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This paper presents a bibliometric analysis within the research domain dedicated to the utilization of agent-based modeling (ABM) in the field of transportation. By employing specific keywords related to both agent-based modeling and transportation, we have identified and extracted 1016 scholarly papers from the ISI Web of Science database, spanning the period from 2002 to 2023. Through the application of bibliometric methods, we have systematically examined key contributors, affiliations of academic institutions, influential publications, and renowned journals within this domain. Our analysis reveals a consistent and robust growth in scholarly interest pertaining to agent-based modeling in the field of transportation throughout the considered period. Notably, within approximately four decades of ABM's application in transportation, a distinct upward trajectory began in 2008, culminating in the year 2021. The entire considered period witnessed a remarkable surge in paper production, characterized by an annual growth rate of 21.67%. Furthermore, employing an n-gram analysis, we have delineated and discussed the principal areas within transportation that have progressively benefited from the advancements in agent-based modeling. Prominently, the domains of air transport and road transport have exhibited substantial development over time, while the implications of climate change have emerged as a persistent concern throughout the entire study period. [ABSTRACT FROM AUTHOR]

Efficient specialized vehicle cooperative scheduling is significant for airport operations, particularly during times of high traffic, which reduces the risk of flight delays and increases customer satisfaction. In this paper,we construct a multi-type vehicles collaborative scheduling model with the objectives of minimizing vehicle travel distance and vehicle waiting time. Additionally, a three-layer genetic algorithm is designed, and the crossover and mutation operations are enhanced to address the scheduling model. Due to the numerous uncertainties and stochastic interferences in airport operations, conventional scheduling methods unable to effectively address these challenges, this paper combines improved genetic algorithm, simulation algorithm, and digital twins technology, proposing a multi-strategy scheduling framework for specialized vehicles based on digital twins. The scheduling framework utilises digital twins to capture dynamic data from the airport and continuously adjusts the scheduling plan through the scheduling strategy to ensure robust scheduling for specialized vehicles. In the event of severe delays at the airport, fast and efficient re-scheduling can be achieved. Finally, the effectiveness of the proposed scheduling framework is validated using domestic flight data, and extensive experiments and analyses are conducted in different scenarios. This research contributes to addressing the optimization problem of cooperative scheduling for multi-type vehicles at airports. [ABSTRACT FROM AUTHOR]

This paper presents the initial steps taken in analysing the benefits of connected autonomous vehicles (CAVs), especially Modular Autonomous Vehicles (MAVs), in search of sustainable solutions for reducing energy consumption per passenger in air transport. For this particular case, a Mobility-as-a-Service (MaaS) solution is proposed, correlating airside transport with landside transport, as an urban mobility alternative. To better understand the benefits of the proposal, this paper studies the impact on energy consumption conceptual differences between a conventional public transport fleet using Battery Electric Buses (BEBs) and an MAV fleet. Simulations for simple public transport tasks are performed to highlight the advantages of the modular vehicle concept, in which routes are assigned dynamically based on the requested passenger carrying capacity and travel distance, aiming to optimize the efficiency of the entire system. With a proven reduction in energy consumption due to better use of available passenger capacity and reduced travel times in which the vehicle is driving with a number of passengers less than half of its capacity, the concept can be addressed further in developing a predictive system that processes public transport data and delivers an optimized schedule for the entire fleet. The main goal being to improve overall operational efficiency and total cost of ownership, the second part of the paper studies the impact of weight distribution on efficiency parameters such as energy consumption, range, and overall performance of an electric bus. The impact on dynamic elements such as acceleration, braking, and cornering performance is analyzed, to assess the viability and safety of all types of electric bus operations. [ABSTRACT FROM AUTHOR]

This paper studies the performance of machine learning predictions for the counterfactual analysis of air transport. It is motivated by the dynamic and universally regulated international air transport market, where ex post policy evaluations usually lack counterfactual control scenarios. As an empirical example, this paper studies the impact of the COVID-19 pandemic on airfares in 2020 as the difference between predicted and actual airfares. Airfares are important from a policy makers' perspective, as air transport is crucial for mobility. From a methodological point of view, airfares are also of particular interest given their dynamic character, which makes them challenging for prediction. This paper adopts a novel multi-step prediction technique with walk-forward validation to increase the transparency of the model's predictive quality. For the analysis, the universe of worldwide airline bookings is combined with detailed airline information. The results show that machine learning with walk-forward validation is powerful for the counterfactual analysis of airfares. [ABSTRACT FROM AUTHOR]

The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020–2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020–2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development. [ABSTRACT FROM AUTHOR]

Approximately 40 % of the final energy is used for heating and cooling of buildings. Of this, as much as 75 % is used in residential buildings. The proportion of energy needed in buildings is relatively high, so it is necessary to start using technologies that have low energy consumption, use it efficiently or provide it from renewable sources. One such technology is thermal energy storage, which allows us to store excess energy for later when we need extra energy. The paper presents two experiments in the field of adsorption space heating. In the first experiment, measurements were carried out on the adsorbents - zeolite 13X and zeolite NaYBFK, which were placed into a duct, through which humid air was transported by means of a centrifugal fan. In the second experiment, water vapour as the working medium was used. With the first experiment we achieved better water uptake on NaYBF, while the second experiment shows the increase of water uptake of zeolite 13X. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic negatively affected many sectors including aviation and travel. Travel bans and forced lockdowns prevented transportation activity, especially air travel. Accordingly, huge amounts of emission reductions occurred. On the other hand, travel restrictions are not the only cause of emissions reductions. Changing travel intention in the era of Covid-19 is another important factor that affects aviation emissions. This paper aims to investigate the Landing/Take-Off (LTO) emission changes at Turkish airports. An emission inventory has been implemented for the years 2019 and 2020 to reveal the impacts of Covid-19 on aviation emissions. Domestic, international, and cargo flights have been included in the inventory. According to the results, total emissions of SO2, CO2, CO, NOx, NMVOC, CH4, N2O, and PM2.5 have decreased in 2020 compared to 2019 by 49.8%, 49.7%, 41.0%, 52.6%, 40.0%, 33.8%, 49.8%, and 50.3%, respectively. Total CO2 reductions in the Q2, Q3, and Q4 periods of 2020 compared to that of 2019 are 87%, 50% and 43%, respectively. Another aim of this paper is to find the underlying reasons for emission reductions. For Turkish airports, emission reductions have resulted from travel bans in Q2. After the relaxation of restrictions with the declaration of the "New Normal" in Turkey, flight traffic rebounded to a certain level but was lower than 2019 levels. Therefore, changing travel intention is the main cause of emission reductions in Q3 and Q4 of 2020. The results of this study contribute to both the areas of air pollution and tourism management. [ABSTRACT FROM AUTHOR]

