Vulnerability and resilience of transport systems – A discussion of recent research

The transport system is critical to the welfare of modern societies. This article provides an overview of recent research on vulnerability and resilience of transport systems. Definitions of vulnerability and resilience are formulated and discussed together with related concepts. In the increasing and extensive literature of transport vulnerability studies, two distinct traditions are identified. One tradition with roots in graph theory studies the vulnerability of transport networks based on their topological properties. The other tradition also represents the demand and supply side of the transport systems to allow for a more complete assessment of the consequences of disruptions or disasters for the users and society. The merits and drawbacks of the approaches are discussed. The concept of resilience offers a broader socio-technical perspective on the transport system’s capacity to maintain or quickly recover its function after a disruption or a disaster. The transport resilience literature is less abundant, especially concerning the post-disaster phases of response and recovery. The research on transport system vulnerability and resilience is now a mature field with a developed methodology and a large amount of research findings with large potential practical usefulness. The authors argue that more cross-disciplinary collaborations between authorities, operators and researchers would be desirable to transform this knowledge into practical strategies to strengthen the resilience of the transport system.     

The role of travel demand and network centrality on the connectivity and resilience of an urban street system

In the transportation literature, two major and parallel approaches exist to identify the critical elements of a transportation system. On the one hand, conventional transportation engineering emphasizes travel demand, often in terms of traffic volume (i.e., demand side). On the other hand, newer techniques from Network Science emphasize network topology (i.e., supply side). To better understand the relationship between the two approaches, we first investigate whether they correlate by comparing traffic volume and node centrality. Second, we assess the impact of the two approaches on the connectivity and resilience of a transportation network; connectivity is measured by the relative size of the giant component, and resilience is measured by the network’s adaptive capacity (the amount of extra flow it can handle). The urban road system of Isfahan (Iran) is used as a practical case study. Overall, we find that traffic volume indeed correlates with node centrality. In addition, we find that the weighted degree of a node, i.e., the sum of the capacities of its incident links (for small disruptions) and node betweenness (for large disruptions), best captures node criticality. Nodes with high weighted degree and betweenness should therefore be given higher priority to enhance connectivity and resilience in urban street systems. Regarding link criticality, roads with higher capacities showed a more important role as opposed to betweenness, flow, and congestion.

     

An integrated measure of accessibility and reliability of mass transit systems

The growth of a city or a metropolis requires well-functioning transit systems to accommodate the ensuing increase in travel demand. As a result, mass transit networks have to develop and expand from simple to complex topological systems over time to meet this demand. Such an evolution in the networks’ structure entails not only a change in network accessibility, but also a change in the level of network reliability on the part of stations and the entire system as well. Network accessibility and reliability are popular measures that have been widely applied to evaluate the resilience and vulnerability of a spatially networked system. However, the use of a single measure, either accessibility or reliability, provides different results, which demand an integrated measure to evaluate the network’s performance comprehensively. In this paper, we propose a set of integrated measures, named ACCREL (Integrated Accessibility and Reliability indicators) that considers both metrics in combination to evaluate a network’s performance and vulnerability. We apply the new measures for hypothetical mass transit system topologies, and a case study of the metro transit system in Seoul follows, highlighting the dynamics of network performance with four evolutionary stages. The main contribution of this study lies in the results from the experiments, which can be used to inform how transport network planning can be prepared to enhance the network functionality, thereby achieving a well-balanced, accessible, and reliable system. Insights on network vulnerability are also drawn for public transportation planners and spatial decision makers.     

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

ABSTRACT

Anthropogenic 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.     

