Transportation Network Vulnerability Research Articles

An analysis of the vulnerability of road networks in response to disruption events through accessibility indicators specification

ABSTRACT The objective of this paper is to propose an analysis of the vulnerability of road transportation networks in response to external shocks. Through the estimation of the accessibility and Link Importance Indicator (LII), a vulnerability road transportation analysis has been carried out and applied to a real case study. The case study comprises the 112 districts of the metropolitan area of the city of Naples, in the south of Italy. The main findings of this study are represented by the accessibility indicator introduced, which can be considered a measure to capture the vulnerability due to disruptions in the road network, and the LII, which can be used to identify critical roads. The proposed methodology represents a useful tool for local administrations, transportation agencies, and civil protection that need to deal with emergency situations, which are becoming more common.

A random-key genetic algorithm-based method for transportation network vulnerability envelope analysis under simultaneous multi-link disruptions

Transportation network vulnerability envelope (TNVE), constituted by the upper and lower bounds of network performance among all possible disruption scenarios, has recently been proposed as a systematic tool to characterize the impact of simultaneous disruptions of multiple links in a transportation network. Both pessimistic and optimistic cases and the possible range of disruption consequences can be revealed by the TNVE, which can be modeled as a unified optimization problem without the need to enumerate and evaluate all possible disruption scenarios. Specifically, the TNVE problem can be formulated as a binary integer bi-level program (BLP), in which the upper-level problem maximizes/minimizes the remaining network performance under a given number of disrupted links, and the lower-level problem adopts the shortest path problem to check the post-disruption connectivity of each origin–destination (O-D) pair while circumventing the cumbersome path enumeration or path set pre-generation. However, the binary integer BLP is computationally intractable, which hinders the applications of TNVE in practice. This study aims to develop an efficient method based on the random key genetic algorithm (RKGA) for determining the TNVE under simultaneous multi-link disruptions. The main features and benefits of the proposed method include: (a) it simultaneously solves the upper- and lower-bound problems at the same time while guaranteeing the feasibility of all solutions in the solution procedure; (b) it improves the computational efficiency to ensure the applicability to real transportation networks; and (c) it can provide a variety of alternative solutions in addition to the single optimal one, which facilitates the derivation of TNVE buffer and identification of sub-important links. These benefits make the proposed method efficient and effective for solving the TNVE problem. The applicability of the proposed method is demonstrated with small and medium-sized networks, as well as a large-scale real road network. Numerical experiments are conducted to illustrate the usage of TNVE for vulnerability analysis of transportation networks.

Vulnerability analysis in complex networks under a flood risk reduction point of view

The measurement and mapping of transportation network vulnerability to natural hazards constitute subjects of global interest for a sustainable development agenda and as means of adaptation to climate change. During a flood, some elements of a transportation network can be affected, causing the loss of lives. Furthermore, impacts include damage to vehicles, streets/roads, and other logistics services - sometimes with severe economic consequences. The Network Science approach may offer a valuable perspective considering one type of vulnerability related to network-type critical infrastructures: the topological vulnerability. The topological vulnerability index associated with an element is defined as reducing the network’s average efficiency due to removing the set of edges related to that element. In this paper, we present the results of a systematic literature overview and a case study applying the topological vulnerability index for the highways in Santa Catarina (Brazil). We produce a map considering that index and areas susceptible to urban floods and landslides. Risk knowledge, combining hazard and vulnerability, is the first pillar of an Early Warning System and represents an important tool for stakeholders of the transportation sector in a disaster risk reduction agenda.

Vulnerability and robustness of interdependent transport networks in north-western Italy

Infrastructure networks have become increasingly complex, whose progressively higher levels of interdependence make them even more vulnerable. This empirical analysis based on the Morandi bridge collapse examines the robustness and vulnerability of the motorway and railway networks in north-western Italy. By following a network topology-based approach, motorways and railways are studied as one single interconnected multi-layer transport infrastructure. Based on the concepts of geographic and functional interdependence the study provides insight into which nodes (and links) should be restored as quickly as possible when an emergency and destructive event renders them inaccessible. Moreover, it highlights the greater fragility of the intermodal network which opens up the debate on regulation and coordination of restoring measures carried out by the relevant authorities.

