Fast Computation of Betweenness Centrality to enable Real-time Resilience Assessment and Improvement of Complex Transport Networks (original) (raw)

2020

With the growth of the population concentrated in urban areas of large agglomerations, the need for e cient and resilient multi-modal transportation systems is paramount. To model, analyze and improve transportation dynamics at large scale, complex networks represent an extremely versatile toolkit: multi-modal mobility networks can be modelled as a multi-layered weighted graph. In the last decade, several works [1, 2, 3] have shown that complex network approaches based on computation of centrality metrics can be extremely useful to model and analyze the resilience properties of complex networks. In such representation, each layer of the graph can be associated to a transportation mode (e.g., road, metro, buses, etc); each node of the network is an intersection between roads, a parking spot or a bus/metro stop/station; and the edges are links between the nodes, possibly belonging to di↵erent layers of the transportation network (e.g., links connecting bus with metro stations or parki...

Recent Development in Public Transport Network Analysis From the Complex Network Perspective

2019

A graph, comprising a set of nodes connected by edges, is one of the simplest yet remarkably useful mathematical structures for the analysis of real-world complex systems. Network theory, being an application-based extension of graph theory, has been applied to a wide variety of real-world systems involving complex interconnection of subsystems. The application of network theory has permitted in-depth understanding of connectivity, topologies, and operations of many practical networked systems as well as the roles that various parameters play in determining the performance of such systems. In the field of transportation networks, however, the use of graph theory has been relatively much less explored, and this motivates us to bring together the recent development in the field of public transport analysis from a graph theoretic perspective. In this paper, we focus on ground transportation, and in particular the bus transport network (BTN) and metro transport network (MTN), since the ...

Application of Complex Networks Theory in Urban Traffic Network Researches

Springer US, 2019

Complex network theory is a multidisciplinary research direction of complexity science which has experienced a rapid surge of interest over the last two decades. Its applications in land-based urban traffic network studies have been fruitful, but have suffered from the lack of a systematic cognitive and integration framework. This paper reviews complex network theory related knowledge and discusses its applications in urban traffic network studies in several directions. This includes network representation methods, topological and geographical related studies, network communities mining, network robustness and vulnerability, big-data-based research, network optimization, co-evolution research and multilayer network theory related studies. Finally, new research directions are pointed out. With these efforts, this physics-based concept will be more easily and widely accepted by urban traffic network planners, designers, and other related scholars.

A New Method for Assessing the Resiliency of Large, Complex Networks

2006

Designing resilient and reliable networks is a principle concern of planners and private firms. Traffic congestion whether recurring or as the result of some aperiodic event is extremely costly. This paper describes an alternative process and a model for analyzing the resiliency of networks that address some of the shortcomings of more traditional approaches – e.g., the four-step modeling process

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