Transportation Network Vulnerability Research Articles

Probabilistic assessment of transport network vulnerability with equilibrium flows

This article develops a probabilistic approach for assessing transport network vulnerability. A novel performance measure is proposed to evaluate the expected impact when multiple transport network components fail simultaneously at various degrees. The proposed measure captures both the likelihood and consequence of a combination of transport network component failures. The most critical combination of transport network component failures is obtained by solving a bi-level optimization problem. The upper-level problem is to solve for the combination of transport network components together with their corresponding disruption levels, which induces the maximum reduction in the performance measure. The lower-level problem is to capture the response of travelers to network changes due to network component failures and is formulated as a traffic assignment problem. The clonal selection algorithm (CSA), a biologically inspired approach, is adopted to tackle the proposed bi-level optimization problem. Numerical results indicate that neglecting partial capacity degradation and its probability of occurrence could misestimate the worst scenario, and different vulnerability assessment approaches could identify similar critical components but our approach can discover some components that are not found by other existing approaches. Moreover, it is shown that the CSA outperforms the well-known genetic algorithm in terms of solution quality in a large network.

Assessing potential likelihood and impacts of landslides on transportation network vulnerability

As one of the devastating natural disasters, landslide may induce significant losses of properties and lives area-wide, and generate dramatic damages to transportation network infrastructure. Accessing the impacts of landslide-induced disruptions to roadway infrastructure can be extremely difficult due to the complexity of involved impact factors and uncertainties of vulnerability related events. In this study, a data-driven approach is developed to assess landslide-induced transportation roadway network vulnerability and accessibility. The vulnerability analysis is conducted by integrating a series of static and dynamic factors to reflect the landslide likelihood and the consequences of network accessibility disruptions. The analytical hierarchy process (AHP) model was developed to assess and map the landslide likelihood. A generic vulnerability index (VI) was calculated for each roadway link in the network to identify critical links. Spatial distributions of landslide likelihood, consequences of network disruptions, and network vulnerability degrees were fused and analyzed. The roadway network on Oahu Island in Hawaii is utilized to demonstrate the effectiveness of the proposed approach with all the geo-coded information for its network vulnerability analysis induced by area-wide landslides. Specifically, the study area was classified into five categories of landslide likelihood: very high, high, moderate, low, and stable. About 34% of the study area was assigned as the high or very high categories. The results of network vulnerability analyses highlighted the importance of three highway segments tunnel through the Ko‘olau Range from leeward to windward, connecting Honolulu to the windward coast including the Pali highway segment, Likelike highway segment, and Interstate H-3 highway segment. The proposed network vulnerability analysis method provides a new perspective to examine the vulnerability and accessibility of the roadway network impacted by landslides.

Flooding related traffic crashes: findings from association rules

In the United States, flooding related crashes have exposed the vulnerability of transport networks. Without realizing the depth of a flooded roadway, some may attempt to cross. At night during heavy storms, determining if a road is flooded is especially difficult. Only 18–24 inches of moving water are needed to sweep away a truck, and only 6 inches are needed to carry away a small car. Louisiana’s geographic location places the state in a unique position to receive both frontal tropical hurricanes and large air masses, which may result in high air moistures in almost any direction and drop rain with heavy intensity. In 2016, 12% of flooding related crashes occurred in Louisiana. During 2010–2016, flooding resulted in a total of 449 crashes in Louisiana with a total of 22 fatalities. This study collected seven years (2010–2016) of flooding related crash data to identify the key contributing factors. The findings show that two-way roadway with separation, rear-end crashes, higher average precipitation, and driver violations are frequently seen in the generated rules. This study provides a comprehensive picture of flooding related to traffic crashes; thus, targeting suitable countermeasures can be devised to reduce the number of crashes.

