Robustness Of Transportation Networks Research Articles

Enhancing flood-response commuting resilience via driving mechanism investigation: New evidence from Wuhan, China

In the context of climate change, transportation resilience to flood threats has received significant attention. However, measures to improve practical resilience have not been addressed and elucidated. Various studies from the domains of disaster and transport have been devoted to commuting vulnerability analysis and transport network robustness assessment, whereas a systematic perspective is rarely used to analyze the damage mechanism of floods to the commuting system. To fill this research gap, we constructed an index system from the dimensions of hazard, transport network condition, and commuting pattern as driving factors of commuting risk during floods. The contribution to commuting loss was first assessed to guide intervention prioritization based on flood modeling and commute simulation. We adopted gradient boosting decision trees to examine the relationship between driving factors from three dimensions and commuting. The results of this study conducted in Wuhan indicate that the contribution rate of commuting pattern is the highest, followed by hazard, and finally road network conditions. The effective thresholds of the driving factors were also identified to guide urban governance. This study is a novel exploration of disaster impact mechanism that can provide new insights for the improvement of commuting resilience practices under climate change.

Estimation and improvement of transportation network robustness by exploiting communities

Throughout the past years, researchers increasingly study the resilience of transportation systems through the lens of complex networks. This model simplification has helped to identify bottlenecks for all kinds of systems, e.g., subway, railway, and road networks. Nevertheless, for large networks, with ten thousand and more nodes, standard complex network-based robustness analysis methods do not scale up well. In this study, we propose to estimate and improve the robustness of transportation systems by exploiting the presence of communities in complex network representations. A community, by definition, is densely connected inside, but loosely connected to other components in the system. Accordingly, the community structure and the induced edges connecting communities can help to orchestrate a framework for better analysis and protection of our transportation systems. Experiments on twelve real-world transportation systems demonstrate the efficiency and scalability of our novel community-based framework.

Measuring the Topological Robustness of Transportation Networks to Disaster-Induced Failures: A Percolation Approach

This paper presents a framework that integrates network theory methods into infrastructure network assessment in order to investigate transportation network robustness from a topological perspective. The objectives of this paper are threefold: (1) develop a framework that can effectively measure network performance under different stress levels (hazard scales); (2) determine the constraints of infrastructure networks’ spatially embedded nature in network robustness assessment; and (3) characterize the percolation transition in infrastructure networks and systematically evaluate cities’ robustness, and in doing so provide an evidence-driven evaluation framework for urban resilience planning. In this research, 13 city and 3 state transportation networks were investigated through both the proposed simulation and an analytical framework. The results show that (1) certain theoretical methods, such as generating functions, do not apply to transportation network analysis due to their unique spatially embedded features; (2) different city and state transportation networks’ degree distribution and percolation dynamics display similar patterns; (3) critical percolation threshold identifies the robustness feature in extreme cases and provides an early warning for urban traffic disruption, and the robustness index accurately measures the network robustness from a holistic point of view; and (4) reducing network spatial complexity by decreasing the node assortativity will make the empirical simulation comply with the theoretical results, which unveils the source of spatial essence inherent in infrastructure networks. Through the validation of different transportation networks, the proposed robustness assessment framework is verified to be able to extend the robustness analysis to a general network.

Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events

Robustness measures a system's ability of being insensitive to disturbances. Previous studies assessed the robustness of transportation networks to a single disturbance without considering simultaneously happening multiple events. The purpose of this article is to address this problem and propose a new framework to assess the robustness of an urban transportation network. The framework consists of two layers. The upper layer is to define the robustness index based on the impact evaluation in different scenarios obtained from the lower layer, whereas the lower layer is to evaluate the performance of each hypothetical disrupted road network given by the upper layer. The upper layer has two varieties, that is, robustness against random failure and robustness against intentional attacks. This robustness measurement framework is validated by application to a real-world urban road network in Hong Kong. The results show that the robustness of a transport network with consideration of multiple events is quite different from and more comprehensive than that with consideration of only a single disruption. We also propose a Monte Carlo method and a heuristic algorithm to handle different scenarios with multiple hazard events, which is proved to be quite efficient. This methodology can also be applied to conduct risk analysis of other systems where multiple failures or disruptions exist.

Robustness analysis metrics for worldwide airport network: A comprehensive study

Robustness of transportation networks is one of the major challenges of the 21st century. This paper investigates the resilience of global air transportation from a complex network point of view, with focus on attacking strategies in the airport network, i.e., to remove airports from the system and see what could affect the air traffic system from a passenger’s perspective. Specifically, we identify commonalities and differences between several robustness measures and attacking strategies, proposing a novel notion of functional robustness: unaffected passengers with rerouting. We apply twelve attacking strategies to the worldwide airport network with three weights, and evaluate three robustness measures. We find that degree and Bonacich based attacks harm passenger weighted network most. Our evaluation is geared toward a unified view on air transportation network attack and serves as a foundation on how to develop effective mitigation strategies.