The continuous and strategic planning of full-service carriers plays a prominent role in transferring and adapting them into resilient full-service carrier network structures. The exploration of full-service carrier network structures using the latest long-term empirical data facilitates enhancing cognitive capabilities in aspects of identifying network development tendencies, readjusting network structures, and supporting determinations of strategic business routes. Aiming at providing sustainable transport network solutions with historical long-term network structure analysis, this paper researches the global top 10 full-service carriers' air transport networks from 2007 to 2022, applied using social network analysis (SNA). The static metrics from local to path-based perspectives are adopted to explore the global network evolution trend, along with competitiveness characteristics over critical airports. The cascading failure model is applied as a key indicator to analyze the dynamic robustness capability for the network. The similarity changing feature among the selected networks over the past years from 2007 to 2022 is measured using the autocorrelation function (ACF). The results indicate that, from 2011 to 2019, the majority of full-service carrier networks belong to the network types of closed, structural symmetry and two-way transitivity. The critical airports in North America present superiority in terms of network efficiency over those in Europe, Asia, and Oceania. The 10 full-service carriers' air transport networks all show the trend of being more destruction-resistant. During the COVID-19 pandemic period, the merger with other airlines and the signing of a joint venture agreement led to higher temporal variability in the network structure. [ABSTRACT FROM AUTHOR]

Background: International transportation has grown substantially, causing total logistics costs (TLCs) to rise. Companies are increasingly striving for their reduction. The most crucial factor affecting TLCs is the transportation mode, and its appropriate selection has become vital for firms. Maritime transport is the most preferred mode for international shipments, while air transport is also increasingly preferred due to the rise in underweight and high-frequency shipments, the expectation of reduced delivery times, and inventory costs. However, a thorough comparative analysis is necessary for the selection. Methods: This paper proposes an intelligent approach based on TLCs. Non-linear optimization is adopted for regular replenishment, while maching-learning classifiers are employed to establish a decision boundary for the chargeable weight of shipments. Conclusions: The study assists in decision making and also establishes a country-wide threshold, highlighting the importance of a country-based logistics strategy. The paper successfully establishes the trends and relations between logistics parameters, which assists the logistics decision making. Research identifies the gaps in the existing literature and bridges them by addressing the required concerns. [ABSTRACT FROM AUTHOR]

Recent technological developments in aviation, such as vertical take-off and landing and electric engines, are bringing the development of integrated urban air transport systems closer and are generally helping to promote the concept of Urban Air Mobility (UAM). UAM makes it possible to provide integrated air transport services for people and goods in urban areas, reducing travel time initially and leading to cost reductions in the future. The development of UAM will allow urban airspace to be used for short and medium range operations, potentially connecting larger urban areas or neighbouring cities. However, the operation of UAM requires, on the one hand, the development of appropriate urban infrastructure to provide full and vertical support for aircraft, such as vertical landing and take-off areas, specially designed intermediate areas for embarkation and disembarkation of passengers and cargo, as well as areas with operational technical bases for loading, parking and maintenance of aircraft. All this is the concept of the VertiPorts/Voloports/Vertistops. However, the development of a VertiPorts/Voloports/ Vertistops in the dense and complex modern urban environment can be challenging, as on the one hand specific rules for aviation safety have to be followed, and on the other hand their integration into the urban environment requires compliance with the rules of urban planning, land use and protection of private property.This paper presents the challenges that researchers have to face in order to integrate Voloports into an already formed and dense urban environment, such as that of the city Athens, the metropolitan centre and capital of Greece, in respect to various constitutional, institutional and spatial restrictions. [ABSTRACT FROM AUTHOR]

This paper demonstrates the effectiveness of the Extended First-Come, First-Served (EFCFS) scheduler for integrated arrival and departure scheduling by comparing the scheduling results with the recorded operational data at Incheon International Airport (ICN), Republic of Korea. The EFCFS scheduler can handle multiple capacity- or flow-rate-related constraints along the path of each flight, which is represented by a node–link graph structure, and can solve large-scale problems with low computational cost. However, few studies have attempted a systematic verification of the EFCFS scheduler by comparing the scheduling results with historical operational data. In this paper, flights are scheduled between gates and runways on the airport surface with detailed constraints such as runway wake turbulence separation minima and conflict-free taxiing. The scheduler is tested using historical flight data from 15 August 2022 at ICN. The input schedule is generated based on the flight plan data extracted from the Flight Operation Information System (FOIS) and airport surface detection equipment data, and the results are compared with the times extracted from the FOIS data. The scheduling results for 500 aircraft show that the average takeoff delay is reduced by about 19 min, while the average landing delay is increased by less than one minute when the gate occupancy constraint is not considered. The results also confirm that the EFCFS effectively utilizes the available time slots to reduce delays by switching the original departure or arrival orders for a small number of flights. [ABSTRACT FROM AUTHOR]