Internet of Things Based Solutions for Transport Network Vulnerability Assessment in Intelligent Transportation Systems

Intelligent Transportation System (ITS) is essential for effective identification of vulnerable units in the transport network and its stable operation. Also, it is necessary to establish an urban transport network vulnerability assessment model with solutions based on Internet of Things (IoT). Previous research on vulnerability has no congestion effect on the peak time of urban road network. The cascading failure of links or nodes is presented by IoT monitoring system, which can collect data from a wireless sensor network in the transport environment. The IoT monitoring system collects wireless data via Vehicle-to-Infrastructure (V2I) channels to simulate key segments and their failure probability. Finally, the topological structure vulnerability index and the traffic function vulnerability index of road network are extracted from the vulnerability factors. The two indices are standardized by calculating the relative change rate, and the comprehensive index of the consequence after road network unit is in a failure state. Therefore, by calculating the failure probability of road network unit and comprehensive index of road network unit in failure state, the comprehensive vulnerability of road network can be evaluated by a risk calculation formula. In short, the IoT-based solutions to the new vulnerability assessment can help road network planning and traffic management departments to achieve the ITS goals.

Graph Theory Approach to the Vulnerability of Transportation Networks

Nowadays, transport is the basis for the functioning of national, continental, and global economies. Thus, many governments recognize it as a critical element in ensuring the daily existence of societies in their countries. Those responsible for the proper operation of the transport sector must have the right tools to model, analyze, and optimize its elements. One of the most critical problems is the need to prevent bottlenecks in transport networks. Thus, the main aim of the article was to define the parameters characterizing the transportation network vulnerability and select algorithms to support their search. The parameters proposed are based on characteristics related to domination in graph theory. The domination, edge-domination concepts, and related topics, such as bondage-connected and weighted bondage-connected numbers, were applied as the tools for searching and identifying the bottlenecks in transportation networks. Furthermore, the algorithms for finding the minimal dominating set and minimal (maximal) weighted dominating sets are proposed. This way, the exemplary academic transportation network was analyzed in two cases: stationary and dynamic. Some conclusions are presented. The main one is the fact that the methods given in this article are universal and applicable to both small and large-scale networks. Moreover, the approach can support the dynamic analysis of bottlenecks in transport networks.

Evaluating the Vulnerability of Time-Sensitive Transportation Networks: A Hub Center Interdiction Problem

Time-sensitive transportation systems have received increasing research attention recently. Examples of time-sensitive networks include those of perishable goods, high-value commodity, and express delivery. Much research has been devoted to optimally locating key facilities such as transportation hubs to minimize transit time. However, there is a lack of research attention to the reliability and vulnerability of time-sensitive transportation networks. Such issues cannot be ignored as facilities can be lost due to reasons such as extreme weather, equipment malfunction, and even intentional attacks. This paper proposes a hub interdiction center (HIC) model for evaluating the vulnerability of time-sensitive hub-and-spoke networks under disruptions. The model identifies the set of hub facilities whose loss will lead to the greatest increase in the worst-case transit time. From a planning perspective, such hubs are critical facilities that should be protected or enhanced by preventive measures. An efficient integer linear programming (ILP) formulation of the new model is developed. Computational experiments on a widely used US air passenger dataset show that losing a small number of hub facilities can double the maximum transit time.

Vulnerability of Transport Networks to Multi-Scenario Flooding and Optimum Location of Emergency Management Centers

Floods are the climatic factors that cause more significant impacts on transportation infrastructures. This circumstance could get worse, taking into account climate change effects. The literature points out different adaptation measures to minimize the possible increasing effects caused by climate change. Among them is the improvement of the vulnerability of a transport network and Emergency Management Systems. The effective management of emergencies is of vital importance to minimize the potential damage resulting from a catastrophe. Given such circumstances, analysis of the vulnerability of networks is a technique whose results highlight deficiencies and serve as support for future decisions concerning the transformation of the network or the installation of new emergency centers. The main objective of this research is to highlight the vulnerability of the road network in a variety of multi-contingency scenarios related to flooding and to identify the optimal location for a new emergency management center based on that analysis. The results obtained could be used in urban planning tasks to improve the resilience of urban areas in the face of an increase in flood episodes caused by climate change.