The value of new public transport links for network robustness and redundancy

A common argument for introducing new links or services to transport networks is that they will contribute to greater capability to withstand system breakdowns. This paper presents a methodology for assessing the value of new links for public transport network robustness, considering disruptions of other lines and links as well as the new links themselves. The value is evaluated in terms of passenger welfare under disruptions and can be compared to traditional welfare benefits and investment costs. Distinction is made between the value of robustness, defined as the change in welfare during disruption compared to the baseline network, and the value of redundancy, defined as the change in welfare losses due to disruption. The paper introduces the total values of robustness and redundancy by considering a full space of scenarios and their respective frequencies. Using a model that considers passengers’ dynamic travel choices, stochastic traffic conditions, timetables and capacity constraints, results are more nuanced than analyses based only on network topology and other static attributes. A new cross-radial light rail transit line in Stockholm, Sweden, is evaluated. The new link increases welfare levels under all scenarios and has a positive value of robustness. However, disruption costs increase under some scenarios and the value of redundancy is negative. In general, the value of redundancy depends on the new link's role as complement or substitute and passengers’ ability to utilise spare capacity during short-term unexpected disruptions.

Planning for the unexpected: The value of reserve capacity for public transport network robustness

Public transport networks (PTN) are subject to recurring service disruptions. Most studies of the robustness of PTN have focused on network topology and considered vulnerability in terms of connectivity reliability. While these studies provide insights on general design principles, there is lack of knowledge concerning the effectiveness of different strategies to reduce the impacts of disruptions. This paper proposes and demonstrates a methodology for evaluating the effectiveness of a strategic increase in capacity on alternative PTN links to mitigate the impact of unexpected network disruptions. The evaluation approach consists of two stages: identifying a set of important links and then for each identified important link, a set of capacity enhancement schemes is evaluated. The proposed method integrates stochastic supply and demand models, dynamic route choice and limited operational capacity. This dynamic agent-based modelling of network performance enables to capture cascading network effects as well as the adaptive redistribution of passenger flows. An application for the rapid PTN of Stockholm, Sweden, demonstrates how the proposed method could be applied to sequentially designed scenarios based on their performance indicators. The method presented in this paper could support policy makers and operators in prioritizing measures to increase network robustness by improving system capacity to absorb unexpected disruptions.

A review of current practice in network disruption analysis and an assessment of the ability to account for isolating links in transportation networks

This paper presents a comprehensive review of the scholarly literature related to the field of network-disruption analysis. Research related to network disruption has progressed immensely since the late 1990s and now includes a wide variety of themes and approaches used to assess the impacts associated with a variety of disruptive events. Of particular relevance are those approaches which use repetitive link and/or node-removal methodologies to develop measures of network robustness or vulnerability (complementary concepts). More recently, various methods have begun to focus on the sequential application of equilibrium-based traffic assignments to measure the cost of a disruption to the network. It is crucial for these types of methods to handle the complexities of real-world transportation networks — one of which is the presence of isolating links in a network, which provide a single link to a particular region or subnetwork. A number of methods have attempted to deal with the problem of isolating links in different ways, but none has been ubiquitously successful. To develop a comprehensive and useful measure of transportation network robustness it is important to successfully address the issue of isolating network links.

A relative total cost index for the evaluation of transportation network robustness in the presence of degradable links and alternative travel behavior

AbstractIn this paper, we demonstrate how to capture the robustness of a transportation network in the case of degradable links represented by decreasing capacities. In particular, with the use of Bureau of Public Roads user link travel cost functions, we propose two relative total cost indices to assess transportation network robustness in the case of travel behavior associated with either user optimization or system optimization. We derive upper bounds of the relative total cost index for transportation networks with special structure and congestion parameters under the user optimal flow pattern. We also derive an upper bound for the relative total cost index under the system optimal flow pattern for general transportation networks. Numerical examples are presented for illustration purposes. This research is the first to quantify transportation network robustness in the presence of degradable links and alternative travel behavior. This research has implications for transportation planning and management, for vulnerability analysis, as well as for security issues.

A Relative Total Cost Index for the Evaluation of Transportation Network Robustness in the Presence of Degradable Links and Alternative Travel Behavior

In this paper, we demonstrate how to capture the robustness of a transportation network in the case of degradable links represented by decreasing capacities. In particular, with the use of Bureau of Public Road user link travel cost functions, we propose two relative total cost indices to assess transportation network robustness in the case of travel behavior associated with either user-optimization or system-optimization. We derive upper bounds of the relative total cost index for transportation networks with special structure and congestion parameters under the user-optimal flow pattern. We also derive an upper bound for the relative total cost index under the system-optimal flow pattern for general transportation networks. Numerical examples are presented for illustration purposes.This research is the first to quantify transportation network robustness in the presence of degradable links and alternative travel behavior. This research has implication for transportation planning and management, for vulnerability analysis, as well as for security issues.