As the aviation industry seeks sustainable propulsion solutions, innovative technologies have emerged, among which rim-driven fan (RDF) systems hold notable promise. This comprehensive review paper deeply investigates RDF technology, uncovering its principles, benefits, and transformative potential for aviation propulsion. Amid escalating concerns about greenhouse gas emissions, the aviation sector's shift towards electric propulsion has gained impetus. RDF technology has emerged as a beacon of optimism, heralding the prospect of energy-efficient and eco-conscious air travel. Navigating the slower development pace of RDF technology for aerospace applications, this paper draws insights from analogous marine technologies and relevant literature. Merging these realms, this paper meticulously examines RDF systems, spotlighting their unique attributes, with particular emphasis on the rim-driven configuration and its fundamental design principles. This review delves into the progressive strides accomplished in RDF's evolution, encompassing the spectrum from evolving electric motor variants to intricate design considerations, strategic noise and vibration management, innovative control methodologies, advancements in bearing technology, and the strategic integration of finite element analysis (FEA) and computational fluid dynamics (CFD) for comprehensive performance optimization. In the context of aviation's electrification journey, the exploration of RDF technology marks a pivotal inflection point. This paper concludes by succinctly encapsulating pivotal insights, accentuating RDF technology's central role in reshaping aviation's propulsion paradigm. As the aviation sector charts a course towards sustainable progress, the lessons gleaned from RDF technology are poised to chart the trajectory of aviation's environmental transformation. [ABSTRACT FROM AUTHOR]

Carbon emission intensity is an important index reflecting an entity's low-carbon competitiveness. This paper presents an extended logarithmic mean divisia index (LMDI) model to dissect carbon intensity within China's civil aviation from 1998 to 2019, revealing a significant reduction in CO2 emissions per air transport revenue. It attributes this decrease to technological advancements, optimized fleet structures, and improved operational efficiencies, highlighting the impact of larger, more efficient aircraft and enhanced load factors. The study also explores economic factors influencing carbon efficiency, suggesting a comprehensive approach encompassing technological innovation and strategic operational improvements for sustainable aviation development. [ABSTRACT FROM AUTHOR]

Most accidents and serious incidents of commercial air transport helicopters occur during standard flight phases, whereby a main cause is pilots' situational awareness. Enabling pilots to better assess their situational awareness can make an important contribution in reducing the risk of fatal accidents. One approach is to examine a pilot's gaze behavior with the help of eye tracking. This paper reports the results of a case study with eye tracking measurements during real flight and simulator studies of a standard mission profile. The general gaze behavior is characterized by a dominant, external view, and the airspeed and altitude indicator as the most important flight instruments. A real-world applicability of gaze data obtained in the simulator could be shown. [ABSTRACT FROM AUTHOR]

Connection trips is often an important part of long-distance travel, especially for air travel. Models of long-distance travel would therefore benefit from a more detailed representation of the connection part. In this paper it is however shown that most models of connection trips are stand-alone models not integrated with the model for main mode. Only a handful models that integrate connection trip modelling into a large-scale transport model for long-distance travel are found. The connection trip models are classified into different types using a typology developed within the paper. The typology identifies nine model types that differ in how access/egress mode choice and terminal choice are handled. The scarce literature on connection trip modelling within large-scale transport modelling systems call for more research regarding detailed representation of access/egress mode choice and terminal choice, especially regarding the trade-off between model complexity and detailed representation, as well as whether the detailed representation of connection trips should primarily be conducted within the public transport network assignment or on the demand modelling side. [ABSTRACT FROM AUTHOR]

Contact network models are recent alternatives to equation-based models in epidemiology. In this paper, the spread of disease is modeled on contact networks using bond percolation. The weight of the edges in the contact graphs is determined as a function of several variables in which case the weight is the product of the probabilities of independent events involving each of the variables. In the first experiment, the weight of the edges is computed from a single variable involving the number of passengers on flights between two cities within the United States, and in the second experiment, the weight of the edges is computed as a function of several variables using data from 2012 Kenyan household contact networks. In addition, the paper explored the dynamics and adaptive nature of contact networks. The results from the contact network model outperform the equation-based model in estimating the spread of the 1918 Influenza virus. [ABSTRACT FROM AUTHOR]

This paper takes the airport terminal area as the main research content and combines genetic algorithm with airport terminal area analysis theory to analyze and study the traffic scheduling in the airport terminal area. Based on the study of traditional traffic scheduling techniques and key techniques of genetic algorithms, this paper participates in the actual project of genetic algorithm-based traffic scheduling, analyzes the requirements of the project, focuses on the design and implementation of the traffic scheduling algorithm module in the genetic algorithm-based traffic scheduling system, and conducts further research on the pathfinding by constraints submodule. In this paper, the flight approach and departure sequencing problem and runway allocation problem are the main research objects. The dynamic optimal scheduling model of flight approach and departure is established by considering the interests and demands of airlines and airports, and a new scheduling algorithm is proposed. In this paper, a brief introduction to the airport terminal area is given, and the feasibility of the approach/departure optimal scheduling is introduced from the perspective of airlines with a long-range parallel two-runway airport as the research background. Secondly, through the analysis of the flight approach and departure process and the study of the approach and departure cooperative optimization strategy, a single-runway flight approach and departure traffic scheduling model under the joint sequencing strategy is established with the optimization objective of minimizing the total flight delay time, and the model is solved by using the sliding time window algorithm. Then, based on the single-runway scheduling model, a multirunway multiobjective flight optimal scheduling model is established with the objectives of minimizing total delay time, increasing runway throughput per unit time and fairness of flight delay time allocation, and a dynamic algorithm (STW-GA) combining sliding time window algorithm and dual-structured chromosome genetic algorithm is proposed to solve the model. [ABSTRACT FROM AUTHOR]

