Component Of Transportation Infrastructure Research Articles

Aerodynamic study of high-speed railway tunnels with variable cross section utilizing equivalent excavation volume

High-speed railway tunnels, being critical components of transportation infrastructure, are subject to various aerodynamic effects that can impact train operations and passenger comfort. To address these challenges, the concept of tunnels with variable cross sections offers a promising solution, allowing for non-uniform adjustments to tunnel geometry along its length. By employing the notion of equivalent excavation volume, this paper aims to provide a comprehensive aerodynamic analysis of variable cross section tunnels, focusing on different rates of cross section variation (CR). The simulation of high-speed trains (HSTs) passing through tunnels is conducted using the compressible, unsteady Reynolds-Averaged Navier–Stokes model, and the accuracy is confirmed through experimental validation. The transient pressure and peak distribution, slipstream characteristics, micro-pressure waves, and aerodynamic loads acting on trains are fully evaluated. The results indicate that variable cross section tunnels can alleviate the negative pressure on train surface, particularly with streamlined heads and tails exhibiting superior effects, whereas its influence on positive pressure is minimal. The mitigation of both positive and negative pressures on the tunnels is promising, with the maximum peak-to-peak pressures exhibiting a quadratic decrease as the CR increases, resulting in a maximum relief of 17.7%. However, variable cross section tunnels have certain adverse effects on slipstreams and transient loads when HSTs passing through front junctions. Therefore, it is necessary to choose an appropriate CR to control these effects during design process. The findings of this research contribute novel insight for optimizing tunnel design and engineering practices to enhance operational efficiency and passenger comfort.

Seeding roadsides is necessary but not sufficient for restoring native floral communities

Abstract The plant community in roadside right‐of‐ways is an important component of transportation infrastructure. Revegetation after construction is an opportunity to improve the plant community and create pollinator habitat. However, native seed mixes are substantially more expensive than those used in conventional roadside plantings, and transportation agencies often lack resources for management. Here, we compare the actively flowering plant community across a growing season in roadside plots seeded with native seed mixes versus non‐native seed mixes in Minnesota, USA. Plots varied in age from 2 to 20 years old. We demonstrate that native seeded plots had more native flowering forbs than non‐native seeded plots, as native flowers were rare in the non‐native seeded plots. However, despite some native species establishing well, many species in native seed mixes had poor or non‐existent establishment. Furthermore, the native and non‐native seeded plots converged in the makeup of their floral communities after a few years; part of this pattern is due to colonisation of species that were never seeded at either type of plot. Practical implication. If the goal of revegetation is to produce diverse, native dominated floral communities in roadsides, agencies must invest more in long‐term management. Managers could also alter seed mixes to remove species that fail to establish, which would reduce the cost of the seed mix, but not the diversity of the plant community that ultimately establishes. The use of such streamlined seed mixes across more land area would increase the availability of pollinator habitat without substantially altering current budgets or management plans.

Section Line Roads in the U.S. Great Plains

The landscape of the Public Land Survey System (PLSS), or township and range system, is a well-known feature of the U.S. Great Plains. The area displays a checkerboard pattern of farm fields with a grid of roads, plainly visible from the air. Despite being a substantial component of transportation infrastructure, the mileage of section line roads has never been tallied, nor has their distribution been studied relative to population, land use, or environmental factors that might be important in the region. Although they are often said to be ubiquitous, even this has not been examined. The section line road network of five Great Plains states is examined here. A set of procedures was used in geographic information systems to identify section line roads, which were then analyzed with population and land-use variables. The results show that section line roads are not strongly related to either population or land use but do show some correspondence to environmental conditions such as precipitation, a legacy of the settlement of the Great Plains.

