Large-scale Transportation Infrastructure Research Articles

Toward a Better Understanding of the Construction Impacts of a Light Rail System in Montréal, Canada

Large-scale transport infrastructure projects generate long-lasting changes in the built environment and alter the lives of nearby residents. It is crucial to understand public perceptions of public-transit projects and associated construction impacts, as they influence the social acceptance and eventual success of such projects. To characterize the construction-phase experiences of a new light rail in Montréal, Canada—the Réseau express métropolitain (REM)—we analyzed data from 1,236 respondents from the Greater Montréal region who self-reported ongoing construction activities near their homes. This study employs an exploratory factor and k-means cluster analysis to group residents by their different experiences and perceptions of the REM and its associated construction impacts. The analysis returned five clusters with distinct construction experiences: construction-concerned travelers, REM-critical respondents, neutral travelers, REM enthusiasts, and rerouted travelers. Subsequently, the acceptability of the impacts during the construction phase on each cluster is assessed by comparing perceptions of the impact of neighborhood change on their quality of life and their intention to use the REM. Finally, we derive targeted policy recommendations to help promote increased social acceptability of light-rail transit (LRT) projects, including mitigating disruptions in construction zones, public information campaigns, and inclusive decision-making processes. Findings from this study can benefit policymakers and transport planners as they aim to reduce the disruptions associated with the construction of LRT systems and promote increased social acceptability.

Performance controls and accountability in African transport infrastructure megaprojects: A systematic literature review

Poor performance is common in the delivery of large-scale transport infrastructure. Despite previous studies examining the management of transport megaprojects, there is a lack of systematic reviews on performance Controls and Accountability in Megaprojects (CAMP). We analyze research on CAMP in Africa. Out of the 947 records retrieved, 35 articles published between 1980 and 2022 meet our inclusion criteria. We identify four main research themes: “project governance,” “performance management,” “project conceptual management,” and “complexity management.” Our findings indicate significant weaknesses in project governance and a lack of proper project conception. Practical implications involve restructuring project governance policies and implementing a multi-level project governance model. The research supports recognizing corruption as a characteristic of megaprojects, implementing project governance as a standard management practice, and improving governance in public-private partnerships. Additionally, future research should prioritize integrating and developing policies, strengthening institutions, implementing participatory governance mechanisms, and building capacity for project management.

Significant risks that trigger cost overruns and delays in urban rail projects: a typical case study of Vietnam

PurposeUrban rail projects are typically large-scale transport infrastructure projects (megaprojects) which have many potential risks that can influence the strategic goals of owners. However, there is a paucity of studies which explore the impact of risks on both “urban rail” project time and cost together considering quantitative assessments. Therefore, this paper focuses on investigating critical risks and quantifying such risk impacts on urban railway project schedule and cost in practice.Design/methodology/approachA combination of qualitative and quantitative research methods comprising semi-interviews with five experts and a questionnaire survey of 132 professional respondents is used. The data were modeled using Monte Carlo Simulation to predict the probability of project schedule and cost.FindingsThe results show that 30 risk variables are categorized into seven main groups which have significant impacts on both project time and cost. Outstanding five risk variables were highlighted as follows: (1) project site clearance and land compensation; (2) design changes; (3) physical project resources; (4) contractors’ competencies and (5) project finance. Such findings were supported by Monte Carlo simulation which predicted in the worst case that the project may suffer 11.03 months’ delays and have cost overrun with a contingency of US$287.68 million.Originality/valueThis study expands our knowledge about time and cost contingency of urban metro railway implementation across developing economies and particularly within the context of Vietnam. Policymakers will not only gain an understanding about risk structure but will also recognize the significant impacts of critical risk through risk impact modeling and simulation. Such an approach provides insights into risk treatment priorities for planners so that they can proactively establish suitable strategies for risk mitigation in practice.

Localised Perceptions of Large-Scale Active Transport Infrastructure: Resident Attitudes Towards Pedestrian and Cyclist-Only Bridges on the Gold Coast, Australia

ABSTRACT Large-scale active transport infrastructure is essential to connect walking and cycling networks severed by physical impediments (e.g. waterways and motorways). Yet, implementations in car-centric urban areas have experienced localised ‘bikelash’ and Not-in-my-backyard (NIMBY) resistance. Our mixed-method, cross-sectional study from the Gold Coast, Australia, identified positive sentiments towards green bridge implementations within the broader urban area. However, support for future bridge implementations decreased with proximity to respondents’ homes. State and local governments planning new facilities must account for this geographical discounting effect, where residents want to reside near active transport infrastructure to derive benefit from them, but not too close.

