Dynamic and disequilibrium analysis of interdependent infrastructure systems

There is a growing awareness in recent years that the interdependencies among the civil infrastructure systems have significant economic, security and engineering implications that may influence their resiliency, efficiency and effectiveness. To capture the various types of infrastructure interdependencies and incorporate them into decision-making processes in various application domains, Zhang and Peeta (2011) propose a generalized modeling framework that combines a multilayer infrastructure network (MIN) concept and a market-based economic approach using computable general equilibrium (CGE) theory and its spatial extension (SCGE) to formulate a static equilibrium infrastructure interdependencies problem. This paper extends the framework to address the dynamic and disequilibrium aspects of the infrastructure interdependencies problems. It briefly reviews the static model, and proposes an alternative formulation for it using the variational inequality (VI) technique. Based on this equivalent VI formulation, a within-period equilibrium-tending dynamic model is proposed to illustrate how these systems evolve towards an equilibrium state within a short duration after a perturbation. To address a longer time scale, a multi-period dynamic model is proposed. This model explicitly considers the evolution of infrastructure interdependencies over time and the temporal interactions among the various systems through dynamic parameters that link the different time periods. Using this model, numerical experiments are conducted for a special case with a single region to analyze the sensitivity of the model to the various parameters, and demonstrate the ability of the modeling framework to formulate and solve practical problems such as cascading failures, disaster recovery, and budget allocation in a dynamic setting.     

Adaptation planning for climate-resilient urban infrastructures

This paper analyzes the interdependency across two critical infrastructures of transportation and motor fueling supply chains, and investigates how vulnerability to climatic extremes in a fueling infrastructure hampers the resilience of a transportation system. The proposed model features both a bi-stage mathematical program and an extension to an ‘α-reliable mean-excess’ regret model. The former aspect allows decision makers to optimize the pre-disaster asset prepositioning against the maximum post-disaster system resilience. The latter aspect of the proposed model devalues the impact of ‘low-probability, high-cost’ sub-scenarios upon model results. The model reveals the reliance of post-disaster urban mobility on the interdependent critical infrastructure of motor fueling supply chains. The results also suggest how investment in the fueling infrastructure’s vulnerable elements protects urban mobility while the transportation network is stressed or under attack.     

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.     

Designing computable general equilibrium models for transportation applications

This paper presents a review of Computable General Equilibrium (CGE) model applications for spatial economic and transport interaction modelling. This paper has three objectives (1) To deliver an up to date and comprehensive literature review on applications of CGE models in transportation, (2) To analyze the different methodological approaches and their theoretical and practical advantages and disadvantages, and (3) To ultimately provide guidance on designing CGE models for various transportation analyses. The content of the paper is as follows: first, a brief introduction to CGE models is provided. The history of CGE models is traced, ranging from their origins and seminal applications in economics, to their eventual adoption in transportation research. This is followed by a comprehensive review of the application of CGE models to transport projects and policies. Various applications in transportation are reviewed in terms of their intended application, as well as their treatment of space and time. Finally, these applications are contrasted with respect to their methodological approaches, with a close examination of various influential model choices. Here, the essential design choices made within these model applications are explained and debated, to clearly elaborate on the workings of the models and the design choices facing CGE model developers.     

An optimization model of energy and transportation systems: Assessing the high-speed rail impacts in the United States

This paper presents a long-term investment planning model that co-optimizes infrastructure investments and operations across transportation and electric infrastructure systems for meeting the energy and transportation needs in the United States. The developed passenger transportation model is integrated within the modeling framework of a National Long-term Energy and Transportation Planning (NETPLAN) software, and the model is applied to investigate the impact of high-speed rail (HSR) investments on interstate passenger transportation portfolio, fuel and electricity consumption, and 40-year cost and carbon dioxide (CO₂) emissions. The results show that there are feasible scenarios under which significant HSR penetration can be achieved, leading to reasonable decrease in national long-term CO₂ emissions and costs. At higher HSR penetration of approximately 30% relative to no HSR in the portfolio promises a 40-year cost savings of up to $0.63 T, gasoline and jet fuel consumption reduction of up to 34% for interstate passenger trips, CO₂ emissions reduction by about 0.8 billion short tons, and increased resilience against petroleum price shocks. Additionally, sensitivity studies with respect to light-duty vehicle mode share reveal that in order to realize such long-term cost and emission benefits, a change in the passenger mode choice is essential to ensure higher ridership for HSR.     