A logical retrofit strategy optimization framework for resiliency bridge infrastructure management considering life-cycle cost

Bridges play an important role in providing essential services to communities as one of the most critical components of transportation infrastructure. In this regard, selecting reliable, robust, and efficient indicators is necessary to prepare a disaster management strategy. This study presents a multi-objective optimization framework for decision-makers to find the most optimal retrofit strategies that satisfy a given threshold of functionality/Resilience (R) while minimizing a structure's Life-Cycle Cost (LCC). Accordingly, various retrofit strategies include different materials (steel, Carbon Fiber Reinforced Polymer (CFRP), and Glass Fiber Reinforced Polymer (GFRP)), thicknesses, arrangements, and timing of retrofitting actions. In each scenario, the fragility curves are derived through nonlinear time-history Incremental Dynamic Analysis (IDA) to evaluate the LCC and resilience. In the subsequent step, the LCC analysis is conducted, considering the proposed formulation of multiple occurrences of seismic events, which incorporates the effects of complete/incomplete repair actions of damage conditions induced by previous seismic events. This study employs an elitist Non-dominated Sorting Genetic Algorithm II (NSGA-II) to identify the optimal set of solutions. The various aspects of the optimal retrofit strategies are thoroughly investigated and discussed for a bridge as a case study infrastructure. Results show that the considered objectives lead to reasonable and sense-making retrofit strategies.

Not just more, but more diverse: Green landscapes along urban roads may significantly reduce drivers' psychophysiological fatigue

The impact of roadside greenness on driving fatigue in real urban settings has been insufficiently investigated, presenting a critical knowledge gap for researchers, policymakers, professionals, and the public. In this onsite driving experiment, 34 urban residents completed seven driving tasks on different urban road routes in a randomized order with one-day intervals. A total of 238 tasks were conducted, each lasting an hour, assessing psychophysiological, visual, and muscular fatigue. A cardiovascular activity monitor (BioHarness) continuously measured the driver's heart rate, with lower rates indicating reduced psychophysiological fatigue. Visual and muscular fatigue were self-reported using a Visual Analog Scale questionnaire administered before, at the midpoint, and after completing the driving task. Deep transfer learning semantic segmentation analyzed road landscape characteristics and traffic conditions recorded from the drivers' view. Statistical analysis demonstrated that higher mean and variation in greenness significantly predicted lower psychophysiological fatigue after adjusting for multiple covariates. These results indicate that enhancing both the quantity and diversity of green landscapes along urban roads is vital for reducing driver's psychophysiological fatigue. This study reveals that roadside landscapes in urban settings are not trivial decorations, and they should be considered an essential component of transportation infrastructure.

Condition Rating Prediction for Highway Bridge Based on Elman Neural Networks and Markov Chains

Bridges are a critical component of transportation infrastructure, playing a vital role in connectivity. The safe operation of bridges demands significant resource and capital investment, particularly as the operation phase is the most extended period in a bridge’s life cycle. Therefore, the efficient allocation of resources and funds is crucial for the maintenance and repair of bridges. This study addresses the need to predict changes in bridge condition over time. The commonly used state-based Markov chain method for bridge condition rating prediction is straightforward but limited by its assumptions of homogeneity and memorylessness. To improve upon this, we propose a novel method that integrates an Elman neural network with a Markov chain to predict the bridge condition rating. Initially, the ReliefF algorithm conducts a sensitivity analysis on bridge features to obtain the importance ranking of these features that affect the bridge condition. Next, six significant features are selected for data classification: bridge age, average daily truck traffic volume, material type, skew angle between bridges and roads, bridge deck structure type, and bridge type. The Elman neural network is then trained to train a prediction model for bridge condition ratings using the classified data, which can predict the condition levels of bridges. The Markov chain’s transition probability matrix is derived using a genetic algorithm to match the deterioration curve predicted by the Elman neural network. This proposed method, when applied to actual bridge data, demonstrates its effectiveness as evidenced by the condition rating of an actual bridge.