Large-Scale Transport Infrastructure Project Performance: Generating a Narrative of Context and Meaning

Large-Scale Transport Infrastructure Project Performance: Generating a Narrative of Context and Meaning

On the numerical treatment of interlaced target values: modeling, optimization and simulation of regulating valves in gas networks

Due to the current and foreseeable shifts towards carbon dioxide neutral energy production, which will likely result in balancing fluctuating renewable energy generation by transforming power-to-gas-to-power as well as building a large-scale hydrogen transport infrastructure, the trading and transport operations of gas will become more dynamic, volatile, and hence also less predictable. Therefore, computer-aided support in terms of rapid simulation and control optimization will further broaden its importance for gas network dispatching. In this paper, we aim to contribute and openly publish two new mathematical models for regulators, also referred to as control valves, which together with compressors make up the most complex and involved types of active elements in gas network infrastructures. They provide direct control over gas networks but are in turn controlled via target values, also known as set-point values, themselves. Our models incorporate up to six dynamical target values to define desired transient states for the elements’ local vicinity within the network. That is, each pair of every two target values defines a bounding box for the inlet pressure, outlet pressure as well as the passing mass flow of gas. In the proposed models, those target values are prioritized differently and are constantly in competition with each other, which can only be resolved dynamically at run-time of either a simulation or optimization process. Besides careful derivation, we compare simulation and optimization results with predictions of the widely adopted commercial simulation tool SIMONE, serving as our substitute for actual real-world transport operations.

An Evolutionary Neural Network Approach for Slopes Stability Assessment

A current big challenge for developed or developing countries is how to keep large-scale transportation infrastructure networks operational under all conditions. Network extensions and budgetary constraints for maintenance purposes are among the main factors that make transportation network management a non-trivial task. On the other hand, the high number of parameters affecting the stability condition of engineered slopes makes their assessment even more complex and difficult to accomplish. Aiming to help achieve the more efficient management of such an important element of modern society, a first attempt at the development of a classification system for rock and soil cuttings, as well as embankments based on visual features, was made in this paper using soft computing algorithms. The achieved results, although interesting, nevertheless have some important limitations to their successful use as auxiliary tools for transportation network management tasks. Accordingly, we carried out new experiments through the combination of modern optimization and soft computing algorithms. Thus, one of the main challenges to overcome is related to the selection of the best set of input features for a feedforward neural network for earthwork hazard category (EHC) identification. We applied a genetic algorithm (GA) for this purpose. Another challenging task is related to the asymmetric distribution of the data (since typically good conditions are much more common than bad ones). To address this question, three training sampling approaches were explored: no resampling, the synthetic minority oversampling technique (SMOTE), and oversampling. Some relevant observations were taken from the optimization process, namely, the identification of which variables are more frequently selected for EHC identification. After finding the most efficient models, a detailed sensitivity analysis was applied over the selected models, allowing us to measure the relative importance of each attribute in EHC identification.

МЕТОДЫ СТРАТЕГИЧЕСКОГО УПРАВЛЕНИЯ ТРАНСПОРТНОЙ ИНФРАСТРУКТУРОЙ В УСЛОВИЯХ ПЕРЕМЕН

The goals and methods of managing the development of Russia's transport infrastructure in the conditions of change are considered. To support decision-making related to such development, it is proposed to use the Complex of Strategic Management Models for Large-Scale Transport Infrastructure, tested in the process of developing the transport infrastructure of Siberia, the Far East and the Russian Arctic.

Reexamination of the association between development patterns and truck crashes: A case study in Dallas-Fort Worth, TX

Over the last decade, urban logistics operations have changed significantly due to globalized production and distribution systems and expanding online shopping sales. On the one hand, goods are distributed on a greater scale through large-scale transportation infrastructure. On the other, exploding online shopping shipment has added another layer of complexity to urban logistics operations. Nowadays, instant home delivery has become prevalent. Provided that the geography, extent, and frequency of freight trip generation have completely changed, it can be assumed that the relationship between the development pattern characteristics and road safety outcomes has also changed, accordingly. Then, it is imperative that the spatial distribution of truck crashes, in conjunction with development pattern characteristics, is reexamined. As a Dallas-Fort Worth, TX metro area case study, this research examines whether the spatial distribution of truck crashes on city streets is different from that of other vehicle crashes and tests whether truck crashes have a unique association with development patterns. Results show that truck and passenger car crashes are distinguished in terms of how they are associated with urban density and employment sector compositions. The explanatory variables with significant and expected signs of relationship are VMT per network mile (exposure), intersection density, household income, % non-white, and % no high school diploma. Results indicate that the spatial heterogeneity in goods shipment intensity has strong implications for the variation in truck crash patterns. Results also call for a comprehensive reexamination of trucking activity in dense urban areas.