The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis

This study investigates the impact of high-speed rail investment on the economy and environment in China using a computable general equilibrium (CGE) model. The analysis is implemented in a dynamic recursive framework capturing long-run capital accumulation and labor market equilibrium. A national level impact was simulated through direct impact drivers including land use conversion, output expansion, cost reduction, productivity increase, transport demand substitution and induced demand. The results suggest that rail investment in China over the past decade has been a positive stimulus to the economy, while the effect on CO₂ emissions generation has been large. Overall, the economic impacts of rail investment are achieved primarily through induced demand and output expansion, whereas the contribution from a reduction of rail transportation costs and rail productivity increases were modest. In addition, negligible negative impacts were found from land use for rail development and the substitution effect among other modes. Emissions reduction from substitution of rail for other modes was small and offset by output expansion due to lowered rail transport costs and induced demand.     

The underground economy: Tracking the higher-order economic impacts of the São Paulo Subway System

Over one million workers commute daily to São Paulo City center, using different modes of transportation. The São Paulo subway network reaches 74.2 km of length and is involved in around 20% of the commuting trips by public transportation, enhancing mobility and productivity of workers. This paper uses an integrated framework to assess the higher-order economic impacts of the existing underground metro infrastructure. We consider links between mobility, accessibility and labor productivity in the context of a detailed metropolitan system embedded in the national economy. Simulation results from a spatial computable general equilibrium model integrated to a transportation model suggest positive economic impacts that go beyond the city limits. While 32% of the impacts accrue to the city of São Paulo, the remaining 68% benefit other municipalities in the metropolitan area (11%), in the State of São Paulo (12.0%) and in the rest of the country (45%).     

Planning for economic and environmental resilience

Climate protection will require major reductions in GHG emissions from all sectors of the economy, including the transportation sector. Slowing growth in vehicle miles traveled (VMT) will be necessary for reducing transportation GHG emissions, even with major breakthroughs in vehicle technologies and low-carbon fuels (Winkelman et al., 2009). The Center for Clean Air Policy (CCAP) supports market-based policy approaches that minimize costs and maximize benefits. Our research indicates that significant GHG reductions can be achieved through smart growth and travel efficiency measures that increase accessibility, improve travel choices and make optimum use of existing infrastructure. Moreover, we find such measures can deliver compelling economic benefits, including avoided infrastructure costs, leveraged private investment, increased local tax revenues and consumer vehicle ownership and operating cost savings (Winkelman et al., 2009).As a society, what we build – where and how – has a tremendous impact on our carbon footprint, from building design to transportation infrastructure and land-use patterns. The empirical and modeling evidence is clear – people drive less in locations with efficient land use patterns, high quality travel choices and reinforcing policies and incentives (Ewing et al., 2008). It is also clear that there is growing and unmet market demand for walkable communities, reinforced by demographic shifts and higher fuel prices (Leinberger, 2006, Nelson, 2007). Transportation policy in the United States must rise to meet this demand for more travel choices and more livable communities.The academic, ideological and political debates about the level of GHG reductions and penetration rates that can or should be achieved via smart growth and pricing on the one hand, or measures such as ‘eco-driving’ and signal optimization on the other, have served their purpose: we know which policies are ‘directionally correct’ – policies that reduce GHG emissions even though we may not know the scope of those reductions. Now is the time to implement directionally correct policies, assess what works best where, and refine policy based on the results. It is a framework that CCAP calls “Do. Measure. Learn.”The Federal government is poised to spend $500 billion on transportation (Committee on Transportation and Infrastructure, 2009). CCAP encourages Congress to “Ask the Climate Question” – will our transportation investments help reduce GHG emissions or exacerbate the problem? Will they help increase our resilience to climate change impacts or increase our vulnerability? And, while we’re at it, will our investment foster energy security, livable communities and a vibrant economy? Federal transportation and climate policies should empower communities to implement locally-determined travel efficiency solutions by providing appropriate funding, tools and technical support.     

Appraising large-scale investments in a metropolitan transportation system

A package of large-scale investments in the transportation infrastructure in the Stockholm metropolitan region is currently being proposed. It contains new investments in the railway and subway systems as well as new links in the road system. This paper deals with the issue of appraising this kind of investment program. One major problem is the lack of a unique standard method, and it is argued that several tools should be used in a practical evaluation of large-scale investments in the transportation system.Four different approaches are presented and related to each other. First, one study uses a network-based mode-split/assignment model with a fixed trip matrix. The second study is complementary, as its aim is to also trace the impacts on the spatial distribution of population and jobs by applying an integrated transportation and land use model. Third, the long-run effects of the investments on regional economic growth are discussed within the framework of regional production functions. Fourth, an alternative approach is used, in which benefits from the investments are assessed through their estimated influence on aggregate land values.Abbreviations RA Reference Alternative - IP Investment Proposal - IMREL Integrated Model of Residential and Employment Location - RPFM Regional Production Function Model An earlier version of this paper was presented at the 31th European Congress of the Regional Science Association, Lisbon, August 1991.     