THE ROLE OF INTERNATIONAL TRANSPORT LOGISTICS IN OPTIMIZING TRANSPORT INFRASTRUCTURE ARCHITECTURES

Nowadays, transport infrastructure is a crucial component of any social and economic system. The arrangement of infrastructure is a top priority in economic activity due to the globalization of international logistics. This study aims to comprehensively analyse the transport infrastructure system regarding architectural objects. It also seeks to identify the main issues of the management paradigm in the industry and options for solving them. The research employed general scientific methods of cognition, including logical and structural analysis, comparison, theoretical modelling, abstraction, induction, and deduction, as well as statistical methods, specification, generalization, and formalization. The article examines innovative approaches to developing transport infrastructure in the international logistics system. The authors analysed the main issues, challenges, and achievements of managing the architectural component of transport infrastructure. The paper concludes that the effective use of transport infrastructure capabilities is essential for increasing the productivity of economic processes. The authors also identified the position and role of architectural objects in the international logistics system.

The Significance of the Factors Increasing the Asphalt Pavement Recycling Rate in the Country, Determined Using Multiple-Criteria Decision-Making Methods

Asphalt pavement, a component of transport infrastructure, deteriorates under the influence of destructive factors. The damages which have occurred during its period of use are repaired and the asphalt pavement is recycled when its further rehabilitation is economically and technically irrational. The material from the asphalt pavement layer that has reached its limit state is milled out or broken and crushed and then is repeatedly used in the production of hot-mix asphalt (HMA) or warm-mix asphalt (WMA) mixtures. In this paper, the dynamics of the percentage recycling ratio (RR) of old asphalt pavement material was investigated. RR represents the quantity of reclaimed asphalt pavement (RAP) used in the production of HMA and WMA mixtures in Europe and the USA, divided by the total amount of RAP prepared in the country. Factors and goals affecting it are analyzed. An original system of 10 criteria that increase the RR country has been created. Decision makers do not know which factors have the maximum influence in increasing the use of RAP and this should go in connection with environmental pollution reduction and achieving economic utility. By applying different multiple-criteria decision-making (MCDM) methods and using the importance given to these criteria by 14 experts, the normalized subjective weights of the criteria were determined. Analytic hierarchy process (AHP), rank correlation, average rank transformation into weight—linear (ARTIW-L) and non-linear (ARTIW-N), and direct percentage weight (DPW) methods were used in the study. The results show that the RAP recycle rate is close to 100% in countries with a sustainable economic background. In the Baltic countries, it is mostly increased by the adequacy of regulatory documents, the strategy promoting asphalt recycling in the country, and the homogeneity and classifying of RAP. The number and capacity of RAP stocks, the number and productivity of asphalt milling equipment and the wear and tear of the asphalt pavement have the least influence on the increase in RR. The opinions of experts in assessing the significance of all criteria are consistent. The averages of the weights of criteria determined by four MCDM methods (AHP, ARTIW-L, ARTIW-N, DPW) made it possible to obtain more reliable results. These results can be used to make strategic decisions and to create a plan of practical actions to increase the RAP recycling rate in the developing countries.

Digital twin-based non-destructive testing for structural health monitoring of bridges

ABSTRACT Bridges are critical components of transportation infrastructure, connecting communities and facilitating the movement of goods and people. Real-time monitoring of structural states of bridges can provide reasonable guidance for bridge maintenance. To reduce maintenance costs and extend the lifespan of bridges, a digital twin-based non-destructive testing (NDT) method for the structural health monitoring of bridges is proposed. The digital twin-based NDT method is realised by the combination of three-dimensional modelling technology, sensor technology, finite element (FE) method, and surrogate models. The main advantage of the proposed method is that each node of the FE model can be regarded as a virtual sensor to reflect the structural performance of the bridge. In other words, the structural performance of the entire bridge can be monitored by the digital twin-based NDT method. In addition, the digital twin-based NDT method integrates the advantages of FE models that can provide a causal relationship in structural analysis and the characteristics of surrogate models that are easy to build and less costly. The feasibility and effectiveness of the proposed method is demonstrated by a suspension bridge.