With the development of society and the improvement of people's material level, more and more people like to travel by airplane. If we can predict the passenger flow of an airline in advance, it can be used as an important decision-making basis for its flight route planning, crew scheduling planning and ticket price formulation in the process of management and operation. However, due to the high complexity of aviation network, the existing traffic prediction methods generally have the problem of low prediction accuracy. In order to overcome this problem, this paper makes full use of graph convolutional neural network and long—short memory network to construct a prediction system with short—term prediction ability. Specifically, this paper uses the graph convolutional neural network as a feature extraction tool to extract the key features of air traffic data, and solves the problem of long term and short term dependence between data through the long term memory network, then we build a high-precision air traffic prediction system based on it. Finally, we design a comparison experiment to compare the algorithm with the traditional algorithms. The results show that the algorithm we proposed in this paper has a higher accuracy in air flow prediction according to the lower loss function value. [ABSTRACT FROM AUTHOR]

The paper explores the potential to enhance aviation safety, particularly in militarized regions, by outfitting aircraft with Side Looking Airborne Radar (SLAR) and employing space-time adaptive processing (STAP) algorithms. The research objective revolves around implementing a model of side-looking airborne radar and the corresponding STAP algorithms. This technology enables the detection of slow-moving targets amidst strong interference, encompassing both passive (clutter) and active (jammer) elements. Slow-moving targets relative to the aircraft's speed include tanks, combat vehicles, command vehicles, artillery, and logistical assets of enemy forces. The theoretical framework of space-time adaptive processing is presented, elucidating the sequential steps of the classical Sample Matrix Inversion Space-Time Adaptive Processing (SMI STAP) algorithm. The paper underscores the significance of characteristic parameters delineating a linear STAP processor. The proposed solution facilitates the detection of enemy combat measures and enhances aviation safety. It outlines a radar model installed beneath the aircraft's fuselage and elucidates algorithms for space-time adaptive processing of radar signals. The simulations conducted within the article were executed using the MATLAB environment. The simulation results indeed suggest that the proposed solution holds promise for deployment in equipping aircraft of one's own military and those engaged in operations within conflict zones. This paper stands as one of the few contributions in the literature addressing the augmentation of aircraft safety through radar and space-time adaptive processing. [ABSTRACT FROM AUTHOR]

The paper investigates the evolution of air passenger profiles in terms of regulatory environment, competitive landscape, socio-economic and demographic trends. The research is supported by passenger surveys carried out since 2001. The surveys have been designed to provide objective and in-depth insights into the preferences and behaviors of air passengers in the Serbian market. The resulting passenger segments are categorized based on socioeconomic and travel purpose criteria, but the surveys conducted at Serbian airports reveal that competition triggered the service quality to become a major issue in the Serbian market, after the entrance of low-cost carriers. The research of future projections of air passengers in Serbia is based on the Delphi method for two-time horizons (2025 and 2035) and three future scenarios are proposed. [ABSTRACT FROM AUTHOR]

Atmospheric air pollution with fine particles PM2.5 and PM10 is one of the main environmental problems of the city. This paper presents the results of the study of quantitative and structural components of solid particles’ emissions in the city of Almaty, released during the operation of cars: by an engine with exhaust gases, by tire abrasion, by braking devices (linings) and road pavement wear. РM solid particles in the amount of 543.2 tons are released annually into the atmospheric air of Almaty by motor transport. The bulk PM10 is released totally from the tires, brakes and road – 65.4 %, from the engine – 34.6 %. On diesel buses and trucks, the bulk РM particles’ emissions are released from the exhaust gas engines. Recommendations are given to reduce PM particles emitted by motor transport. [ABSTRACT FROM AUTHOR]

Air travel market has changed significantly by the emergence of a lowcost carrier (LCC). The LCCs offer lower fares and fewer frills than the traditional full service carriers (FSCs). The key competitive advantage of the LCCs is their ability to offer significantly lower fares, or at least to create the image of offering lower fares, while being able to generate profits by having low unit costs. LCCs have reshaped the competitive environment within air travel markets and have made significant impacts in the domestic passenger markets, which had previously been largely controlled by FSCs. The new demand for air travel experience through the low fares of low-cost airlines increases the likelihood of choosing not only low-cost airlines but also existing large airlines when choosing air travel. This generally equates to the intention of customers to move to more advanced products as their experience with new products increases. Therefore, the purpose of this study is to theoretically discuss the operating characteristics and market ripple effects of low-cost airlines, and to explore the theoretical implications of existing papers. [ABSTRACT FROM AUTHOR]

This paper examines the impact of strategic sub-components of the Global Competitiveness Index (GCI) on the Logistics Performance Index (LPI), positing a correlation between the LPI and selected GCI factors, specifically within the infrastructure domain--namely, the indicators of road quality, rail service efficiency, port efficiency, air transport efficiency, and electrification. The objective is to identify which indicators within the infrastructure sector most significantly affect the Logistics Performance Index. In this study, the LPI is the dependent variable, while the five previously mentioned competitiveness indicators act as independent variables. A panel data regression analysis was employed to evaluate how these independent variables influence the dependent variable. The data for this study were derived from the World Bank, specifically the LPI of the World Bank and the World Economic Forum, covering countries in the ASEAN region from 2012 to 2020. The findings indicate that, among the five indicators, port efficiency significantly impacts the Logistics Performance Index in the ASEAN region. Furthermore, air transportation efficiency and electrification significantly influence the Logistics Performance Index. Conversely, road quality and rail service efficiency do not significantly affect the Logistics Performance Index in the ASEAN region. [ABSTRACT FROM AUTHOR]