Emergence of resilience as a framework for state Departments of Transportation (DOTs) in the United States

State Departments of Transportation (DOTs) in the United States are responsible for a large portfolio of transportation modes and services, including passenger and freight systems. These responsibilities include operations under routine conditions and during incidents and events that result from various natural and human-caused hazards. During unexpected events, disruptions and reductions in service result in requiring the reallocation and reassignment of personnel, modal, and economic resources. To better prevent and respond to the effects of service disruptions, the concept of resilience has emerged as an important framework, within which, DOTs across the United States are using to plan for the occurrence of threats. In this paper, the key findings of recent reviews of literature and practice related to resilience among state DOTs in the United States are summarized. The review effort focused on a range of risks faced by transportation agencies including climate change, terrorism, cyber-attacks, and aging infrastructure and the ways in which DOTs are confronting them in practice. The topics of this paper range from the fundamental, including definitions of transportation resilience; to the more complex such as examinations of risk, vulnerability and threats; to the most sophisticated topics including administrative-level efforts to conceptualize evolving transportation planning and policies within a resilience framework.     

Scheduling freight trains traveling on complex networks

In the US, freight railways are one of the major means to transport goods from ports to inland destinations. According to the Association of American Railroad’s study, rail companies move more than 40% of the nation’s total freight. Given the fact that the freight railway industry is already running without much excess capacity, better planning and scheduling tools are needed to effectively manage the scarce resources, in order to cope with the rapidly increasing demand for railway transportation. This research develops optimization-based approaches for scheduling of freight trains. Two mathematical formulations of the scheduling problem are first introduced. One assumes the path of each train, which is the track segments each train uses, is given and the other one relaxes this assumption. Several heuristics based on mixtures of the two formulations are proposed. The proposed algorithms are able to outperform two existing heuristics, namely a simple look-ahead greedy heuristic and a global neighborhood search algorithm, in terms of railway total train delay. For large networks, two algorithms based on the idea of decomposition are developed and are shown to significantly outperform two existing algorithms.     

A tabu search algorithm to solve the integrated planning of container on an inter-terminal network connected with a hinterland rail network

Transport demand for containers has been increasing for decades, which places pressure on road transport. As a result, rail transport is stimulated to provide better intermodal freight transport services. This paper investigates mathematical models for the planning of container movements in a port area, integrating the inter-terminal transport of containers (ITT, within the port area) with the rail freight formation and transport process (towards the hinterland). An integer linear programming model is used to formulate the container transport across operations at container terminals, the network interconnecting them, railway yards and the railway networks towards the hinterland. A tabu search algorithm is proposed to solve the problem. The practical applicability of the algorithm is tested in a realistic infrastructure case and different demand scenarios. Our results show the degree by which internal (ITT) and external (hinterland) transport processes interact, and the potential for improvement of overall operations when the integrated optimization proposed is used. Instead, if the planning of containers in the ITT system is optimized as a stand-alone problem, the railway terminals may suffer from longer delay times or additional train cancellations. When planning the transport of 4060 TEU containers within one day, the benefits of the ITT planning without considering railway operations account for 17% ITT cost reduction but 93% railway operational cost growth, while the benefits of integrating ITT and railway account for a reduction of 20% in ITT cost and 44% in railway operational costs.     

Data-driven perspectives for energy efficient operations in railway systems: Current practices and future opportunities

Railway systems must increase their performance and economic competitiveness to remain an effective and efficient transport mode. Energy efficiency goals are one of the main drivers for the future evolution of planning and operations of transport systems. An opportunity to improve energy efficiency together with reliability and feasibility of railway systems come from the huge amount of data being currently collected and available in the future. The hidden potential in large sets of data for improving energy efficiency can be fully exploited through novel, data-driven approaches. This paper discusses the relation of those future approaches with the current state of the art and challenges, highlighting natural advantages and possible weak points. We identify dimensions within the current literature describing the suitability of current approaches to embrace the data revolution, and the possible enhancements resulting from that. We refer to practical test cases based on real on-board monitoring of electric trains in Switzerland to identify current and future challenges in improving energy efficiency of train operations. We conclude with a discussion and a roadmap on the introduction of data-driven approaches for improving energy efficiency of railway systems.     

Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study

We present an approach to systematically analysing the vulnerability of road networks under disruptions covering extended areas. Since various kinds of events including floods, heavy snowfall, storms and wildfires can cause such spatially spread degradations, the analysis method is an important complement to the existing studies of single link failures. The methodology involves covering the study area with grids of uniformly shaped and sized cells, where each cell represents the extent of an event disrupting any intersecting links. We apply the approach to the Swedish road network using travel demand and network data from the Swedish national transport modelling system Sampers. The study shows that the impacts of area-covering disruptions are largely determined by the level of internal, outbound and inbound travel demand of the affected area itself. This is unlike single link failures, where the link flow and the redundancy in the surrounding network determine the impacts. As a result, the vulnerability to spatially spread events shows a markedly different geographical distribution. These findings, which should be universal for most road networks of similar scale, are important in the planning process of resource allocation for mitigation and recovery.     

The multi-objective railway timetable rescheduling problem

Unexpected disruptions occur for many reasons in railway networks and cause delays, cancelations, and, eventually, passenger inconvenience. This research focuses on the railway timetable rescheduling problem from a macroscopic point of view in case of large disruptions. The originality of our approach is to integrate three objectives to generate a disposition timetable: the passenger satisfaction, the operational costs and the deviation from the undisrupted timetable. We formulate the problem as an Integer Linear Program that optimizes the first objective and includes $\epsilon$-constraints for the two other ones. By solving the problem for different values of $\epsilon$, the three-dimensional Pareto frontier can be explored to understand the trade-offs among the three objectives. The model includes measures such as canceling, delaying or rerouting the trains of the undisrupted timetable, as well as scheduling emergency trains. Furthermore, passenger flows are adapted dynamically to the new timetable. Computational experiments are performed on a realistic case study based on a heavily used part of the Dutch railway network. The model is able to find optimal solutions in reasonable computational times. The results provide evidence that adopting a demand-oriented approach for the management of disruptions not only is possible, but may lead to significant improvement in passenger satisfaction, associated with a low operational cost of the disposition timetable.     

Social Media Use during Unplanned Transit Network Disruptions: A Review of Literature

Abstract

This paper explores social media's role in managing unplanned transit networks disruptions. Although literature exists more broadly on the use of social media in transit, this paper presents the first literature review in this setting. When disruptions occur, commuters require reliable, up-to-date information. Its provision reduces anxiety and allows informed choices. Social media is beneficial given it provides real-time information but it can only supplement (not replace) conventional approaches. Information reliability was critical. Research in the field of disaster management illustrates the importance of publicly contributed information. Known as “crowdsourcing”, it is part of the emerging field of crisis informatics which for the first time was linked to unplanned transit disruption management. The results highlight that social media's real-time nature can reduce disrupted travel demand; however, its utilisation can be resource-intensive. A framework presented illustrates how social media utilisation varies according to the operational characteristics of a disrupted network. Social media use as an information delivery tool is still in its infancy and an unwillingness to embrace it is an impediment to sustained growth. Crowdsourcing is one approach that could resolve the issue of transit agency resourcing whilst satisfying the increased demand and expectation for real-time information.     

Incorporating Logistics in Freight Transport Demand Models: State-of-the-Art and Research Opportunities

Freight transport demand is a demand derived from all the activities needed to move goods between locations of production to locations of consumption, including trade, logistics and transportation. A good representation of logistics in freight transport demand models allows us to predict the effects of changes in logistics systems on future transport flows. As such it provides better estimations of the costs of interaction and allows to predict changes in spatial patterns of freight transport flows more accurately. In recent years, the attention for freight modelling has been growing and new research work has appeared aimed at incorporating logistics in freight models. In this paper we review the state of the art in the representation of logistics considerations in freight transport demand models. Our focus is on the service and cost drivers of changes in logistics networks and how these affect freight transport. Our review proceeds along a conceptual framework for modelling that goes beyond the conventional 4-step modelling approach. We identify promising areas for freight modelling that have an integrative function within this framework, such as spatial computable general equilibrium models, supply chain choice models and hypernetwork models.     