Design and Implementation of Artificial Intelligence-based Real-time Pothole Detection for IoT Smart Infrastructure

The Internet of Things (IoT) has been extensively deployed for Smart Cities due to its ability to process many different and heterogeneous end systems. The IoT innovation encourages artificial intelligence applications to process data. In Smart City infrastructure, the road is a critical component of transportation infrastructure that supports the economic, social, and cultural things of community life and various aspects of community life. Road conditions affect a variety of community activities. Good roads enhance comfort and support local businesses. However, many roads remain in bad condition, such as potholes. Various methods have been attempted to identify potholes, especially the two-dimensional imaging method. This paper proposes the real-time Artificial Intelligence detection of potholes using the Convolutional Neural Network (CNN), which leverages the Edge Tensor Processing Unit (TPU) with the MobileNet SSD v2. The system was set up on a Jetson Nano with a few extras, including a camera and GPS, to support the IoT infrastructure. Evaluation for the model consists of device implementation, model evaluation, GPS position deviation, and on-road implementation. The effectiveness is confirmed through experiments using a system test-bed that generates ideal mAP off 0.22 and recall values.

Optimizing Locations of Energy Storage Devices and Speed Profiles for Sustainable Urban Rail Transit

Urban growth and the resulting highway congestion is driving up demand for rail transit. Rail, a significant component of transportation infrastructure, is critical to economic efficiency and is one of the least energy-intensive modes. However, the scale of operations results in high energy consumption, atmospheric pollution, and operating costs. Fortunately, some of the braking energy can be harvested and either used to power a simultaneously accelerating train or stored to power subsequent accelerations. The objective of this research was to optimize the number of locations of the energy storage devices and speed profiles. First, kinematic equations were applied to simulate energy consumption. Then, a genetic algorithm (GA) was developed to optimize the speed profiles that minimize the energy consumption with and without a wayside energy storage unit (WESS) for a rail transit line. Finally, a model was developed to optimize the WESS locations that maximized the net benefit. A case study was conducted to examine the model in a real-world setting and to demonstrate its effectiveness. The results indicate that about 980 MWh of electrical energy, or an additional 5%, could be saved by optimizing the WESS locations over only applying speed profile optimization. In addition to significant energy savings, environmental emissions could be mitigated using these methods.

Examining Challenges in Complying with the Principles of Sustainability for the Design of Urban Bridges in Ethiopia

Existential issues obstruct the practice of incorporating sustainability concepts, which is the holistic consideration of urban bridge design factors. Bridge infrastructure is considered a connecting structure for separated highways and railways. The case for ensuring the safe mobility of people and goods across obstacles from one urban corner to another is viewed as an essential component of transportation infrastructure. The design and provision of urban bridges to attain sustainability are associated with tremendous challenges because of a lack of awareness and existential issues and obstacles. The problem in the practice of urban bridge design in Ethiopia is indicated as being “traditional” in delivery, with a lack of accommodation for many essential components of sustainable design. Therefore, a change in thinking is needed to address sustainability. The question of how designers could make design practice sustainable is complicated by multiple challenges. In this research, we used a survey questionnaire to collect the opinions of design professionals. Principal component analysis was employed to explore the major gaps in sustainable urban bridge design practice. A lack of sustainable design impact; sustainability awareness; design codes, practices, and standards that consider sustainability criteria; working guiding protocols and frameworks; and support for sustainability practice were identified as major challenges. Addressing the design problem requires a mechanism to consider the challenges through the defined participation of the designer, client, and public during rule setting, monitoring, and evaluation. Sustainability rating tools must also be deployed to evaluate and quantify the performance of urban bridges.