The green hub‐and‐spoke airline network (GHSAN) is emerging as a dominant feature due to its excellent economic and environmental‐friendly capabilities. However, environmental GHSAN designs still have some concerns, including single pollutant‐domain oversimplification and lack of comprehensive network‐level operation impacts. This paper proposes a multi‐emission‐driven efficient network design approach for GHSAN, utilizing a system, green, and user threefold optimization methodology. The approach includes a multi‐objective optimization model and a two‐layer solving method. The multi‐objective optimization aims at minimizing multiple emissions, including carbon dioxide, carbonic oxide hydrocarbon, and nitric oxide, while also considering transportation system costs and journey user costs. A two‐layer optimization algorithm is adopted to address different scales of optimization. Real‐world results demonstrate that the proposed method mitigates environmental impact and user costs and increases overall airline density in airline networks. The proposed method can have a 16.29% reduction in green‐fold (10 nodes) and a 12.06% decrease in user costs for the user‐fold (10 nodes). As the number of nodes (15, 25, 50 nodes) and hubs (3, 4, 5, 6, 7 hubs) increase, the genetic algorithm (GA) proves to be more efficient and suitable in large‐scale GHSAN. This work is further significant for the long‐term and sustainable development of the future air transport industry. [ABSTRACT FROM AUTHOR]

In recent years, virtual reality technology, which is able to simulate real-life environments, has been widely used in the field of intervention for individuals with autism and has demonstrated distinct advantages. This review aimed to evaluate the impact of virtual reality technology on safety skills intervention for individuals with autism. After searching and screening three databases, a total of 20 pertinent articles were included. There were six articles dedicated to the VR training of street-crossing skills for individuals with autism, nine articles focusing on the training of driving skills for individuals with ASD, and three studies examining the training of bus riding for individuals with ASD. Furthermore, there were two studies on the training of air travel skills for individuals with ASD. First, we found that training in some complex skills (e.g., driving skills) should be selected for older, high-functioning individuals with ASD, to determine their capacity to participate in the training using scales or questionnaires before the intervention; VR devices with higher levels of immersion are not suitable for younger individuals with ASD. Second, VR is effective in training safety skills for ASD, but there is not enough evidence to determine the relationship between the level of VR immersion and intervention effects. Although the degree of virtual reality involvement has an impact on the ability of ASD to be generalized to the real world, it is important to ensure that future virtual reality settings are realistic and lifelike. Again, adaptive models that provide personalized training to individuals with ASD in VR environments are very promising, and future research should continue in this direction. This paper also discusses the limitations of these studies, as well as potential future research directions. [ABSTRACT FROM AUTHOR]

Purpose - Since airlines that employ their resources effectively will achieve operating profitability, air route resource allocation is significant for airlines. This study aims to investigate an appropriate model to reallocate resources into each air route of an airline company. Design/methodology/approach - This study proposes a network centralized data envelopment analysis (DEA) models with slack-based measure (SBM). The proposed model not only takes into account the two interconnected stages but also considers the nonradial approach with transfer-in and transfer-out slacks for resource reallocating. Furthermore, the authorsmodify the objective function to an input-oriented function with SBM, and divide the model into passenger and freight parts, which makes the model more realistic for the characteristic of air routes. Findings - The empirical analysis using an airline company's internal data provides airline operators with information on how they increase or decrease input resources, which can serve as a practical guideline of resource reallocation. Specifically, the results indicate that the airline company should increase their input resources into longhaul air routes such as KOR-OCN while decreasing their input resources into short-haul air routes such as Korean-Oceania (KOR-OCN), Korean-Chinese (KOR-CHN), Korean-SoutheastAsian (KOR-SEA), Korean-Japanese (KOR-JPN). Originality/value - Although some papers evaluate air route efficiencies based on the DEA approach, a few existing papers have addressed resource allocation for air routes. This paper is the first to study the resource reallocation for air routes based on the DEA approach, contributing to the literature in expanding the scope of research on resource reallocation. [ABSTRACT FROM AUTHOR]

Flight demand forecasting is a particularly critical component for airline revenue management because of the direct influence on the booking limits that determine airline profits. The traditional flight demand forecasting models generally only take day of the week (DOW) and the current data collection point (DCP) adds up bookings as the model input and uses linear regression, exponential smoothing, pick-up as well as other models to predict the final bookings of flights. These models can be regarded as time series flight demand forecasting models based on the interval between the current date and departure date. They fail to consider the early bookings change features in the specific flight pre-sale period, and have weak generalization ability, at last, they will lead to poor adaptability to the random changes of flight bookings. The support vector regression (SVR) model, which is derived from machine learning, has strong adaptability to nonlinear random changes of data and can adaptively learn the random disturbances of flight bookings. In this paper, flight bookings are automatically divided into peak, medium, and off (PMO) according to the season attribute. The SVR model is trained by using the vector composed of historical flight bookings and adding up bookings of DCP in the early stage of the flight pre-sale period. Compared with the traditional models, the priori information of flight is increased. We collect 2 years of domestic route bookings data of an airline in China before COVID-19 as the training and testing datasets, and divide these data into three categories: tourism, business, and general, the numerical results show that the SVR model significantly improves the forecasting accuracy and reduces RMSE compared with the traditional models. Therefore, this study provides a better choice for flight demand forecasting. [ABSTRACT FROM AUTHOR]

This paper assesses the impact of transport infrastructure quality on economic competitiveness in the European Union (EU), context in which we argue that the quality of the different modal transport networks has a differentiated contribution on competitiveness. The purpose of our analysis aims to quantify the qualitative contribution of each modal transport network to economic competitiveness in the EU. The econometric quantification of the mentioned impact emphasizes a contributory hierarchy as follows: the quality of port and railroad infrastructure contributes most substantially to economic competitiveness, followed by the quality of the air transport infrastructure, the inland waterways and the road network. Based on the iterated results, we sequenced the EU member states with the lowest quality of networks with the highest impact on competitiveness. Thus, we identified the states for which the priority improvement of the quality of the port and railway infrastructures would significantly improve their economic competitiveness. [ABSTRACT FROM AUTHOR]