Infrastructure deployment under uncertainties and competition: The biofuel industry case

Technological paradigm shifts often come with a newly emerging industry that seeks a viable infrastructure deployment plan to compete against established competitors. Such phenomenon has been repeatedly seen in the field of transportation systems, such as those related to the booming bioenergy production, among others. We develop a game-theoretic modeling framework using a continuum approximation scheme to address the impacts of competition on the optimal infrastructure deployment. Furthermore, we extend the model to incorporate uncertainties in supply/demand and the risk of facility disruptions. Analytical properties of the optimal infrastructure system are obtained, based on which fast numerical solution algorithms are developed. Several hypothetical problem instances are used to illustrate the effectiveness of the proposed algorithms and to quantify the impacts of various system parameters. A large-scale biofuel industry case study for the U.S. Midwest is conducted to obtain additional managerial insights.     

Determining the role of bicycle sharing system infrastructure installation decision on usage: Case study of montreal BIXI system

The traditional quantitative approach to studying Bicycle Sharing System (BSS) usage involves examining the influence of BSS infrastructure (such as number of BSS stations and capacity), transportation network infrastructure, land use and urban form, meteorological data, and temporal characteristics. These studies, as expected, conclude that BSS infrastructure (number of stations and capacity) have substantial influence on BSS usage. The earlier studies consider usage as a dependent variable and employ BSS infrastructure as an independent variable. Thus, in the models developed, the unobserved factors influencing the measured dependent variable (BSS usage) also strongly influence one of the independent variables (BSS infrastructure). This is a classic violation of the most basic assumption in econometric modeling i.e. the error component in the model is not correlated with any of the exogenous variables. The model estimates obtained with this erroneous assumption are likely to over-estimate the impact of BSS infrastructure. Our research effort proposes an econometric framework that remedies this drawback. We propose a measurement equation to account for the installation process and relate it to the usage equations thus correcting for the bias introduced in earlier research efforts by formulating a multi-level joint econometric framework. The econometric models developed have been estimated using data compiled from April 2012 to August 2012 for the BIXI system in Montreal. The model estimates support our hypothesis and clearly show over-estimation of BSS infrastructure impacts in models that neglect the installation process. An elasticity analysis to highlight the advantages of the proposed econometric model is also conducted.     

Contractual PPPs for Transport Infrastructure in Spain: Lessons from the Economic Recession

In this paper, we analyse the successes and failures of contractual public-private partnerships (PPPs) for delivering and operating transport infrastructure in Spain from the award of the first toll highway concession programme to the present. To that end, we show the risk allocation principles used in Spain and explore the evolution of the contracting approaches over the years. We found that the performance was reasonably good until the arrival of the economic crisis in 2008. Taking advantage of that, we make a review of contractual PPPs for different transport modes and assess the impact that the economic crisis has had on their business performance and the capacity of the central and regional governments to fulfil their commitments with the private sector. This analysis enabled us to identify measures that, if had been applied, would have improved the resilience of these contract during the economic crisis.     

Resilience in transportation systems: a systematic review and future directions

ABSTRACT

The Belt and Road (B&R) initiative was introduced by the Chinese government to promote the worldwide economic development and multilateral cooperation between China and the associated countries. As a crucial part of global supply chains, transportation plays a key role to ensure the implementation of the B&R. Safety is one of the issues with great importance in transportation research. However, its foci have been expanded from traditional risk through security to resilience and sustainability. Resilience has attracted considerable interests from both researchers and practitioners across different research domains in recent years. Various studies have been conducted on transportation resilience from different perspectives. Consequently, different definitions have been developed to define and describe resilience. This paper presents a systematic review on transportation resilience with emphasis on its definitions, characteristics, and research methods applied in different transportation systems/contexts. It aims to figure out what transportation resilience is and what kind of essential characters it usually has. More importantly, research challenges are analysed and a future research agenda on the resilience of transportation systems is proposed. This paper will provide comprehensive insights into understanding the transportation resilience, as well as establish new horizons for relevant research topics within the context of the B&R.     