Simulations of the Effects of Different Waiting Point Scenarios on DRT Operation Performance in Gwacheon, South Korea

The usefulness of DRT (Demand Responsive Transit) as an alternative public transportation system for small urban areas without a large-scale transportation infrastructure is widely recognized. The success of DRT operations lies in ensuring sufficient demand against the costs. One of the causes of inefficient DRT operations is the failure to provide a suitable waiting point for vehicles that have just completed a service. Existing simulation studies on DRT performance are based on less realistic assumptions (such as no consideration of vehicle waiting points, a waiting point at the garage only, or limiting to only the optimal waiting points), which makes it difficult to evaluate the differences in DRT performance between various placement approaches for vehicle waiting points. The purpose of this study is to propose alternative methods for designating waiting points of virtual stops for idle vehicles, and to analyze the changes in key performance indices according to each method. To this end, this study established virtual stops on an actual road network in Gwacheon, Gyeonggi-do, which currently operates DRT, and measured and compared the changes in indices such as user waiting time and vehicle driving miles between the proposed methods. The research results have important implications for revitalizing public transportation in small cities and can inform the strategies and improvements of DRT operations.

Ecological security pattern construction and zoning along the China-Laos Railway based on the potential-connectedness-resilience framework

Rapid developments associated with large-scale transport infrastructure have exacerbated ecological risks, posing major threats to biodiversity and ecosystem services. Construction of ecological security patterns (ESPs) can effectively mitigate this threat, but existing construction of ESPs lacks consideration of the risk to landscape connectivity and resilience, as well as zoning optimization at a finer resolution. This study focused on the region along the China-Laos Railway to evaluate the landscape ecological risk (LER) based on the potential-connectedness-resilience framework and extracted ESP elements according to the LER evaluation. Clustering of LER and ecological quality index was introduced to facilitate more targeted management of ESP. We found that the regional LER was most likely elevated because the proportion of LER at the medium level and above was close to 50 %. Moreover, the segmentation and penetration of high-risk areas into low-risk areas was prominent. The distribution of low LER areas was notably shaped by regional resilience, while road expansion would create many medium and higher risk areas, and the development of industrial parks would generate high risks in urban peripheries. 2,615.88 km of ecological corridors enabled the 17,362.08 km2 ecological sources to be effectively connected. 33 ecological nodes and 115 stepping stones were extracted as valid complements to key areas of weak connectivity. Priority treatment of specific sources (4.88 %) and ecological corridors (29.93 %) enhances the resilience of ESP. Our study provides a method for integrating the assessment of ecological risks arising from future regional development with the construction and optimization of ESPs, which can be promoted in ecological conservation planning in developing countries driven by infrastructure and industrial parks.

Impact of Highway Construction on Internal Migration: A Korea Perspective

Transportation facilities in the classical migration model expand the scale of population movement by reducing the physical distance and costs of travel between regions. This study empirically analyzes the effect of population inflow into a region near a highway construction using a migration model. The purpose was to examine whether large-scale transportation infrastructure such as highways contributes to the growth and balanced development of the connected regions. Four metropolitan transport-type and commuter transport-type highway routes constructed in South Korea after 2000 were used as study subjects. The results show that population inflow occurred in the region where commuter transport-type highways were constructed. However, no effect was observed in regions where metropolitan transport-type highways were constructed. The reason for these unique results is that factors affecting migration include not only transit facilities, but also parameters such as economic factors, housing, and amenities. Moreover, the findings show that the impact of population inflow is affected by the geographical characteristics of the highway construction areas and city size.

Multi-objective decision support system for large-scale network pavement maintenance and rehabilitation management to enhance sustainability

Process of sustainable pavement maintenance and rehabilitation (M&R) management can be conducted using various technological and organizational systems. Such systems must meet the implementation conditions of a given project involving pavement M&R, and trade-offs between economic, environmental, and social impacts from various aspects involved. Hence, this study examines a systematic framework for large-scale pavement network decision-making considering sustainability dimensions, constructs a multi-stage decision model considering different modes and options using attribute mapping techniques, and develops a decision support system that (1) determines comprehensive sustainability drivers and quantification methods in the field of pavement management to evaluate the sustainability characteristics of predetermined M&R strategies; and (2) allows the execution of decision space dimensionality reduction process for any given network scales and M&R techniques dimensions considering spatial-temporal distribution, then generate a specific set of sustainable budget allocation and M&R strategy combination scenarios using a redesigned multi-objective optimization model, which can coordinate segment-level and network-level management. A case study was conducted to demonstrate the application of the proposed system. Results show that the approach can significantly reduce the computational cost compared to the scenario without dimensionality reduction, and also facilitates the improvement of agency costs, environmental impacts, as well as user costs from the life cycle perspective. Furthermore, the balance of M&R budget allocation depends on the mapped attributes selected in the dimensionality reduction process, the sustainability and reliability of the decision results can be improved by selecting as many attributes as possible while satisfying the pavement management system. The study provides an exciting opportunity to support decision-making for large-scale transportation infrastructure management.