The number of COVID 19 infections worldwide by the end of September 2020 rose to more than 34 million cases. At the same time number of fatalities caused by the same virus exceeds one million. In the year 2020 about ten per cent drop of economic growth was experienced compared to the previous year due to COVID 19 crisis and with probably the biggest impact on tourism industry. The results of global tourist international arrivals in April, May and June 2020 with drop of 95-98 per cent are self-explanatory. Thus, stabile and continuing growth from the beginning of 21st century has been suddenly brutally interrupted returning the tourism industry on level of at least 30-40 years back, maybe even more. The consequences of COVID 19 on touristic results have been analysed in the paper. The analysis is based on four different geographical areas - global, European, Southeast European and Croatian, based on the last 20 years of tourism results. Since similar dramatic situation has also affected air transport industry, the correlation between the tourism and air carriers' results in the last two decades is also considered in this paper. Different scenarios of the future recovery of tourism industry are considered in the paper [ABSTRACT FROM AUTHOR]

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Flight delay prediction is one of the most significant components of intelligent aviation systems that may spread throughout the whole aviation network and cause multi-billion-dollar losses faced by airlines and airports, it is quickly becoming an important research issue to improve airport and airline performance. Thus this paper proposed an effective algorithm called Flight Delay Path Previous-based Machine Learning (FDPP-ML) capable of improved prediction of individual flight delay minutes using regression models to an up level of accuracy. As aviation system connectivity presents complex spatial–temporal correlations, machine learning approaches have addressed flight delay prediction by using complex flight or weather features, or private information for specific airports and airlines that are hard to obtain, In contrast, the proposed FDPP-ML improved prediction based only on basic flight schedule features even with wide flight networks. The FDPP-ML consists of a novel algorithm with a supervised learning model, which works on reshaping datasets and creates two new features the main feature is previous flight delay (PFD) for flight paths, there is a strong relationship between departure and arrival delay, and vice versa for the same flight path, which increases the strength of the training model based on historical data. For target future flights, the algorithm works on inheriting the predicted flight delay to the next flight on the same flight path and repeats this process to end the prediction forecast horizon. The proving of approach effectiveness by using a wide network of US flight arrival and departure flights containing 366 airports and 10 airlines with various metrics accuracies of regression, and explanatory the impacts on various forecast horizons 2, 6, and 12 h for future flights. The FDPP-ML outperforms traditional training models by using machine and deep learning models and improving model accuracy in 10 models with an average of up to 39% in MAE, and 42% in MSE in a forecast horizon of 2 h. Finally, providing airport and airline analysis further reveals that can improve prediction than traditional training models for the individual busiest airports "Core 30" with an average of 35% in MAE and 42% in MSE respectively, and for the busiest 10 airlines with an average of 36% in MAE and 47% in MSE respectively. The findings of this study may offer informative recommendations to airport regulators and aviation authorities for developing successful air traffic control systems for enhanced flight delay prediction to flight operational effectiveness, not only over the US flight network but with wide worldwide flight networks if a dataset of flights existed. [ABSTRACT FROM AUTHOR]

Design/methodology/approach: This paper used pervious related to aviation literatures to summarise and viewpoint the current aviation environment and conduct the risks, value, and resilience of grounded aircraft-value in the post-pandemic era. Purpose: Throughout 2020 to date, this major event, known as SARS CoV-2, has had a decisive impact on global air transport. Since the outbreak began, passenger travel has declined due to infection risks and new laws and travel restrictions. Dependent Surveillance-Despite the recent recovery in demand from the airline industry, risks posed by new models remain a concern for many airlines. From the data of Broadcasting (ADS-B) is helpful for preliminary observation and judgment of the value level of a certain type of aircraft. Findings: This paper not only focuses on the aviation environment, but discusses aviation highlights such as international perspectives, domestic (i.e. Taiwan) perspectives, and several issues between industry and academic perspectives. Research limitations/implications: The next phase of research needed in this area is a closer assessment of the value of aircraft in the development of global networks, which could have important policy implications for aircraft manufacturers and the aviation industry. Originality/value: This paper provides a contemplative perspective about the aviation industry. [ABSTRACT FROM AUTHOR]

Bearing in mind the socio-economic consequences of COVID-19 on airports and passengers, this study considers cleaning and hygiene a top priority in airports and airlines' operating processes. Both airport operators and passengers should be aware that the COVID-19 pathogen has not yet gone away and, thus, continues to spread despite mass vaccination. In this context, this paper's objective is to show the importance of cleaning and hygiene in the air transport industry to encourage the passengers' confidence in making decisions to travel on commercial airlines and help airport and airline operators make better decisions in their efforts to improve the cleaning and hygiene protocols. Passengers' awareness of hygiene and cleanliness has increased, but unfortunately, airports and airlines have reduced cleaning and hygiene activities to save costs. Although there is much to do to help the aviation sector recover, we also see plenty of reasons to be optimistic about the air transport industry's future, as long as airport and airline operators can guarantee an adequate quality of service with regard to cleaning and hygiene in order to ensure passengers' safety and well-being. Airports and airlines cannot lower their guard because the SARS, H1N1, MERS, and COVID-19 viruses remain active in society. [ABSTRACT FROM AUTHOR]

