś w geografii transportu metod grafowych. Wykorzystując podstawowe wskaźniki, takie jak liczba cyklomatyczna μ, wskaźnik α Kansky’ego, wskaźnik γ Kansky’ego i wskaźnik Gns opracowany przez A. Ciechańskiego analizuje zmiany sieci pozamiejskiego autobusowego publicznego transportu zbiorowego na obszarze Beskidu Niskiego i Bieszczad. Testuje też wskaźnik Gns dla bardziej rozbudowanych grafów o skomplikowanej strukturze, w tym również często z bardzo licznymi izolowanymi wierzchołkami. Niestety w przeciwieństwie do prostych i niespójnych sieci transportowych, dla których został on skonstruowany, w przypadku dużych sieci transportowych, zawierających liczne cykle jego czułość wykazuje znacznie gorszy poziom, a otrzymane wyniki są znacznie mniej jednoznaczne niż w przypadku gdy izolowane podgrafy są mniej liczne, za to o bardziej rozbudowanej strukturze. Słowa kluczowe: metody grafowe, wskaźnik Gns, zmiany sieci pozamiejskiego publicznego transportu zbiorowego, Beskid Niski, Bieszczady Changes in the network of the non-urban public bus transport in Bieszczady and Beskid Niski mountains – a topological approach In the article, the author returns to the graph methods which were once classic in the transport geography. Using basic indicators such as the cyclomatic number μ, the α Kansky index, the γ Kansky index and the Gns index developed by A. Ciechański, he analyzes the changes in the network of non-urban public bus transport in the area of the Beskid Niski and the Bieszczady Mountains. He also tests the Gns indicator for more complex graphs with a complicated structure, including often very numerous isolated vertices. Unfortunately, unlike the simple and inconsistent transport networks for which it was created, in the case of large transport networks containing many cycles its sensitivity shows a much worse level and the obtained results are much less unambiguous than in the case when the isolated subgraphs are less numerous, but with the more elaborate structure.


Sign in / Sign up

Export Citation Format

Share Document