Structural behavior of damaged reinforced concrete beams under static cyclic loading

Bridges are regarded as one of the most important components of transportation infrastructure. More and more repairs, inspections, alterations, and construction processes are required to maintain safe usage due to increasing travel demands in addition to bridge infrastructure aging. In this paper, we will discuss the experimental investigation using five reinforced concrete beams to evaluate the effect of making damage to experimental beams under static cyclic loading to investigate their ductility and energy dissipation. The defective parameters taken into consideration in the experimental program were the gap in the concrete mold and mild steel at the middle bottom reinforcement. All tested specimens had the same cross-sectional dimensions. The concrete dimensions of the beams were 200 mm in width and 300 mm in height, and the beam's length was selected to be 2200 mm, having a clear span of 2000 mm between the supports, they were tested in positive bending using a 3-point bending load system. According to the results, when (RC) beams were subjected to any of the mentioned types of damage, they showed a significant decrease in ultimate capacities ranging from 3.03% to 19.31%. The ANSYS model shows an average difference with the experimental program within 4 % as an acceptable agreement.

Long-term structural health monitoring for bridge based on back propagation neural network and long and short-term memory

Bridges are critical components of transportation infrastructure. To ensure the long-term performance of bridges and the safety of the public, regular inspections are required during their service. Structural performance assessments are subject to various conditions. Structural deterioration is caused by complex environmental and operational conditions (EOCs) including temperature changes, truckloads, chemical corrosion, etc. In this study, an in-site structural health monitoring (SHM) system is designed and deployed on the Caohekou Bridge in China with a series of sensors installed, providing continuous real-time data for 4 years. Crack width, vertical deformation, concrete strains, temperature, longitudinal displacement and acceleration are monitored and assessed. Time-history monitoring data are comprehensively analysed to advance our understanding of structural deterioration caused by time and temperature. It is very common to lose data during the monitoring process, especially in the long-term run. To overcome the challenge of missing data package and to realize early warning, methods including an SHM systems face, a back propagation neural network and a long short-term memory are proposed to predict the bridge responses under the change of EOCs. It has been proved that the performance of predicted crack widths is close to that of the measured value, and the trend of change is consistent. Such results indicate that approaches proposed that quantitatively assess in-service structure are promising. Therefore, effective and efficient maintenance decisions can be made to ensure an immediate response, long-term safety and serviceability of bridge structures.

Unified hazard models for risk assessment of transportation networks in a multi-hazard environment

Transportation networks play a vital role in the economic prosperity of modern societies. Recent hazardous events in Greece, for instance, the 2021 Crete earthquake, the 2021 Thessaly earthquakes and floods, and the heavy 2019 rainfall in Crete, have revealed the vulnerability of roadway networks to natural hazards, resulting in severe physical damage and important economic and societal losses. Severe damage on bridges and tunnels of roadway networks is commonly related to the effects of multiple hazards that may act independently during their life span. However, the literature on risk assessment of the above elements commonly focuses on the effects of a single hazard, disregarding the effects of various hazards in a multi-hazard environment. In this context, there is an increasing need for a reasonable and practical evaluation of the multi-hazard risk of transportation infrastructure. Research project INFRARES (https://www.infrares.gr/) aspires to gain further insight into the risk and resilience assessment of bridges and tunnels subjected to independent and/or multiple subsequent natural hazards, proposing a comprehensive framework toward a more efficient risk assessment of the above critical transportation infrastructure components. This paper presents the first part of the framework. More specifically, a unified methodology for the development and graphic presentation of single seismic- and flood-hazard scenarios, as well as of novel multi-seismic-flood hazard scenarios, are presented, providing a valuable tool for risk assessment of roadway networks for separate, combined (triggered), or subsequent hazards. The unified approach followed to develop single seismic and flood hazard scenarios is initially presented. The data required to develop such scenarios are derived from recently published and freely available data accessible via European databases; hence, allowing for a straightforward application of the proposed methodology throughout Europe. The unified approach in developing single hazard scenarios is further exploited to develop integrated seismic-flood hazard scenarios. Single and multi-hazard scenarios are graphically displayed in the form of GIS format maps, with the methodology being applied to the Greek terrain for various hazard scenarios. Recent hazard events that caused significant damage to the Greek road network are also presented to emphasize the importance of proper evaluation of natural hazards and their effects on roadway networks in multi-hazard environments. The methodology developed within this study contributes toward the generation of uniform multi-hazard scenarios for the risk assessment of various structures and networks in a multi-hazard environment.

