Paper Info
Title
Vulnerability Analysis of the Urban Transport System in the Context of Smart Cities
Abstract
Large cities seek to incorporate intelligent systems into their infrastructure, industrial, educational, and social activities to improve the quality of service provided to citizens and make all processes more efficient. To this end, these cities use technologies that involve the areas of the Internet of Things, Big Data, and Governance to make decisions by governments and authorities. In the field of Urban Computing, it is possible to use open data in the GTFS format to solve the problems of the urban transport system using complex network metrics that make it possible to model complex interactions between objects in high dimensionality. Stops and routes are modeled as a graph, characterized by complex network metrics. According to the literature, if there is an interruption of the urban transport system, we make an evaluation of the degree of vulnerability of the system in the search for solutions. The main goal of this paper is to propose an approach to analyze the vulnerability of the urban transport system using complex network metrics along with GTFS data in scenarios targeted failures. As a contribution, the proposed approach uses the concept of skewness in the methodology established in the literature. The skewness enables a better understanding and differential the failure conditions from the evaluation of the vulnerability the urban transport system, through a quantitative indication of which local metrics most influence the decay of network metrics. The analysis of the results obtained in the proposed approach serves as a subsidy for studies in the search for solutions to the problems of the urban transport system, providing a tool to the set of technological options for the planning of urban transport systems of smart cities available to governments and authorities. The proposed approach can be applied in different cities, regardless of their size and location, as long as you have access to open geographic data in the GTFS format.
Year
DOI
Venue
2020
10.1109/ISC251055.2020.9239050
2020 IEEE International Smart Cities Conference (ISC2)
Keywords
DocType
ISSN
Smart Cities,Urban Computing,Human Mobility,Urban Transport System
Conference
2687-8852
ISBN
Citations 
PageRank 
978-1-7281-8295-7
0
0.34
References 
Authors
7
3
Name
Order
Citations
PageRank
Antônio A. F. G. M. Pertence100.34
Raquel A. F. Mini224823.58
Humberto T. Marques-Neto3294.00