Modeling the Vulnerability and Resilience of Interdependent Transportation Networks under Multiple Disruptions

Because infrastructure systems are highly interconnected, it is crucial to analyze their vulnerability and resilience with the consideration of interdependencies. This paper constructed a bus–metro interdependent network model based on the passenger transfer relationship and used deep learning to identify the network topology attributes. The vulnerability process of the interdependent network to different disruptions under structural and functional perspective was studied. On this basis, this paper adopted a resilience assessment framework and mainly focused on modeling and resilience analysis of interdependent networks’ recovery processes. The optimal and instructive recovery strategy was determined, and it is shown that the increase of the coupling distance cannot alleviate the vulnerability of the interdependent network effectively; after the tolerance coefficient reaches the threshold, the effect on the vulnerability of the dependent network is weakened; and a betweenness-based strategy (BBS) works best in the preferential recovery of key nodes.

Humanitarian aid distribution logistics with accessibility constraints: a systematic literature review

PurposeThe purpose of this paper is to review the relevant literature in order to identify trends and suggest some possible directions for future research in the framework of humanitarian aid distribution logistics with accessibility constraints.Design/methodology/approachThe authors developed a systematic literature review to study the state of the art on distribution logistics considering accessibility constraints. The electronic databases used were Web of science, Scopus, Science Direct, Jstor, Emerald, EBSCO, Scielo and Redalyc. As a result, 49 articles were reviewed in detail.FindingsThis study identified some gaps, as well as some research opportunities. The main conclusions are the need for further studies on the interrelationships and hierarchies of multiple actors, explore intermodality, transshipment options and redistribution relief goods to avoid severe shortages in some nodes and excess inventory in others, studies of the vulnerability of transport networks, correlational analysis of road failures and other future lines.Research limitations/implicationsThe bibliography is limited to peer-reviewed academic journals due to their academic relevance, accessibility and ease of searching. Most of the studies included in the review were conducted in high-income countries, which may limit the generalizability of the results to low-income countries. However, the authors focused on databases covering important journals on humanitarian logistics.Originality/valueThis paper contextualises and synthesises research into humanitarian aid distribution logistics with accessibility constrains, highlights key themes and suggests areas for further research.

Measurement and ranking of important link combinations in the analysis of transportation network vulnerability envelope buffers under multiple-link disruptions

This study proposes an optimization-based approach to rank the importance of link combinations and analyze network vulnerability in extreme and near-extreme cases of disruption under the simultaneous disruption of multiple links. A vulnerability envelope concept is used, which considers the worst and best network performance under multiple-link disruptions. This study goes a step further than previous studies, which have focused on the extreme cases that form the boundary of a vulnerability envelope, to investigate the near-extreme cases inside an envelope and the network performance buffers (i.e., the differences in network performance) between different cases. A flexible framework based on combinatorial optimization modeling is used to determine the most important link combinations and the lower and upper bounds of network performance under their disruptions, which form the vulnerability envelope. A constraint-based method is developed to iteratively identify sub-important link combinations that lead to the formation of buffers of the lower and upper bounds of the vulnerability envelope. Numerical experiments are conducted to illustrate the properties and applicability of the proposed method. The results demonstrate that the consideration of near-extreme cases yields additional valuable information that is not generated by the traditional vulnerability analysis, which is focused on extreme cases. Ranking of the most and sub-most important link combinations enables the identification of non-unique worst/best cases, thereby revealing alternative link combinations to better inform decision-making. Consideration of the network performances in extreme and near-extreme cases affords a less conservative vulnerability assessment and reveals the potential cost of considering only extreme cases in decision-making processes.