An Institutional Analysis of Coordination in Liberalized Port-related Railway Chains: An Application to the Port of Rotterdam

Abstract

The European railway market has gone through a period of liberalization over the last two decades. The liberalization of the railway market has also affected port-related railway transport. Efficient port-related transport chains are key in the competition among ports, however providing this efficiency is to a large extent a coordination challenge. Many forms of coordination are needed to ensure that the railway chain operates efficiently, including the bundling of cargo, and good organization between railway companies, terminal operators and the infrastructure managers to realize an efficient use of assets. From the literature, it appears that less attention has been paid to the economic organization of port-related railway transport in general, and specifically in the new liberalized institutional environment. The goal of this paper is to come up with a framework to better understand the issue of coordination in port-related railway chains in a liberalized institutional environment. This paper presents a conceptual framework rooted in Transaction Cost Economics (TCE). Based on an in-depth study into coordination in liberalized container railway market at the Port of Rotterdam, empirical illustrations are used to adjust the TCE approach toward a dynamic model influenced by Douglas North's theory on economic and institutional change. Empirics from the port of Rotterdam show that new players have entered the railway market and their role has changed. This paper shows that coordination of railway operations has become more complex after the regime change. From a port perspective, liberalization does not lead to an optimal allocation of resources in a process that is highly operationally interdependent. In the liberalized environment, coordination arrangements are necessary to enable efficient coordination of railway operations in Rotterdam.     

Resilience and accessibility of Swedish and Dutch municipalities

Recent years have shown a rising popularity of the concept of resilience—both theoretically and empirically—in complex systems analysis. There is also a rising literature on resilience in the transport and spatial-economic field. The pluriform interpretation of resilience (e.g., engineering vs. ecological resilience) is related to methodological differences (e.g., stability in dynamics vs. evolutionary adaptivity). But in all cases the fundamental question is whether a complex system that is subjected to an external shock is able to recover, and if so, to which extent. The present paper [Based on presentation from cluster 6 (Accessibility) of the Nectar 2015 conference in Ann Arbour, USA.] aims to add a new dimension to resilience analysis in spatial systems, by addressing in particular the relationship between spatial accessibility at a municipality level and the resilience outcomes of the spatial system concerned. It does so by investigating to which extent accessibility of Swedish and Dutch municipalities has mitigated the local shock absorption from the recent economic recession. In our study the shock absorption capacity of municipal accessibility is estimated by analysing the relevant resilience indicators for the period concerned. In this context, conventional resilience indicators based on either multivariate complex data (in particular, the Foster Resilience Capacity Index) or employment data (in particular, the Martin Resilience-Employment Index) are confronted with spatial connectivity data based on local accessibility measures, so that geographical mobility may be regarded as one of the shock-mitigating factors. The empirical analysis is carried out for two countries which have both proven to be rather shock-resistant during the recent economic crisis, viz. Sweden and The Netherlands. Clearly, the geographical structure of these countries forms a sharp mutual contrast, viz. a spatially dispersed economy with a few distinct urban concentrations versus a spatially dense economy with one major metropolitan centre (the Randstad), respectively. Our experiments are carried out for the 290 municipalities in Sweden and 40 COROPs in The Netherlands. Our research findings show relevant and new insights into differences in the local recovery potential in Sweden and The Netherlands.     

Transport network criticality metrics: a comparative analysis and a guideline for selection

ABSTRACT

Transport network criticality analysis aims at ranking transport infrastructure elements based on their contribution to the performance of the overall infrastructure network. Despite the wide variety of transport network criticality metrics, little guidance is available on selecting metrics that are fit for the specific purpose of a study. To address this gap, this study reviews, evaluates and compares seventeen criticality metrics. First, we conceptually evaluate these metrics in terms of the functionality of the transport system that the metrics try to represent (either maintaining connectivity, reducing travel cost, or improving accessibility), the underlying ethical principles (either utilitarianism or egalitarianism), and the spatial aggregation considered by the metrics (either network-wide or localised). Next, we empirically compare the metrics by calculating them for eight transport networks. We define the empirical similarity between two metrics as the degree to which they yield similar rankings of infrastructure elements. Pairs of metrics that have high empirical similarity highlight the same set of transport infrastructure elements as critical. We find that empirical similarity is partly dependent on the network’s topology. We also observe that metrics that are conceptually similar do not necessarily have high empirical similarity. Based on the insights from the conceptual and empirical comparison, we propose a five-step guideline for transport authorities and analysts to identify the set of criticality metrics to use which best aligns with the nature of their policy questions.     