The frictions of highway protests in U.S. cities and the legislative backlash

ABSTRACT Spaces of protest have long been of interest to scholars because of their transgressive and highly visible uses of urban space. However, the increased visibility such spaces bring also puts protestors at greater risk of a backlash from others who expect to be able to keep moving at their own pace. Starting in 2015, a series of protests in the U.S. began using large-scale transportation infrastructure in urban areas, especially Black Lives Matter activists. Shortly thereafter, in 2017, a series of bills were introduced in state legislatures across the U.S. to limit or criminalize this activity. This paper analyzes the arguments made by legislative sponsors and supporters of these bills, using the theoretical lenses of friction and the shoal to argue that in the highly mobile society of the U.S., fear of delay or disruption becomes even more powerful when combined with racialized fears of the city.

Marked crosswalks in US transit-oriented station areas, 2007–2020: A computer vision approach using street view imagery

Improving the built environment to support walking is a popular strategy to increase urban sustainability and walkability. In the past decade alone, many US cities have implemented crosswalk visibility enhancement programs as part of road safety improvements and active transportation plans. However, there are no systematic ways of measuring and monitoring the presence of key built environment attributes that influence the safety and walkability of an area, such as marked crosswalks. Furthermore, little is known about how these attributes change over time at a national scale. In this paper, we introduce an innovative approach using a deep learning-based computer vision model on Street View images to identify changes in intersection-level marked crosswalks around more than 4,000 US transit stations over a 14-year period. We found an increase in the overall number of marked crosswalks at intersections. Furthermore, high-visibility crosswalks became more common, as they replaced existing parallel-line crosswalks. We further examine crosswalks around transit stations in New York City and San Francisco to illustrate geographic variations and compare associations with other characteristics of the built environment as reported in the Smart Location Database. Areas with increases in high-visibility crosswalks focused on high density residential areas and areas with a higher percent of zero-vehicle households. However, geographic variations exist. For example, in San Francisco, transit station areas outside downtown or major corridors (South and Southwest of the city) had the lower prevalence of marked crosswalks. This analysis confirms important gaps in crosswalk visibility that call for safety enhancements and opens the door for additional research involving these data. We conclude by discussing the limitations and future research opportunities using computer vision to automatically detect large-scale transportation infrastructure changes at a relatively low cost.

Patterns of gene flow across multiple anthropogenic infrastructures: Insights from a multi-species approach

Large-scale Transportation Infrastructures (LTIs) are among the main determinants of landscape fragmentation, with strong impacts on animal dispersal movements and metapopulation functioning. Although the detection of LTIs impacts is now facilitated by landscape genetic tools, studies are often conducted on a single species, although different species might react differently to the same obstacle. We surveyed four species (a snake, an amphibian, a butterfly and a ground-beetle) in a landscape fragmented by six LTIs: a motorway, a railway, a country road, a gas pipeline, a power line and a secondary road network. We hypothesized that LTIs carrying vehicles would mostly impact ground-dwelling species, possibly in a cumulative way. We showed that half of the overall explained genetic variability across all species was due to LTIs. While the butterfly was seemingly not impacted by any LTI, the genetic structure of the three other species was mostly influenced by roads and motorway. The power line did not affect any species and the gas pipeline only impacted gene flow in the ground-beetle through forest fragmentation, but roads systematically affected at least two species. Interestingly, we also showed that some LTIs could somehow promote gene flow, embankments probably providing favourable habitats for vertebrate species. Considering the high variability in species response to LTIs, we argue that drawing general conclusions on landscape connectivity from the study of a single species may lead to counterproductive mitigation measures and that multi-species approaches should be more systematically considered in conservation planning.