Purpose: The EU Green Deal aims at making the continent climate-neutral by 2050. This heavily impacts the logistics sector, which currently predominantly relies on carbon-emitting ground, sea and air transports. While there are economic incentives to implement innovative emission-free alternatives in urban regions, rural areas can barely even hope for economical transportation services and thus are often supplied by traditional, emission-intense, means of transport. In particular, Remote Rural Areas (RRAs) provide a challenge to this goal: A combination of factors hinders the application of modern sustainable transport solutions in this context. The purpose of this paper is to define and analyse emission-free transportation in RRAs, providing an overview of current approaches to the issue and aiming to synthesize an opportunity to improve current concepts. Methodology: It provides an overview of existing literature on supplying remote rural regions, with a special focus on emission-free transportation. It relies on quantitative methods, exemplary comparison and analysis of current good practices. Results: The research results in the proposal for an implementation process for associated transportation concepts in RRAs, based on a detailed discussion of literature and practice. This combined logistical concept supports decision makers in their task of supplying their regions sustainably. Conclusion: The paper concludes that freedom from emission is claimed more often than it is realised. Nevertheless, often independent RRA systems provide favourable conditions for achieving the Green Deal objective, assuming that funding and interest in the issue are given. [ABSTRACT FROM AUTHOR]

This paper presents an innovative solution for a distributor head equipped with a deflector (controlled plate)—intended to change the tilt angle (realignment) of the pneumatic seed drill distributor head cover. We compared two qualitative parameters of seed sowing, coefficient of variation and coefficient of lateral unevenness of seed sowing (δ). Values were obtained on the test stand with an innovative deflector built into the distributor head at three angles of inclination (0°, 5° and 10°). Statistical analyses revealed a significant effect of airflow velocity and deflector angle, which corrects the deviation from the vertical plane of the distributor head, on the uniformity of seed sowing. In addition, regression equations were determined to predict the quality of the seed sowing process. The developed and manufactured innovative distributor head with a deflector that tilts in two planes, designed to improve the distribution evenness of the air stream transporting seed to individual coulters in pneumatic seed drills, received a positive review. The use of a deflector with automatic control of its position angle, correcting the deviation of the distributor head from a vertical plane in pneumatic seed drills improves the uniformity of seeding. Therefore, it is reasonable to use this solution for new pneumatic seed drills and those in use on soils with different relief (undulating surface). Moreover, the solution fits in with modern agricultural manufacturing in accordance with the ideas of precision agriculture. [ABSTRACT FROM AUTHOR]

This research paper delves into the longitudinal wind tunnel tests conducted on the 19-passengers aircraft model of the Italian PROSIB project. The concept is an innovative small air transport airplane with distributed propellers and hybrid-electric powerplant. The primary objective was to assess its stability and control characteristics in power-off conditions. In addition to the usual investigation of the aircraft components, the study introduced a belly-mounted pod, which served as a battery storage unit, and explored two distinct tail configurations: a body-mounted (low) tail and a T-tail (high). The results obtained from these tests generally confirmed the anticipated characteristics of the aircraft design. The experiments provided data on aerodynamic forces and moments, giving useful indications on the effects of a belly-mounted battery storage unit and tail layout on the aircraft stability and control characteristics. This information could be used by aircraft designers to size an airplane of the same class. [ABSTRACT FROM AUTHOR]

TCAS II is a rule-based airborne collision avoidance system (ACAS) that is used in current commercial air transport operations, and ACAS Xa is a new optimization-based system. Operational validation studies have mainly used deterministic simulations of ACAS performance using various sets of encounters. Recently a new approach was developed, which employs Monte Carlo (MC) simulation of agent-based models to evaluate the impact of sensor errors and pilot response variability. This paper contrasts the results of both approaches in a comparison of TCAS II and ACAS Xa for various types of synthetic encounters. It was found that conventional estimates of near mid-air collision (NMAC) probabilities are often lower than the estimates achieved using MC simulation, and that the biases in the P(NMAC) estimates are consistently larger for ACAS Xa than for TCAS II. Contributions to unresolved risk are largest for pilot performance, then for encounter types, and finally for sensor errors. The contribution of non-responding pilots is much larger than the differences between TCAS II and ACAS Xa. It is concluded that the agent-based MC simulation overcomes the limitations in traditional evaluation of altimetry errors and pilot response, providing an independent means to effectively analyze the robustness of ACASs. [ABSTRACT FROM AUTHOR]

An airport's terminal area is the bottleneck of the air transport system. Convective weather can seriously affect the normal flight status of arrival and departure flights. At present, pilots take different flight operation strategies to avoid convective weather based on onboard radar, visual information, adverse weather experience, etc. This paper studies trajectory clustering based on the OPTICS algorithm to obtain the arrival of typical flight routes in the terminal area. Based on weather information of the planned typical flight route and flight plan information, Random Forest (RF), K-nearest Neighbor KNN (KNN), and Support Vector Machines (SVM) algorithms were used for training and establishing the Arrival Flight Operation Strategy Prediction Model (AFOSPM). In this paper, case studies of historical arrival flights in the Guangzhou (ZGGG) and Wuhan (ZHHH) terminal area were carried out. The results show that trajectory clustering results based on the OPTICS algorithm can more accurately reflect the regular flight routes of arrival flights in a terminal area. Compared to KNN and SVM, the prediction accuracy of AFOSPM based on RF is better, reaching more than 88%. On this basis, six features—including 90% VIL, weather coverage, weather duration, planned route, max VIL, and planned Arrival Gate (AF)—were used as the input features for AFOSPM, which can effectively predict various arrival flight operation strategies. For the most frequently used arrival flight operation strategies under convective weather conditions—radar guidance, AF changing, and diversion strategy—the prediction accuracy of the ZGGG and ZHHH terminal areas can exceed 95%, 85%, and 80%, respectively. [ABSTRACT FROM AUTHOR]