Adaptive Flood Resilient City Design Strategies: An Exploratory Analysis of the Impact of Flooding on Street Network of Dhaka City

Flood incidents are becoming a common circumstance all over the world due to rapid urbanization and climate change. The dependence on flood control structures is becoming unsustainable and modern approaches are taking place with improved spatial planning, design strategies, adaptation techniques, and forecasting. All the major cities in developing countries like Bangladesh are facing flooding issue. The immediate impact on the urban environment is found in the street network due to flooding. Most of the previous studies are focused on the topography to understand the flooding or vulnerability of transport networks with traffic issues, but less attention is given to the street network performance during flooding and possible strategies for solving those issues. This research aims to understand the appropriateness of flooding resilience vs flooding prevention from a context-sensitive point of view of Dhaka city by identifying flooding impact on the road network. Spatial network analysis with sDNA and flooding data from World Bank helped to understand the relationship between street networks, and before-after situations during flooding. The circumstantial impact on the street network by flooding was visualized with GIS and sDNA analysis to define its performance and possible alternative solutions. This research will help to dictate future planning policy frameworks of Dhaka city derived from this exploratory study. Also, this research endeavors to help the government and corresponding authorities of flood-prone cities to enhance an inclusive strategic tool for the existing and future planning policy by developing shortterm and long-term strategic vision.

Vulnerability of road transportation networks under natural hazards: A bibliometric analysis and review

The vulnerability of the road transportation networks' infrastructures worldwide that can adversely be affected by the extreme weather conditions needs comprehensive assessment for reliable performance, mitigating the traffic hindrance and risks of accidents. Despite many efforts a clear understanding of the vulnerability of road transportation networks remains deficient. Based on this fact, this work bibliometrically analyzed the vulnerability of road transportation networks using 635 state-of-the-art articles published (Scopus database) during 1975–2020. The main purpose was to examine all-inclusively the evolution of diverse scientific studies in this field to ascertain the future research trends and benefits. In addition, the recent research progress and future drifts concerning the vulnerability of transportation networks were evaluated based on the published papers contributed by authors from various nations and co-incidences of authors’ keywords. The proposed bibliometric analyses disclosed that the publications related to the vulnerability in transportation networks have significantly been increased since 2013. Approximately 70.6% countries showed research collaborations or partnership with at least one country. The USA and China presented a significant increase in the research trends in this area. It was found that the vulnerability studies have evolved significantly to include multi-dimensional evaluations, optimization approaches, multi-objective algorithm in order to minimize the disaster impacts and a GIS-based framework to create automated solution on the impacts of transportation network due to natural disasters. There has been a gradual acceptance that the benefit-cost ratios associated with vulnerability reduction are greatly favorable for the mitigation of the disaster risk to make economic sense.

Accessibility-based vulnerability analysis of multi-modal transportation networks with weibit choice models

This study proposes utility-based accessibility measures and a weibit-based analysis method for analyzing multi-modal transportation network vulnerability. To account for the multi-dimensional travel choice behavior in multi-modal transportation networks, an advanced weibit-based combined modal split and traffic assignment model is adopted to derive the accessibility measures based on the weibit-expected travel disutility from both route choice and mode choice dimensions. The accessibility at the modal split level is derived from the nested weibit model, while that at the route choice level is obtained based on the path-size weibit model. The proposed weibit-based vulnerability measures are inherently suitable for assessing the relative degradation in network performance and can measure the vulnerability of networks with heterogeneous scales without overestimating the importance of modes or routes sharing similar features. Using a simplified multi-modal transportation network of Hong Kong, numerical experiments are conducted to demonstrate the properties of the proposed multi-modal vulnerability analysis. The results indicate that the proposed analysis can effectively address similarity and heterogeneity issues in the analysis of choice behavior and network vulnerability, which are often ignored by the traditional logit-based measures.

Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network

With the rise of global trade, maritime transportation networks have become an indispensable element of logistics networks. Approximately 80% of the global trade volume is transported by sea with the maritime logistics network fueling global economic integration. Due to the uncertainty of the transportation process and the impact of accidents, the reliability analysis of the logistics network is a topic of immense interest. In this paper, we propose an original and novel model to quantitatively analyze the vulnerability of the maritime logistics network by considering the importance of each port in the network. Three centrality measures that consider different topology information of the network are used in this paper to identify the importance of ports. Different information about the network is considered through the joint entropy and the multiscale factor q to evaluate the vulnerability of the logistics network. The Asia–Europe maritime transportation network serves as a real-world example to demonstrate the effectiveness and applicability of our proposed model. The experimental results suggest that the performance of the maritime network is closely related to the heterogeneity of the connectivity pattern and the process of decentralization can reduce the vulnerability of the maritime network.