НАУКОВИЙ СУПРОВІД РЕМОНТУ МОСТА НА КМ 159 + 267 ПРИ РЕКОНСТРУКЦІЇ АВТОМОБІЛЬНОЇ ДОРОГИ Н-31 ДНІПРО – ЦАРИЧАНКА – КОБЕЛЯКИ – РЕШЕТИЛІВКА

Abstract Introduction. Bridges are one of the most important components of transport infrastructure. And transport structures are built of complex structures, and the cost of their operation is high. In the last period, the traffic intensity and weight of vehicles on the roads of Ukraine have significantly increased. Ensuring reliable and trouble-free operation is a priority, complex and responsible task. Problem statement. After the installation of a cement-concrete surface on the bridge on KM 159+267 of the H – 31 Dnipro – Tsarichanka – Kobelaki-Reshetilovka road, cracks were found on the cement-concrete surface across the entire passage after some time. Oblique and transverse cracks soon appeared in the surface on both adjacent bridges (separate bridges for different directions of movement). The opening of cracks reached 1 mm. Materials and methods. On the bridge at Km 159+267, an experimental design was applied – a cement-concrete coating made of concrete of class B40. It provides for the device of dense waterproof concrete of the roadway slab, 110 mm thick, made of monolithic concrete of Class B40 F300 W12 (C32/40, XF4, C1 0,20 according to DSTU b v. 2.7-176:2008, crushed stone fraction 5-10 mm), after the device of a monolithic slab with a thickness of 200 mm, combining the beams of the superstructure. To study damaged structures, methods for measuring the opening of cracks using probes and tape measures were used. To determine the adhesion of the coating to a monolithic slab, samples were taken – round cores using a core collector. The strength of the concrete was measured with a sclerometer. Results. As a result of the conducted research, the lack of adhesion of the cement-concrete coating to the monolithic slab of the bridge was revealed. To achieve high performance, it is necessary to disassemble the damaged cement-concrete surface and install a new coating to eliminate defects in the bridge surface on km 159 + 267 of the H-31 highway. Conclusions. Studies have shown that more and more new cracks appear in the cement-concrete coating, and the opening of old ones increases. The cause of cracks is shrinkage of concrete. Since concrete shrinkage can last up to 1.5 years, even more cracks should have been expected to appear. It also turned out that the cement-concrete coating does not adhere to the monolithic slab of the superstructure. Given the above reasons, it is impractical to repair individual cracks. To achieve high performance, it is necessary to disassemble the damaged cement-concrete coating and install a new one. Taking into account the capabilities of the contractor, the construction of the bridge bed and asphalt concrete pavement was developed. Keywords: bridge, highway, cement-concrete pavement, asphalt concrete.

Experimental investigation of subsurface defect detection in concretes by infrared thermography and convection heat exchange

Infrared thermography (IRT) is a non-destructive technique capable of detection and localisation of hidden subsurface defects in components of transportation infrastructure, such as concrete bridges, thereby contributing to structural health monitoring (SHM). Addressing the lack of research on subsurface defect detection in concretes by convection heat exchange, and regarding the importance of laboratory studies for proper implementation of IRT, this paper presents results from recent laboratory investigations of IRT on concrete slabs with simulated hidden defects using a convective thermal excitation mechanism. The concrete slabs in this study had simulated defects ranging 5–25 mm in depth from the surface. These studies show the effect of initial temperature, heating/cooling process, temperature range and defect depth on thermal contrast in the concrete slabs. Furthermore, this paper compares the performance of the IRT as a non-contact sensor and thermocouples attached to the surface, in the evaluation of the thermal contrast on slabs with various defect depth. The dependence of maximum thermal contrast on the initial temperature and defect depth is explored using multivariate linear regression.