As communications technology, air travel, and a complex international economy continue to make the world smaller, the importance of peaceful and cooperative relationships between nations increases. However, it is unclear to what extent research on international relations (IR) has expanded as a global discipline; narrated by balanced perspectives and provides an impact. This study conducts a bibliometric analysis of 4,986 documents related to IR as recorded in the Scopus database from 1913 to 2022. Specifically, this paper analyzes (a) the trends and developments; (b) influential documents and frequent keywords and (c) major players in terms of productive journals, authors and institutions in IR studies. This paper provides a new panoramic view through tables and science maps on the publication of IR studies. The findings show a gradual interest in the IR field before the Second World War and this accelerated during the mid-twentieth century. Political economy is gaining more importance and most publications centre on IR theories while discussing prevailing events affecting the world. However, the Western influence of IR is still primarily mainstream, where IR publications are mainly controlled by large Western publishers, influenced by Western authors affiliated with long-established Western institutions. Seemingly, the non-Western contributions to the IR field have yet to establish their own footing in the field despite much discussion about diversifying IR. This remains a challenge for non-Western scholars, journal publishers, and institutions seeking to contribute to the ongoing debate in the study of international relations. [ABSTRACT FROM AUTHOR]

Globalisation and intense market competition have affected the business environment of the 21st century. The changes have mainly occurred at the customer level, where expectations in terms of service quality have increased, whilst customer loyalty has not reached the same level of expectation. This change has also been felt in the passenger air transport industry, with passenger airlines increasing their efforts to identify and implement new ways of improving the quality of services they provide to customers. However, air transport, be it cargo or passenger, faces considerable challenges arising from the increasingly dynamic and uncertain environment in which it operates. This paper is part of an empirical study aimed at developing a model for measuring and analysing the quality of air passenger services in order to improve the quality of customer service. This paper therefore aims to present some important aspects of the influence of quality on customer satisfaction in a major international airline. [ABSTRACT FROM AUTHOR]

As a specific form of water transport that involves a simultaneous carriage of passengers and cargo, the function of a ferry to bridge one area to another is threatened by the fast growth of air transport, which is not only faster and more convenient but also often cheaper than traveling by ferry. The objective of this paper is to identify market expectations of ferry services and to identify the opportunity for ferry tourism development in Indonesia. This paper is a market survey of 103 ferry passengers in seven locations in Indonesia: Merak, Bakauheni, Bayuwangi, Bali, Batam, Labuan Bajo, and Lake Toba. Data analysis uses descriptive statistics to identify customers' top-of-mind opinions. The results show that the market prefers extended digital platforms to co-create their experience, both in ferry services and their trips, shortened route ferries to enrich their experience on multi-transportation facilities, while providing more entertainment and recreational facilities on longer routes, as well as instagrammable spots, both on the ferry or in the terminal. There are also collaboration opportunities with sports and other communities to cater to weekenders to create island-hopping events on weekends. The conclusion is that ferry operators should conduct market surveys periodically to understand their markets and their requirements to cope with the ever-changing marketplace. In addition, co-creating products with community customers and product development innovations is the solution to make ferry tourism relevant to current and future demands. [ABSTRACT FROM AUTHOR]

Multiplier effects play a major role in determining importance of a sector of interest to the national economy. In order to determine the significance of Croatian transport sectors, in this paper input-output analysis was applied. A comparative analysis of type I and type II output, gross value added and employment multipliers based on input-output tables for Croatian economy for the year 2010 and 2015 was performed. Type I multipliers were calculated based on the open IO model. Closed IO model was used in type II multipliers determination. Results indicate that sector code H49—Land transport services and transport services via pipelines and sector code H50—Water transport services in the year 2015 recorded lower type I and type II output, gross value added and employment multipliers compared to the year 2010. For sector code H51—Air transport services, significant growth in terms of all three economic indicators was detected, especially when interest is focused on type I and type II employment multipliers. Results presented in this paper could be valuable for academia and general public because they reflect multipliers estimation of transport sectors in Republic of Croatia for the first time based on sound macroeconomic analysis tool. [ABSTRACT FROM AUTHOR]

Traffic flow prediction is a significant component for the new generation intelligent transportation. In the field of air transportation, accurate prediction of airport flight flow can help airlines schedule flights and provide a decision-making basis for airport resource allocation. With the help of Deep Learning technology, this paper focuses on the characteristics of flight flow easily disturbed by environmental factors, studies the spatiotemporal dependence between flight flows, and predicts the spatiotemporal distribution of flight flows from the airport network level. We proposed a deep learning architecture named ATFSTNP, which combining the residual neural network (ResNet), graph convolutional network (GCN), and long short-term memory (LSTM). Based big data analytics of air traffic management, this method takes the spatiotemporal causal relationship between weather impact and flight flow as the core, and deeply mines the complex spatiotemporal relationship of flight flow. The model's methodologies are improved from the practical application level, and extensive experiments conducted on the China's flight operation dataset. The results illustrate that the improved model has significant advantages in predicting the flight flow under weather affect. Even in the complex and variable external environment, the model can still accurately predict the spatiotemporal distribution of the airport network flight flow, with strong robustness. [ABSTRACT FROM AUTHOR]

Generally, air track planning is conducted in real time and takes modified track distance minimization as objective. Next-generation air transport systems provide aircrafts with more flexibility in track planning and more responsibilities in self-separation, which present a great challenge for aircraft optimal track planning, especially in some high-density airspaces and some complex conflict scenarios. This paper proposes a novel aircraft track planning method by taking aircraft conflict probability into consideration. First, the concepts of aircraft potential motion space and the estimation method for aircraft conflict probability is introduced. Then, taking conflict probability minimization as the objective, the classical ant colony algorithm (ACA) algorithm is improved to solve the model. Finally, an experimental study is conducted to illustrate the proposed method. Results show that the proposed method is able to provide a scientific and effective track planning approach considering the potential conflict probability of aircrafts, which is able to provide fundamental to the safety of entire air transport system. [ABSTRACT FROM AUTHOR]