A network mobility indicator using a fuzzy logic approach

This paper introduces a methodology to assess the mobility of a road transport network from the 3 network perspective. In this research, the mobility of the road transport network is defined as the 4 ability of the road transport network to connect all the origin-destination pairs within the network with 5 an acceptable level of service. Two mobility attributes are therefore introduced to assess the physical 6 connectivity and the road transport network level of service. Furthermore, a simple technique based 7 on a fuzzy logic approach is used to combine mobility attributes into a single mobility indicator in 8 order to measure the impact of disruptive events on road transport network functionality. 9 The application of the proposed methodology on a hypothetical Delft city network shows the ability of the technique to estimate variation in the level of mobility under different scenarios. The method allows the study of demand and supply side variations on overall network mobility, providing a new tool for decision makers in understanding the dynamic nature of mobility under various events. The method can also be used as an evaluation tool to gauge the highway network mobility level, and to highlight weaknesses in the network

Using Space Syntax For Estimation Of Potential Disaster Indirect Economic Losses

The study of applicable network measures shows that Normalised Angular Choice can be used as criteria for selecting alternatives for minimizing indirect costs caused by road network damages. At the same time, this methodology cannot be used for monetizing indirect costs or identifying losses in different economic sectors. The study approach does not contradict the main theoretical approaches and it gives new opportunities for research on disasters recovery

Decision aid problems criteria for infrastructure networks vulnerability analysis (regular paper)

Natural disasters through infrastructure networks might aggravate or mitigate consequences to stakes. The objective of this paper is to characterize this kind of situation in order to provide a solid foundation for the decision aid. This characterization includes a description of the typology, actions and potential actions identification, determining preference systems, as well as a set of specific problems to each phase

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Developing a context-based bounded centrality approach of street patterns in flooding: a case study of London

Floods affect an average of 21 million people worldwide each year, and their frequency is expected to increase due to climate warming, population growth, and rapid urbanisation. Previous research on the robustness of transport networks during floods has mainly used percolation theory. However, giant component size of disrupted networks cannot capture the entire network’s information and, more importantly, does not reflect the local reality. To address this issue, this study introduces a novel approach to bounded context-based centrality to extract the local impact of disruption. In particular, we propose embedding travel behaviour into the road network to calculate bounded centrality and develop new measures characterising the size of connected components during flooding. Our analysis can identify critical road segments during floods by comparing the decreasing trend and dispersibility of component sizes on road networks. To demonstrate the feasibility of these approaches, a case study of London's transport infrastructure that integrates road networks with relevant urban contexts was developed. This approach is beneficial for practical risk management, helping decision-makers allocate resources efficiently in space and time

Resilience of ground transportation networks: a case study on Melbourne

A city with a transportation system so well designed that failure of any arbitrary waypoint triggers no major event, is the major goal for every single urban planning and management board. However, city planning comes with inherent design constraints. Research is needed to understand the interaction between these constraints and city resilience. This understanding is useful for those planning for a new city and more importantly, when evaluating and designing cost-effective ways to improve the resilience of existing cities.In this paper, we promote a proactive attitude for prevention. We use network analysis to estimate the resilience of ground transportation system in Melbourne. Real data extracted from GPS navigation maps of Melbourne is used and resilience is computed for train, tram and street networks. The interdependency and interaction of these networks is then used to risk assess Melbourne’s transportation system. The system-level risk identification process paints a risk picture for Melbourne City ground transport system.The approach can be generalised to any piece of ground covered by a GPS navigation map, being a promising cost-effective, systemic and structured approach to quantify and manage risk of virtually any city in the world

APPROACHES TO VULNERABILITY ANALYSIS FOR DISCOVERING THE CRITICAL ROUTES IN ROADWAY NETWORKS

All modes of transportation are vulnerable to disruptions caused by natural disasters and/or man-made events (e.g., accidents), which may have temporary or permanent consequences. Identifying crucial links where failure could have significant effects is an important component of transportation network vulnerability assessments, and the risk of such occurrences cannot be underestimated. The ability to recognize critical segments in a transportation network is essential for designing resilient networks and improving traffic conditions in scenarios like link failures, which can result in partial or full capacity reductions in the system. This study proposes two approaches for identifying critical links for both single and multiple link disruptions. New hybrid link ranking measures are proposed, and their accuracy is compared with the existing traffic-based measures. These new ranking measures integrate aspects of traffic equilibrium and network topology. The numerical study revealed that three of the proposed measures generate valid findings while consuming much less computational power and time than full-scan analysis measures. To cover various disruption possibilities other than single link failure, an optimization model based on a game theory framework and a heuristic algorithm to solve the mathematical formulation is described in the second part of this research. The proposed methodology is able to identify critical sets of links under different disruption scenarios including major and minor interruptions, non-intelligent and intelligent attackers, and the effect of presenting defender. Results were evaluated with both full scan analysis techniques and hybrid ranking measures, and the comparison demonstrated that the proposed model and algorithm are reliable at identifying critical sets of links for random and specially targeted attacks based on the adversary\u27s link selection in both partial and complete link closure scenarios, while significantly reducing computational complexity. The findings indicate that identifying critical sets of links is highly dependent on the adversary\u27s inelegancy, the presence of defenders, and the disruption scenario. Furthermore, this research indicates that in disruptions of multiple links, there is a complex correlation between critical links and simply combining the most critical single links significantly underestimates the network\u27s vulnerability