Impacts of Determining Economic Life of Large-Scale Infrastructure Projects on Their Economic Effectiveness

The paper deals with the refinement of the Cost-Benefit Analysis methodological procedure for the assessment of the economic effectiveness of large-scale transport infrastructure projects. The basic input is economic Cash Flow which consists of investment costs, operating income, operating expenses, societal benefits, and harms as well as the investment residual value. According to the methodological guidelines, the currently evaluated project period is considered to be 30 years including the investment phase starting in the first year of the construction, the relevant part of the operational phase, and the residual value of the project in the last year of the assessed period. The evaluation of the economic effectiveness of projects is largely influenced by the determination of the construction economic life. A procedure for calculating the residual value of the project while respecting the gradual implementation of partial constructions was established as part of the research. A case study based on the research sample of several investment construction projects of the highway sections in the Czech Republic demonstrates how this methodological procedure affects the economic effectiveness of the project.

Large-scale CO2 transport and storage infrastructure development and cost estimation in the Netherlands offshore

A plan was developed for large-scale transport and storage of CO2, inspired by the measures in The Netherlands Climate Agreement to reduce greenhouse gas emissions to the atmosphere. The main focus was on reduction of CO2 emissions captured from large industrial sources in the Rotterdam harbour area (Rijnmond region). CO2 storage potential is available within depleted gas fields in the Dutch sector of the North Sea. Specific attention was given to the potential for re-use of existing oil and gas infrastructure and the costs and development time of the re-used or new build infrastructure for CO2 transport and storage.The study revealed that depleted gas fields in The Netherlands offshore provide ample storage capacity to accommodate a supply of 10 million tonnes (Mt) CO2 per year by 2030 and for a subsequent period of 40 years. An average total unit technical costs for compression, transport and storage was calculated at €8.6 per tonne CO2. Concurrent operation of four to five reservoirs will be needed if the required 5 Mt annual injection rate in the base case scenario is to be met and eight to nine reservoirs need to be in operation simultaneously with a target rate of 10 Mt per year. In the accelerated case of injection of 10 Mt per year individual reservoirs will be brought on-stream much earlier than in the base case scenario. This can be up to several decades earlier for the reservoirs deployed in the final phase of CO2 storage activities.

Evaluation of the Effects of the Belt and Road Initiative on the Unified Economic and Environmental Efficiency of Transportation Infrastructure in China Based on Range-Adjusted Measure Model and Difference in Difference Model

The Belt and Road Initiative has brought new opportunities for countries along the routes to develop their transportation infrastructure. Through large-scale transportation infrastructure construction, these countries enhanced the Belt and Road cooperation with each other, which further facilitates the rapid development of their own economy, but whether this can promote the sustainable development of their own environment, relevant research is still lacking. In this paper, China is taken as the study subject to evaluate the comprehensive effects that the Belt and Road Initiative exerts on the economy and environment through improving transportation infrastructure. In the study, RAM indicators were first established to measure the unified economic and environmental efficiency of transportation infrastructure, a DID model was then built to study the effects of the Initiative on the unified efficiency, and mediation models were finally created to discuss the ways in which the Belt and Road Initiative can improve the unified economic and environmental efficiency of transportation infrastructure through transformation and upgrade of industrial structure. The study result shows that the Belt and Road Initiative can significantly promote the improvement of the unified economic and environmental efficiency of the national transportation infrastructure, but the result is regionally heterogeneous. The Initiative has positive effects in improving the unified efficiency in eastern region but has no effect in the central and western regions. Although the Initiative can significantly enhance the efficiency through transforming and upgrading the industrial structure, the industrial structure rationalization plays a primary positive role. This paper provides the empirical evidences to evaluate the implementation effects of the Initiative in the transportation infrastructure sector and verifies that countries along the routes can achieve sustainable development through large-scale transportation infrastructure construction under the Belt and Road Initiative.

An SLCA method based framework of large-scale transportation infrastructure in China

Large-scale infrastructure has complex social impacts because it involves large investments, long life cycle, and extensive stakeholders. However, studies on social life cycle assessment (S-LCA) of large-scale infrastructure are still lacking. Based on the extant S-LCA literature and characteristics of large-scale infrastructure, this study proposes an S-LCA framework for large-scale transportation infrastructure and evaluates the following five social impact categories: economy, welfare, participation, safety, and justice. The framework determines categories of stakeholders, such as workers, users, the public, value chain participants, and local communities. Additionally, the study puts forward the subcategories, inventory indicators, and characterization models of each stakeholder; it constructs a weighting system for stakeholders and subcategories and then aggregates and compares different impact categories. The proposed framework was applied to evaluate the life cycle social impacts of the Fengtai High-speed Railway Station reconstruction project in Beijing. Results confirmed the feasibility and practicability of the framework. The proposed S-LCA framework is theoretically valuable for quantifying the complex and long-term social impacts of large-scale infrastructure and has practical value for improving the social performance and decision-making effectiveness of infrastructure project investment.