Vulnerability of Transport Networks Under Disruption of Their Collaborations: A Multi-Layer Network Model

Vulnerability of Transport Networks Under Disruption of Their Collaborations: A Multi-Layer Network Model

Vulnerability of Transport Networks Under Disruption of Their Collaborations: A Multi-Layer Network Model

Vulnerability of Transport Networks Under Disruption of Their Collaborations: A Multi-Layer Network Model

Vulnerability of the worldwide air transportation network to global catastrophes such as COVID-19

This paper studies the vulnerability of the worldwide air transportation network (WATN) during a global catastrophe such as COVID-19. Considering the WATN as a weighted network, many airport connections could be completely or partially disrupted during such extreme events. However, it is found that existing weighted metrics cannot reflect the impact of connection capacity reduction on network connectivity. Therein, this work proposes a novel network efficiency metric termed as layered weighted network efficiency (LWNE) metric to measure the connectivity of the air transportation networks (ATNs) and study their vulnerability in response to different levels of disruptions, including airport level, country level, and global level. The most critical airport connections and their impact on network connectivity are identified. It is found that the critical connections are mostly between so-called bridge airports but not core airports in the WATN. By examining the impact of partial link disruptions, it is found that some connections mainly serve local travel demand and are very robust to partial disruptions, while the others connecting global hubs are sensitive to partial disruptions. Further, the WATN is robust to the individual disconnection of most countries; however, it is vulnerable to the simultaneous disconnection of countries that serve international transfers. Interestingly, the WATN is insensitive to the disconnection between any two countries, even those with sizeable domestic ATNs. Concerning global disconnections, as long as all the international connections hold 10% of their original flights, the WATN can still expect 40% of its pre-disruption performance. This paper deepens the understanding of ATNs under extreme events and provides a method for studying transportation networks’ vulnerability facing global disruptions.

Infrastructure-based transportation network vulnerability modeling and analysis

Most studies evaluating impacts and consequences of disruptive events on transportation network performance have focused on the measurement of transportation network vulnerability from macroscopic perspectives. Few works explore the effects of road infrastructure attributes on network vulnerability from a mesoscopic perspective. Road sections with different infrastructure attributes could have different impacts on the vulnerability of transportation network under disruptions. Overlooking of these differences about attributes would produce inaccurate or incorrect results of vulnerability assessment as well as subsequent countermeasure suggestions. This study proposes an accessibility approach addressing attributes of road infrastructure to measure road network vulnerability. In particular, the methodology explores the impacts of road alignment and types on network degradation under accidents. This approach was tested on the highway network of Florida, USA. Results show that various road alignment and types could have different impacts on the accessibility of road network. Road network vulnerability is obviously affected by road alignment and types. When road sections are more curved, the network becomes more vulnerable under disruptions. More bridge and tunnel sections in transportation network would result in higher vulnerability of the highway network. This work could also assist decision makers when designing and managing road infrastructures under disasters.

Public Transport Network Vulnerability and Delay Distribution among Travelers

Methodologies and approaches for assessing the vulnerability of a public transport network are generally based on quantifying the average delay generated for passengers by some type of disruption. In this work, a novel methodology is proposed, which combines the traditional approach, based on the quantitative evaluation of averaged disruption effects, with the analysis of the asymmetry of effects among users, by means of Lorenz curves and Gini index. This allows evaluating whether the negative consequences of disruptions are equally spread among passengers or if differences exist. The results obtained show the potential of the proposed method to provide better knowledge about the effects of a disruption on a public transport network. Particularly, it emerged that disrupted scenarios that appear similar in terms of average impacts are actually very different in terms of the asymmetry of effects among users.

