Bus transport network analysis in Rio de Janeiro based on topological models using Social Networks

TL;DR

This study analyzes the topological structure of Rio de Janeiro's bus network before and after system changes using social network models, revealing key connectivity features and potential expressway corridors.

Contribution

It applies topological social network models to compare bus network structures over time, identifying key parameters and potential corridors in Rio de Janeiro.

Findings

22.75% reduction in bus lines from 2014 to 2016

Maximum of four lines needed to connect any two stops

Over 99% of stops reachable with three lines

Abstract

In recent years, studies on public transport networks have intensified in the Social Networks field, especially in bus networks. This has occurred because of the relevance of urban mobility for the proper functioning of a city. The Rio de Janeiro city, Brazil, has undergone recent changes in the city of Rio de Janeiro, Brazil, has undergone recent changes in its municipal bus system, modifying several lines and bus stops. This paper proposes to analyze the structure of the bus transportation network of this city, comparing its topology in 2014 and 2016, before and after the change. For this, the properties of the bus system were investigated based on the topological models B\-space, P\-space, and C\-space. Some essential parameters were calculated, such as the giant component, distance, diameter, degree, closeness, and betweenness. The results showed that there was a reduction of 22.75\% of the lines and 5.19\% of the bus stops from 2014 to 2016. It was also verified that a maximum of four lines is required to move between any two bus stops within the city in both years. However, with three lines is possible to reach more than 99\% of the bus stops. Besides, this study also suggests exploring the C\-space network according to a minimum number of frequent bus stops that the lines had. Based on the component giant analysis of these networks with many common points, it is possible to detect possible expressway corridors.