Hub-and-Spoke System in Air Transportation and Its Implications to Regional Economic Development——A Case Study of United States

Considerable changes have taken place in commercial passenger air transport since the enactment of the 1978 Airline Deregulation Act in the US and the deregulation of airline networks that has occurred elsewhere. The commercial and operational freedoms have led most of the larger carriers to develop hub-and-spoke networks, within which certain cities or metropolitan areas emerge as key nodes possessing tremendous advantages over other locations in the air transport system. This paper examines the nature of hub-and-spoke operations in air transportation services, and the benefits that accrue to a city or geographical region that is host to an airline hub. In particular, it looks into linkages between the air service hub and local economic development. Four potential types of impact of airports on the regional economy are defined and discussed. As an example, the assessment of the economic impacts of Cincinnati-Northern Kentucky International Airport (CVG), a major Delta Airlines hub, is introduced.

Network Aggregation Process in Multilayer Air Transportation Networks

The air transportation network, one of the common multilayer complex systems, is composed of a collection of individual airlines, and each airline corresponds to a different layer. An important question is then how many airlines are really necessary to represent the optimal structure of a multilayer air transportation system. Here we take the Chinese air transportation network （CATN） as an example to explore the nature of multiplex systems through the procedure of network aggregation. Specifically, we propose a series of structural measures to characterize the CATN from the multilayered to the aggregated network level. We show how these measures evolve during the network aggregation process in which layers are gradually merged together and find that there is an evident structural transition that happened in the aggregated network with nine randomly chosen airlines merged, where the network features and construction cost of this network are almost equivalent to those of the present CATN with twenty-two airlines under this condition. These findings could shed some light on network structure optimization and management of the Chinese air transportation system.

Air transportation in China: Temporal and spatial evolution and development forecasts

This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province＇s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows：（1） Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low.（2） Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others.（3） Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.

Medical transportation and the contribution of air medical evacuation in isolated mountainous areas of Greece-Case study,Municipality of Agrafa

In every emergency medical situation,access to emergency medical services is an inalienable right of any citizen.The average acceptable time to provide first aid assistance is 60 minutes.In this paper,the possibility of using helicopters for air travel in mountainous areas was examined for the first time for all of Greece and especially for a mountainous and isolated area such as the Municipality of Agrafa.Initially,the time distance-virtual distance,from the hospitals was calculated at the national level of Greece,with an acceptable first contact time of 60 minutes(golden hour),i.e.,less than two hours from the nearest hospital to the incident and back to the hospital and the relevant conclusions are drawn.Then,the case study of Municipality of Agrafa,one of the most mountainous areas in Greece,was examined.The time distance of the settlements from the nearest primary health point,namely the Primary Health Centre(PHC)of West Fragkista,was calculated and the transportation by ground means was compared with the corresponding time by flying means,to investigate the contribution of air transportation or not,of the timely arrival of the patients in the appropriate health structure.Finally,possible helicopter landing locations were identified,using a geographic information system to facilitate the process of air medical transportation in the Municipality of Agrafa.

Network science approach for identifying disruptive elements of an airline

Currently,flight delays are common and they propagate from an originating flight to connecting flights,leading to large disruptions in the overall schedule.These disruptions cause massive economic losses,affect airlines’reputations,waste passengers’time and money,and directly impact the environment.This study adopts a network science approach for solving the delay propagation problem by modeling and analyzing the flight schedules and historical operational data of an airline.We aim to determine the most disruptive airports,flights,flightconnections,and connection types in an airline network.Disruptive elements are influential or critical entities in an airline network.They are the elements that can either cause(airline schedules)or have caused(historical data)the largest disturbances in the network.An airline can improve its operations by avoiding delays caused by the most disruptive elements.The proposed network science approach for disruptive element analysis was validated using a case study of an operating airline.The analysis indicates that potential disruptive elements in a schedule of an airline are also actual disruptive elements in the historical data and they should be considered to improve operations.The airline network exhibits small-world effects and delays can propagate to any part of the network with a minimum of four delayed flights.Finally,we observed that passenger connections between flights are the most disruptive connection type.Therefore,the proposed methodology provides a tool for airlines to build robust flight schedules that reduce delays and propagation.