Sparse rail network robustness analysis: Functional vulnerability levels of accidents resulting from human errors

Transportation network vulnerability analysis has developed increasingly in the last decade with the goal to identify the most critical locations against incidences. In this domain, many of the previous researches have focused on congested urban networks; however, there is still a need to consider regional and interurban sparse rail networks, specifically those networks in developing countries. In such sparse rail networks, there are limited possibilities to redirect trains if a link is disrupted, there might be less possibility of finding redundant alternative routes, and network failures are usually accompanied by a phenomenon called ‘unsatisfied demand.’ The study reported in this paper stemmed from research aimed to design precautionary actions for a developing country's sparse railway system. Our study framework deemed to find the most vulnerable part of an inter-urban sparse rail network using a network scan approach, which found the consequences of network disruptions. A number of criteria were defined to determine the total cost including unsatisfied demand and additional transportation costs due to disruptions. The results showed that how well the process of the vulnerability analysis, considering the features of both supply and demand sides, can be a guide for railway authorities in applying system safety measures.

City transportation network vulnerability to disasters: the case of Hurricane Hermine in Florida

ABSTRACT Hurricanes affect millions of people in the U.S. every year and cause billion-dollar economic losses. Florida is one of the states in the U.S. which is vulnerable to hurricanes and major infrastructure damages were reported due to these extreme events such as Hurricane Hermine (2016). This study aims to assess the impacts of Hermine on the transportation network of Tallahassee, the capital of Florida, using a spatial-analytical approach and real-world hurricane data on roadway closures, power outages, power network configuration, and other storm-related variables. First, a geographic information systems (GIS)-based analysis was utilised to obtain the spatial patterns of hurricane-induced roadway closures along with power outages, power lines, downed trees, and the city’s flood hazard zones. Second, a statistical model was developed to understand the association between the aforementioned variables and roadway closures. The spatial model results revealed that the roadway closures and power outages almost have the same patterns, and the city centre experienced more disruptions than other areas. The statistical model findings indicated that the power outages and power lines have strong relationships with roadway closures. The obtained knowledge of this study can provide valuable information for city officials to prepare better emergency policies for future potential hurricanes.

Topological-Based Measures with Flow Attributes to Identify Critical Links in a Transportation Network

An important part of transportation network vulnerability analysis is identifying critical links where failure may lead to severe consequences, and the potential of such incidents cannot be considered negligible. Existing transportation network vulnerability assessment can be categorized as topological, or traffic based. Topological-based assessment identifies the most critical components in the network by considering network structure and connectivity. Traffic-based assessment identifies the most critical components in the network by full-scan analysis and takes into consideration effects of link failures to traffic flow assignment. The former approach does not consider traffic flow dynamics and fails to capture the non-linearity performance function of transport systems while the latter, even though accurate and robust, requires significant computational power and time and may not always be feasible for real life size networks. The primary objective of this paper is to propose new link criticality measures and evaluate their accuracy for transportation network vulnerability assessment. These measures combine characteristics of traffic equilibrium and network topology to balance accuracy and computational complexity. Nine measures are proposed, and their accuracy is compared with three existing traffic-based measures using three case study transportation networks from the literature. Results indicate that three of the proposed measures show strong correlation to the three traffic-based measures while requiring significantly less computational power and time.

Analysis of Transportation Network Vulnerability and Resilience within an Urban Agglomeration: Case Study of the Greater Bay Area, China

Recently, urban agglomerations have become the main platform of China’s economic development. As one of those, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has an important strategic position in national blueprints. Its amazing achievement is inseparable from reliable and resilient transportation networks. With the aim of improving the sustainability of the GBA, this paper presents a novel view of vulnerability and resilience of integrated transportation networks within an urban agglomeration. According to complex network theory, the integrated transportation network model of the GBA was established. Various scenarios were considered to improve the overall level of defensive ability, including random failures, targeted attacks and natural hazards. Vulnerability and resilience assessment models were developed to investigate the influences on the whole network. Finally, a simulation analysis was conducted on the GBA to examine the variations in network performance when faced with different attack scenarios. The results indicate that the transportation network of the GBA is more vulnerable and has less resilience to targeted attacks, while natural hazards had little influence on the performance, to a certain extent. Moreover, the betweenness recovery strategy seemed to be the best choice for every attack scenario.