Proper functioning of a city relies on how optimal all its critical infrastructure systems operate. One of the most important infrastructure systems, especially for metropolitan cities are transportation networks which are the backbone of all critical infrastructures. Transportation systems behave differently in the face of disruptions due to a “Random Failure or Incident”, “Intentional Attack” and “Natural Disasters”. In addition, the response of each mode of transportation in case of the same disruptive event can be totally different (e.g. comparing a node disruption in an aviation network with a subway network which leads to totally different economic consequences). As a result, we should be aware of all kinds of risks, which threaten each mode of transportation network to avoid any devastating scenario. Increasing the resiliency of different transportation networks has even become more vital in recent years because of two reasons: 1. uncertainty in the context of future climate change and concern about increases in the frequency and severity of natural hazards; 2. countering terrorism is a worldwide top national security priority. By boosting the resiliency of the networks, we will be able to minimize the costs of a disruptive event from the economical, social and operational point of view. In order to do so, we have to define the critical components of networks and simulate the response of networks when those components stop working. Graphs are among the most commonly used tools for studying different types of transportation systems. Through graph analysis, we are able to find and modify the most vulnerable parts of the network to increase its general robustness. In this thesis, subway networks were analyzed by settling measures on graphs. Thirty-four subway networks all around the world were studied through some known indices (the four centrality indices) and three new ones (Ishortest, Icentr, and Pathrank) specifically developed for this study. The most crucial components of these networks (through the four centrality indices, Icentr and Pathrank) as well as the stations whose malfunctions have the highest effects on the performance of the whole system (through Ishortest), were defined. The obtained results will help us to decrease the vulnerability of existing subway networks by increasing the robustness of defined stations. The methodology which has been used in this thesis can be extended to other modes of transportation with minimal effort.
Il corretto funzionamento di una città dipende dall'ottimale funzionamento di tutti i suoi sistemi di infrastrutture critiche. Uno dei sistemi infrastrutturali più importanti, specialmente per le città metropolitane, sono le reti di trasporto che sono la spina dorsale di tutte le infrastrutture critiche. I sistemi di trasporto si comportano in modo diverso a causa di interruzioni dovute a "Guasto o incidente casuale", "Attacco intenzionale" e "Disastri naturali". Inoltre, la risposta di ciascuna modalità di trasporto in caso di uno stesso evento perturbatore può essere totalmente diversa (ad es. Confrontare una rottura del nodo in una rete aerea con una rete metropolitana che porta a conseguenze economiche totalmente diverse). Di conseguenza, dovremmo essere consapevoli di tutti i tipi di rischi, che minacciano ogni modalità di rete di trasporto per evitare qualsiasi scenario devastante. Aumentare la resilienza delle diverse reti di trasporto è diventato ancora più vitale negli ultimi anni per due motivi: 1. incertezza nel contesto dei futuri cambiamenti climatici e preoccupazione per l'aumento della frequenza e della gravità dei pericoli naturali; 2. la lotta al terrorismo è una delle massime priorità di sicurezza nazionale a livello mondiale. Aumentando la resilienza delle reti, saremo in grado di ridurre al minimo i costi di un evento dirompente dal punto di vista economico, sociale e operativo. Per fare ciò, dobbiamo definire i componenti critici delle reti e simulare la risposta delle reti quando tali componenti smettono di funzionare. I grafici sono tra gli strumenti più comunemente usati per studiare diversi tipi di sistemi di trasporto. Attraverso l'analisi dei grafici, siamo in grado di trovare e modificare le parti più vulnerabili della rete per aumentarne la solidità generale. In questa tesi, le reti della metropolitana sono state analizzate stabilendo misure sui grafici. Trentaquattro reti metropolitane in tutto il mondo sono state studiate attraverso alcuni indici noti (i quattro indici di centralità) e tre nuovi (Ishortest, Icentr e Pathrank) sviluppati appositamente per questo studio. Sono state definite le componenti più cruciali di queste reti (attraverso i quattro indici di centralità, Icentr e Pathrank), nonché le stazioni i cui malfunzionamenti hanno il massimo effetto sulle prestazioni dell'intero sistema (tramite Ishortest). I risultati ottenuti ci aiuteranno a ridurre la vulnerabilità delle reti metropolitane esistenti aumentando la solidità delle stazioni definite. La metodologia che è stata utilizzata in questa tesi può essere estesa ad altri modi di trasporto con il minimo sforzo.
Assessing criticality in subway networks for risk prevention through topological performance indices
VISEH, HIVA
2019/2020
Abstract
Proper functioning of a city relies on how optimal all its critical infrastructure systems operate. One of the most important infrastructure systems, especially for metropolitan cities are transportation networks which are the backbone of all critical infrastructures. Transportation systems behave differently in the face of disruptions due to a “Random Failure or Incident”, “Intentional Attack” and “Natural Disasters”. In addition, the response of each mode of transportation in case of the same disruptive event can be totally different (e.g. comparing a node disruption in an aviation network with a subway network which leads to totally different economic consequences). As a result, we should be aware of all kinds of risks, which threaten each mode of transportation network to avoid any devastating scenario. Increasing the resiliency of different transportation networks has even become more vital in recent years because of two reasons: 1. uncertainty in the context of future climate change and concern about increases in the frequency and severity of natural hazards; 2. countering terrorism is a worldwide top national security priority. By boosting the resiliency of the networks, we will be able to minimize the costs of a disruptive event from the economical, social and operational point of view. In order to do so, we have to define the critical components of networks and simulate the response of networks when those components stop working. Graphs are among the most commonly used tools for studying different types of transportation systems. Through graph analysis, we are able to find and modify the most vulnerable parts of the network to increase its general robustness. In this thesis, subway networks were analyzed by settling measures on graphs. Thirty-four subway networks all around the world were studied through some known indices (the four centrality indices) and three new ones (Ishortest, Icentr, and Pathrank) specifically developed for this study. The most crucial components of these networks (through the four centrality indices, Icentr and Pathrank) as well as the stations whose malfunctions have the highest effects on the performance of the whole system (through Ishortest), were defined. The obtained results will help us to decrease the vulnerability of existing subway networks by increasing the robustness of defined stations. The methodology which has been used in this thesis can be extended to other modes of transportation with minimal effort.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/152779