Leveraging socio-ecological resilience theory to build climate resilience in transport infrastructure

ABSTRACTAnthropogenic climate change poses risks to transport infrastructure that include disrupted operations, reduced lifespan and increased reconstruction and maintenance costs. Efforts to decrease the vulnerability of transport networks have been largely limited to understanding projected risks through governance and administrative efforts. Where physical adaptation measures have been implemented, these have typically aligned with a traditional “engineering resilience” approach of increasing the strength and rigidity of assets to withstand the impacts of climate change and maintain a stable operating state. Such systems have limited agility and are susceptible to failure from “surprise events”. Addressing these limitations, this paper considers an alternate approach to resilience, inspired by natural ecosystems that sense conditions in real-time, embrace multi-functionality and evolve in response to changing environmental conditions. Such systems embrace and thrive on unpredictability and instability. This paper synthesises key literature in climate adaptation and socio-ecological resilience theory to propose a shift in paradigm for transport infrastructure design, construction and operation, towards engineered systems that can transform, evolve and internally manage vulnerability. The authors discuss the opportunity for biomimicry (innovation inspired by nature) as an enabling discipline for supporting resilient and regenerative infrastructure, introducing three potential tools and frameworks. The authors conclude the importance of leveraging socio-ecological resilience theory, building on the achievements in engineering resilience over the past century. These findings have immediate practical applications in redefining resilience approaches for new transport infrastructure projects and transport infrastructure renewal.

Vulnerability Analysis of Intercity Multimode Transportation Networks; A Case Study of the Yangtze River Delta

The disruption of an intercity transportation network will seriously influence the economic activities and communication between cities. At the regional or national transportation network level, in most cases, there is no link redundancy because of the high construction cost of the extra transportation infrastructure, so the impacts caused by the disruption of regional intercity transportation networks should be paid more attention. This paper proposes an accessibility-based method to analyze the vulnerability of multimode transportation networks. The measurement captures the influence of the disruption of network components in terms of the travel cost, socio-economic impacts, and level of transportation service of cities, and besides the network vulnerability analysis, it can also be used in the analysis of city relationships and development status of cities, providing a reference direction of the sustainable development for the city cluster. Finally, with the rapid application of high-speed trains in China, a preliminary study of the public transportation network of the Yangtze River Delta (YRD) region is conducted to illustrate the applicability of the evaluating method. The results show that the proposed measurement can be used to analyze the transportation network from the perspective of socio-economic impacts and level of transportation service, providing a reference for network planners and managers.

Vulnerability of public transportation networks against directed attacks and cascading failures

This paper presents some results devoted to providing network analysis functionalities for vulnerability assessment in public transportation networks with respect to disruptive events and/or targeted attacks to stations. The results have been obtained on two public transportation networks: the bus network in Florence, Italy, and the transportation network in the Attika region, Greece. The analysis implements a topological approach, based on graph theory, using a multi-graph to model public transportation networks and analyse vulnerabilities with respect to the removal of one or more of their components. Both directed attacks and cascading failures are considered. While the first type of disruptive events is related to a static analysis, where nodes are removed according to a rank related to some centrality measures, the second type is related to a dynamic analysis, where a failure cascade is simulated making unavailable the node with the highest betweenness value. Vulnerability measures are computed as loss of connectivity and efficiency, with respect to both the two different types of disruptive events considered. This study allows to evidence potential vulnerabilities of the urban networks, that must be considered to support the planning process into the creation of resilient structures.

Resilient transport systems to reduce urban vulnerability to floods in emerging-coastal cities: A case study of Ho Chi Minh City, Vietnam

The role of transportation is becoming ever more important as cities are spatially expanded along with urban development, yet highly agglomerated by complex activities over their geographic territory. Flooding incidents in cities across the world have exposed the vulnerability of transport networks which can result in significant, lasting disruption. This appears to be overlooked in emerging-coastal cities, especially prone to flooding as plans for transport development, are ultimately driven by economic drivers resulting in uncontrolled urbanisation. By using a combined method of hydrological flood modeling and GIS analysis, this paper demonstrates the increasing vulnerability of the transport system in Ho Chi Minh City based on current plans for transport development. The paper highlights the need to consider a new approach to transport planning and advocates the application of a Resilient Transport System (RTS) which can be integrated into potential revisions of city master plans to help Ho Chi Minh City (HCMC) shift from resistance to resilience to extreme floods. The focal point of the concept is the spatial transfer of transport flows based on a pre-organised structural and flexible transport system constituted by links, nodes and relevant services in terms of different levels of elevation and locations. The intrinsic value of its application to the transport plan is that a city can retain a certain capacity (probably on a smaller scale) of its transport system in order to mitigate potential impacts on urban activities resulting from flood disruptions.

