Name
Title | ||
|---|---|---|
Congestion Potential – A New Way to Analyze Public Transportation based on Complex Networks |
Abstract | ||
|---|---|---|
Based on complex network theory, metrics are proposed in this paper to identify local characteristics of public transportation networks, in special, congestion potential. As case of studies, two major Brazilian cities were chosen. Using L-space representation and geographic distances between connected bus stops as link weights at the resulting PTN model as complex network, we identified regions with high probability of vehicle and passenger congestion in both cities. We find out a type of complex network for PTNs, characterized by high degree, high number of modular communities and low clustering coefficient, differing from usual ones, characterized by bus/train terminals as network hubs. The achieved results of the complex network analysis can be applied to city planning. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ISC2.2018.8656960 | 2018 IEEE International Smart Cities Conference (ISC2) |
Keywords | Field | DocType |
Complex networks,Urban areas,Measurement,Public transportation,Electron tubes,Biological system modeling | Computer science,Computer network,Public transport,Urban planning,Complex network,Modular design,Complex network analysis,Clustering coefficient | Conference |
ISBN | Citations | PageRank |
978-1-5386-5959-5 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anderson De Bona | 1 | 0 | 0.34 |
| Marcelo Rosa | 2 | 0 | 1.01 |
| Keiko Fonseca | 3 | 0 | 0.34 |
| Ricardo Lüders | 4 | 24 | 7.23 |
| Nádia P. Kozievitch | 5 | 20 | 11.55 |