TY - GEN
T1 - Measuring the Resilience of the Transport Infrastructure in Big Cities
AU - Alatrista-Salas, Hugo
AU - Nunez-Del-Prado, Miguel
AU - Rodriguez, Guillermo
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/1/23
Y1 - 2019/1/23
N2 - The accelerated growth of the cities, the vehicular congestion, the abrupt climatic and social events, have propitiated disruptive scenarios in the harmony of the urban ecosystem. These events motivate several research and debates in the scientific community to try to explain the transformations of urban behavior in different aspects, including the weakness of streets networks. This paper presents a study of the impact of an adverse event in the transport infrastructure in a city. Precisely, we represent the transport infrastructure of a city thanks to a graph. This graph is analyzed using some measures like as the degree of connectivity, the density, and the intermediate centrality. Later, three kinds of attacks on the network were implemented, i.e., nodes of the network were systematically eliminated, and the characteristics of the network were re-measured. The idea behind is to measure - for instance - if a health center can still be accessible when the routes that allow access to the center are closed due to an adverse event (e.g., an earthquake). Two cities of two countries in South-America have been compared in different granularity levels. Our results highlight the pertinence of our approach.
AB - The accelerated growth of the cities, the vehicular congestion, the abrupt climatic and social events, have propitiated disruptive scenarios in the harmony of the urban ecosystem. These events motivate several research and debates in the scientific community to try to explain the transformations of urban behavior in different aspects, including the weakness of streets networks. This paper presents a study of the impact of an adverse event in the transport infrastructure in a city. Precisely, we represent the transport infrastructure of a city thanks to a graph. This graph is analyzed using some measures like as the degree of connectivity, the density, and the intermediate centrality. Later, three kinds of attacks on the network were implemented, i.e., nodes of the network were systematically eliminated, and the characteristics of the network were re-measured. The idea behind is to measure - for instance - if a health center can still be accessible when the routes that allow access to the center are closed due to an adverse event (e.g., an earthquake). Two cities of two countries in South-America have been compared in different granularity levels. Our results highlight the pertinence of our approach.
UR - http://www.scopus.com/inward/record.url?scp=85062567369&partnerID=8YFLogxK
U2 - 10.1109/LA-CCI.2018.8625202
DO - 10.1109/LA-CCI.2018.8625202
M3 - Conference contribution
AN - SCOPUS:85062567369
T3 - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
BT - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
Y2 - 6 November 2018 through 9 November 2018
ER -