Incorporating uncertainty and risk in transportation investment decision-making

This paper presents a framework for addressing uncertainty and risk for large-scale transportation investments involving public–private participation. Demand, fare/toll and demand responsive costs are considered in the uncertainty analysis. Uncertainty analysis provides information on economic feasibility of the project. A set of relaxation policies is proposed to form various Ownership, Tenure and Governance (OTG) strategies reflecting the nature and level of participation by the public and private entity. A Monte Carlo Simulation-based Value at Risk is used to quantify risk. Finally, a methodology is proposed to integrate uncertainty and risk. The framework is tested on the proposed multibillion dollar Detroit River International Crossing connecting the cities of Detroit in the USA with Windsor in Canada. The analysis provides insights to probable outcomes for this transportation infrastructure investment under different OTG scenarios.     

Economic analyses of sea-level rise adaptation strategies in transportation considering spatial autocorrelation

This paper reports the impacts of economic analysis results on sea-level rise adaptation decision making with different economic analysis methods. The methodology was applied to Hillsborough County, Florida. A general conclusion is that partial shoreline protection should be implemented to reduce the potential impacts of sea-level rise on important land use, then transportation infrastructure is preferred to be protected or accommodated, and finally managed relocation should be adopted. More specifically, the results show that the best adaptation strategy is shoreline protection plus transportation infrastructure accommodation; the length of shoreline protection plays an important role in the economic analysis results, and shoreline protection and accommodation adaptation strategies for all areas are not recommended because of either high costs or low benefits; the value of travel time saving and spatial autocorrelation play important roles in the economic analysis results of accommodation strategy, which highlights the importance of including indirect economic factors and spatial autocorrelation impacts when making sea-level rise adaptation decisions.     

Infrastructure maintenance,regeneration and service quality economics: A rail example

This paper proposes a formalized framework for the joint economic optimization of continuous maintenance and periodic regeneration of rail transport infrastructure taking into account output consisting not only in traffic levels but also in track service quality. In contrast with much optimization work pertaining to spatially contiguous maintenance works, its principal economic emphasis and objective focus are centered on the optimal allocation of current maintenance and periodic renewal expenses, on their yearly distribution among large network partitions, and on infrastructure pricing. The model equations are based on very simple assumptions of infrastructure degradation laws and on a manager's objective function optimized through optimal control procedures. Equations are tested on national French rail track segment databases using Box–Cox transformations and match rail regeneration and maintenance practices prevailing in France. More generally, the paper makes a broad contribution to capital theory, on the optimal maintenance and renewal of equipment, and defines a method applicable not only to other transport infrastructure but to a wide range of capital goods, including housing, cars and industrial machines.     

Book Review

This paper examines the relationship between investment in transportation infrastructure capital and the debt-to-gross domestic product (GDP) ratio. We analyse the effect of bringing forward investment originally planned for future years to be executed during times of economic crisis and also consider the possible advantages of carrying out such investments with private sector financing. This paper presents a model which shows how policy aimed to encourage investment in transportation infrastructure projects through private sector participation may help raise long-term GDP and thus lead to a lower debt-to-GDP ratio. The theoretical model is then applied to current empirical data from Israel.     

Resilience in railway transport systems: a literature review and research agenda

ABSTRACT

Critical infrastructure networks, such as transport and power networks, are essential for the functioning of a society and economy. The rising transport demand increases the congestion in railway networks and thus they become more interdependent and more complex to operate. Also, an increasing number of disruptions due to system failures as well as climate changes can be expected in the future. As a consequence, many trains are cancelled and excessively delayed, and thus, many passengers are not reaching their destinations which compromises customers need for mobility. Currently, there is a rising need to quantify impacts of disruptions and the evolution of system performance. This review paper aims to set-up a field-specific definition of resilience in railway transport and gives a comprehensive, up-to-date review of railway resilience papers. The focus is on quantitative approaches. The review analyses peer-reviewed papers in Web of Science and Scopus from January 2008 to August 2019. The results show a steady increase of the number of published papers in recent years. The review classifies resilience metrics and approaches. It has been recognised that system-based metrics tend to better capture effects on transport services and transport demand. Also, mathematical optimization shows a great potential to assess and improve resilience of railway systems. Alternatively, data-driven approaches could be potentially used for detailed ex-post analysis of past disruptions. Finally, several rising future scientific topics are identified, spanning from learning from historical data, to considering interdependent critical systems and community resilience. Practitioners can also benefit from the review to understand a common terminology, recognise possible applications for assessing and designing resilient railway transport systems.     

Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.