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.     

Passenger Perspectives in Railway Timetabling: A Literature Review

When looking at railway planning, a discrepancy exists between planners who focus on the train operations and publish fixed railway schedules, and passengers who look not only at the schedules but also at the entirety of their trip, from access to waiting to on-board travel and egress. Looking into this discrepancy is essential, as assessing railway performances by merely measuring train punctuality would provide an unfair picture of the level of service experienced by passengers. Firstly, passengers’ delays are often significantly larger than the train delays responsible for the passengers to be late. Secondly, trains’ punctuality is often strictly related to too tight schedules that in turn might translate into knock-on delays for longer dwelling times at stations, trip delays for increased risk of missing transfer connections, and uncertain assessment of the level of service experienced, especially with fluctuating passenger demand. A key aspect is the robustness of railway timetables. Empirical evidence indicates that passengers give more importance to travel time certainty than travel time reductions, as passengers associate an inherent disutility with travel time uncertainty. This disutility may be broadly interpreted as an anxiety cost for the need for having contingency plans in case of disruptions, and may be looked at as the motivator for the need for delay-robust railway timetables. Interestingly, passenger-oriented optimisation studies considering robustness in railway planning typically limit their emphasis on passengers to the consideration of transfer maintenance. Clearly, passengers’ travel behaviour is far more complex and multi-faceted and thus several other aspects should be considered, as becoming more and more evident from passenger surveys. The current literature review starts by looking at the parameters that railway optimisation/planning studies are focused on and the key performance indicators that impact railway planning. The attention then turns to the parameters influencing passengers’ perceptions and travel experiences. Finally, the review proposes guidelines on how to reduce the gap between the operators’ railway planning and performance measurement on the one hand and the passengers’ perception of the railway performance on the other hand. Thereby, the conclusions create a foundation for a more passenger-oriented railway timetabling ensuring that passengers are provided with the best service possible with the resources available.     

Recent applications of big data analytics in railway transportation systems: A survey

Big data analytics (BDA) has increasingly attracted a strong attention of analysts, researchers and practitioners in railway transportation and engineering. This urges the necessity for a review of recent research development in this field. This survey aims to provide a comprehensive review of the recent applications of big data in the context of railway engineering and transportation by a novel taxonomy framework, proposed by Mayring (2003). The survey covers three areas of railway transportation where BDA has been applied, namely operations, maintenance and safety. Also, the level of big data analytics, types of big data models and a variety of big data techniques have been reviewed and summarized. The results of this study identify the existing research gaps and thereby directions of future research in BDA in railway transportation systems.     

Valuation of improved railway rolling stock: A review of the literature and new evidence

The paper provides a comprehensive review of a large amount of previously unpublished British evidence about the valuation of new railway rolling stock and its effects on demand. An important conclusion is that incentives to bias Stated Preference responses and unfamiliarity with the rolling stock being considered have led to inflated values. This has broader implications for the use of Stated Preference techniques. Also provided is fresh empirical evidence for a range of different types of rolling stock and specific rolling stock attributes. A novel aspect of the research was the use of disaggregate Revealed Preference choice data. The estimated rolling stock values are much lower than those obtained from previous studies.     

The impact of high-speed technology on railway demand

This paper estimates a passenger railway demand function to analyse effects arising from the introduction and use of high-speed technologies. The paper reports estimates of demand elasticities with respect to price, income, quality of service and a range of exogenous characteristics. The results show that travel time savings from conventional high-speed technology have a larger impact on passenger demand than tilting train technology. The introduction of conventional high-speed technology is associated with an 8% increase in passenger railway demand. Increasing the use of either type of high-speed technology appears to induce small positive effects on demand beyond those obtained from usual traffic density increases on non-high-speed existing technology.