Optimization of geometric parameters of arch bridges using visual programming FEM components and genetic algorithm

Arch bridges are essential components of transportation infrastructure. Their attractive geometry is based on a multitude of geometric parameters, which makes them a challenging design task. Therefore, arch bridges’ optimization should be aided by modern computational techniques and algorithms. This study presents an automated optimization process of steel through arch bridges. We merged visual programming, an accessible text programming alternative, with a genetic algorithm to establish an automated framework. We used Dynamo, an open-source civil engineering visual programming language (VPL), to develop a model generation script. Our finite element method (FEM) package enriched the basic VPL functions; it allowed geometry modeling and static strength analysis inside one parametric environment. Linked genetic algorithm replaced the designer in iterative, time-consuming optimization tasks, automating the process. The algorithm adjusted construction’s geometric parameters to provide solutions optimized for the typical objective: minimizing the material consumption while still fulfilling strength requirements. We evaluated the procedure with optimization of selected reference construction. The system dealt with cases of increasing complexity, adjusting cross-section dimensions, static scheme parameters, and material properties. The paper describes practical aspects of implementing and utilizing the visual programming-genetic algorithm solution, which can also be adapted for other structures, additional objectives, and constraints.

Transport infrastructure of Ussuriy city district: state, problems and solutions

The work considers the general characteristic of transport infrastructure and considers the main problems of Ussuriysk urban district. An analysis of the state of the main components of transport infrastructure (road, rail) of Ussuriysk city district has been carried out. A number of proposals aimed at improving the transport process necessary for the development of the Ussuriysk urban district have been considered. Keywords: infrastructure, urban district, transport network, analysis, transport and logistics center

ПІДХОДИ ДО ОЦІНКИ ЕФЕКТИВНОСТІ ФУНКЦІОНУВАННЯ ТРАНСПОРТНОЇ ІНФРАСТРУКТУРИ УКРАЇНИ

The article considers the essence and components of transport infrastructure, there were analyzed the dynamics of passenger and freight turnover for all modes of transport, and identified favorable and unfavorable factors influencing the domestic transport infrastructure. Thus, in the period 2015–2020, the dynamics of freight and passenger traffic of all modes of transport differed significantly. The data of 2020 have undergone special changes due to the impact of the COVID-19 coronavirus pandemic. Different approaches to assessing the efficiency of transport infrastructure were considered: Logistics Performance Index (LPI – Logistics Performance Index), Global Competitiveness Index (GCI), Global Infrastructure Index, Infrastructure Index of Ukraine. The first two indices are calculated by international organizations. The Global Infrastructure Index has been proposed by a team of scientists, but is not calculated on an ongoing basis. The last approach, which provides for the calculation of the Infrastructure Index of Ukraine, was proposed only in 2020, so it takes into account indicators only for 2020 and does not provide for the reflection of changes in this index in the dynamics. The results of evaluation of these indices for the transport infrastructure of Ukraine were analyzed. Summarizing the results of the evaluation of the efficiency of the transport infrastructure of Ukraine, it currently demonstrates an average level of efficiency. A comparative analysis of these approaches was carried out. Thus, some approaches are assessing the infrastructure of the country as a whole, paying little attention to its transport component. Other approaches evaluate more than once every few years, which does not always take into account the current situation, which is changing rapidly. It was concluded that it is necessary to develop a single methodology for assessing the effectiveness of transport infrastructure, which would be consistent with international approaches and provide an opportunity to constantly monitor (annually) the dynamics of changes in transport infrastructure.