Evaluation of Seismic vulnerability of transport networks with an emphasis on criteria earth resistance and design of routes and rescue using GIS

Evaluation of Seismic vulnerability of transport networks with an emphasis on criteria earth resistance and design of routes and rescue using GIS

Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective

Robust public transport networks are important, since disruptions decrease the public transport accessibility of areas. Despite this importance, the full passenger impacts of public transport network vulnerability have not yet been considered in science and practice. We have developed a methodology to identify the most vulnerable links in the total, multi-level public transport network and to quantify the societal costs of link vulnerability for these identified links. Contrary to traditional single-level network approaches, we consider the integrated, total multi-level PT network in the identification and quantification of link vulnerability, including PT services on other network levels which remain available once a disturbance occurs. We also incorporate both exposure to large, non-recurrent disturbances and the impacts of these disturbances explicitly when identifying and quantifying link vulnerability. This results in complete and realistic insights into the negative accessibility impacts of disturbances. Our methodology is applied to a case study in the Netherlands, using a dataset containing 2.5 years of disturbance information. Our results show that especially crowded links of the light rail/metro network are vulnerable, due to the combination of relatively high disruption exposure and relatively high passenger flows. The proposed methodology allows quantification of robustness benefits of measures, in addition to the costs of these measures. Showing the value of robustness, our work can support and rationalize the decision-making process of public transport operators and authorities regarding the implementation of robustness measures.

An innovative gravity-based approach to assess vulnerability of a Hazmat road transportation network: A case study of Guangzhou, China

The transportation of hazardous material (hereinafter referred to as Hazmat) is different from general cargo. If a Hazmat road transportation accident occurs, it will not only cause significant casualties and road network damage but also threaten the safety of the lives and property of the residents near the road. Therefore, a quantitative vulnerability analysis of the Hazmat road transportation network is developed to assess the vulnerability of each link, which can help improve the road transportation risk management level. First, we propose an indicator to measure the relevance between two links based on comprehensive analysis of the road transportation network topology and Hazmat road transportation risk characteristics. Second, we discover that we cannot identify road vulnerability using only topology and risk characteristics alone. Thus, an Impact Strength model is developed to assess Hazmat road transportation vulnerability. This model is based on the classical Gravity model and considers both topology and risk characteristics. Relevant algorithms are proposed accordingly. Third, we use Guangzhou’s Hazmat highway transportation as a case study to verify our Impact Strength model. The related statistics data are collected, and ArcGIS software is employed. By using this model, we can calculate the Impact Strength of each link in the whole transportation network. The empirical results verify that this innovative Impact Strength model can help to identify the links with significant vulnerabilities, which can thus help to reduce road transportation risk in advance and build the road transportation risk early-warning mechanism. This innovative model can also be used to support the relevant decision-making process for further analysis.

Recovery time and propagation effects of passenger transport disruptions

We propose a method to evaluate public transport network vulnerability. We study the evolution of the passenger Volume Over Capacity (VOC) ratio throughout the network to measure the spatial and temporal extent of the impacts caused by an unplanned service segment disruption. The VOC ratio provides an indication of the on-board travel comfort, an important level-of-service indicator, as well as reflects the residual capacity for absorbing additional demand. Because of the dynamic nature of public transport systems, disturbances propagate through the network in both time and space. Our modelling approach is able to capture transit system dynamics and quantify the extent to which the network exhibits spillover effects. We apply the method to the case of the rapid public transport system of Stockholm Sweden We demonstrate how the changes in network saturation and the corresponding recovery time can be quantified.

Assessing network vulnerability of heavy rail systems with the impact of partial node failures

Much of the literature in recent years has examined the vulnerability of transportation networks. To identify appropriate and operational measures of nodal centrality using connectivity in the case of heavy rail systems, this paper presents a set of comprehensive measures in the form of a Degree of Nodal Connection (DNC) index. The DNC index facilitates a reevaluation of nodal criticality among distinct types of transfer stations in heavy rail networks that present a number of multiple lines between stations. Specifically, a new classification of transfer stations—mandatory transfer, non-mandatory transfer, and end transfer—and a new measure for linkages—link degree and total link degree—introduces the characteristics of heavy rail networks when we accurately expose the vulnerability of a node. The concept of partial node failure is also introduced and compare the results of complete node failure scenarios. Four local and global indicators of network vulnerability are derived from the DNC index to assess the vulnerability of major heavy rail networks in the United States. Results indicate that the proposed DNC indexes can inform decision makers or network planners as they explore and compare the resilience of multi-hubs and multi-line networks in a comprehensive but accurate manner regardless of their network sizes.

Assessing Vulnerability of Transportation Networks for Disaster Response Operations

Transportation networks and systems are vulnerable to natural disasters. During disaster response operations, the degraded functionality of the system can negatively impact the affected population because disrupting relief activitiesincreases human suffering resulting from the lack of access to essential goods or services. Mathematical formulations for assessing transportation network vulnerability do not generally consider this lack of access or deprivation costs, and can lead to inappropriate strategies for humanitarian assistance. This paper proposes a transportation network vulnerability assessment model that allows identifying critical links for the development of high impact disaster response operations. The model is based on an economic analysis that considers the logistical costs of the distribution operations and the external effects derived from the delays in the provision of basic supplies (deprivation costs). The approach is particularly useful for planning resilient disaster response plans in the preparednessstage, prioritizing investment for mitigation and adaptation, and prioritizing the rehabilitation (access restoration) of the disrupted links in the response and recovery stages. In addition to numerical experiments using case study networks, the authors implemented the model to the coffee-producing region of Colombia, which was hit by an earthquake in 1999.

Research on the Vulnerability of a City Agglomeration Compound Traffic Network Based on Two Attack Strategies

To improve the ability of city agglomeration to resist emergency disruption, the model of a city agglomeration compound traffic network was constructed with a new perspective on investigating its vulnerability. First, on the basis of complex network theory, the city agglomeration compound traffic network structure was analyzed thoroughly and its model was established using the site mapping method. Then, facing the compound traffic network structure of urban agglomeration, both the different attack strategies and the measures of the vulnerability of a city agglomeration compound traffic network were proposed. Finally, taking Hohhot-Baotou-Erdos city agglomeration as an example of our empirical study, the city agglomeration road network and rail transit network were formed, and the topology characteristics and vulnerability of the compound traffic network were analyzed to identify critical sites and lines within the network. Results show that the construction of urban agglomeration compound traffic network can effectively reduce the vulnerability of a single-mode network. Moreover, strengthening the protection of the identified key sites and lines further increases the likelihood of reducing the vulnerability of urban complex transportation networks and the risks of traffic network paralysis caused by sudden disasters.

An optimization approach for deriving upper and lower bounds of transportation network vulnerability under simultaneous disruptions of multiple links

This paper aims to develop an optimization approach for deriving the upper and lower bounds of transportation network vulnerability under simultaneous disruptions of multiple links without the need to evaluate all possible combinations as in the enumerative approach. Mathematically, we formulate the upper and lower bounds of network vulnerability asa binary integer bi-level program (BLP). The upper-level subprogram maximizes or minimizes the remaining network throughput under a given number of disrupted links, which corresponds to the upper and lower vulnerability bounds. The lower-level subprogram checks the connectivity of each origin-destination (O-D) pair under a network disruption scenario without path enumeration. Two alternative modeling approaches are provided for the lower-level subprogram: the virtual link capacity-based maximum flow problem formulation and the virtual link cost-based shortest path problem formulation. Computationally, the BLP model can be equivalently reformulated asa single-level mixed integer linear program by making use of the optimality conditions of the lower-level subprograms and linearization techniques for the complementarity conditions and bilinear terms. Numerical examples are also provided to systematically demonstrate the validity, capability, and flexibility of the proposed optimization model. The vulnerability envelope constructed by the upper and lower bounds is able to effectively consider all possible combinations without the need to perform a full network scan, thus avoiding the combinatorial complexity of enumerating multi-disruption scenarios. Using the vulnerability envelope asa network performance assessment tool, planners and managers can more cost-effectively plan for system protection against disruptions, and prioritize system improvements to minimize disruption risks with limited resources.

Systemic Seismic Vulnerability of Transportation Networks and Emergency Facilities

AbstractIn the aftermath of an earthquake, structural damage and debris represent major obstructions to the mobility of evacuees and first responders and to normal economic activities. Few studies ...