Analysis of the Chinese air route network as a complex network

The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network （CARN） within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network （CAN）. Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.

Prediction of Departure Aircraft Taxi Time Based on Deep Learning

With the continuous increase in the number of flights,the use of airport collaborative decision-making(ACDM)systems has been more and more widely spread.The accuracy of the taxi time prediction has an important effect on the A-CDM calculation of the departure aircraft’s take-off queue and the accurate time for the aircraft blockout.The spatial-temporal-environment deep learning(STEDL)model is presented to improve the prediction accuracy of departure aircraft taxi-out time.The model is composed of time-flow sub-model(airport capacity,number of taxiing aircraft,and different time periods),spatial sub-model(taxiing distance)and environmental sub-model(weather,air traffic control,runway configuration,and aircraft category).The STEDL model is used to predict the taxi time of departure aircraft at Hong Kong Airport and the results show that the STEDL method has a prediction accuracy of 95.4%.The proposed model also greatly reduces the prediction error rate compared with the other machine learning methods.

A Bilevel Programming Approach for Optimization of Airport Ground Movement

This paper proposes an optimization model for the airport ground movement problem(GMP)based on bilevel programming to address taxi conflicts on the airport ground and to improve the operating safety and efficiency.To solve GMP,an iterative heuristic algorithm is designed.Instead of separately investigating each problem,this model simultaneously coordinates and optimizes the aircraft routing and scheduling.A simulation test is conducted on Nanjing Lukou International Airport(NKG)and the results show that the bilevel programming model can clearly outperform the widely used first-come-first-service(FCFS)scheduling scheme in terms of aircraft operational time under the precondition of none conflict.The research effort demonstrates that with the reduced operating cost and the improved overall efficiency,the proposed model can assist operations of the airports that are facing increasing traffic demand and working at almost maximum capacity.

4-D Trajectory Prediction and Dynamic Planning of Aircraft Taxiing Considering Time and Fuel

Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed,and the optimization goal is the shortest taxi time.Although it is easy to solve,it does not consider the changes in the speed profile of the aircraft when turning,and the shortest taxi time does not necessarily bring the best taxi fuel consumption.In this paper,the number of turns is considered,and the improved A*algorithm is used to obtain the P static paths with the shortest sum of the straight-line distance and the turning distance of the aircraft as the feasible taxi paths.By balancing taxi time and fuel consumption,a set of Pareto optimal speed profiles are generated for each preselected path to predict the 4-D trajectory of the aircraft.Based on the 4-D trajectory prediction results,the conflict by the occupied time window in the taxiing area is detected.For the conflict aircraft,based on the priority comparison,the waiting or changing path is selected to solve the taxiing conflict.Finally,the conflict free aircraft taxiing path is generated and the area occupation time window on the path is updated.The experimental results show that the total taxi distance and turn time of the aircraft are reduced,and the fuel consumption is reduced.The proposed method has high practical application value and is expected to be applied in real-time air traffic control decision-making in the future.

An Air Route Planning Model of Unmanned Aerial Vehicles Under Constraints of Ground Safety

With the rapid growth of the number and flight time of unmanned aerial vehicles(UAVs),safety accidents caused by UAVs flight risk is increasing gradually.Safe air route planning is an effective means to reduce the operational risk of UAVs at the strategic level.The optimal air route planning model based on ground risk assessment is presented by considering the safety cost of UAV air route.Through the rasterization of the ground surface under the air route,the safety factor of each grid is defined with the probability of fatality on the ground per flight hour as the quantitative index.The air route safety cost function is constructed based on the safety factor of each grid.Then,the total cost function considering both air route safety and flight distance is established.The expected function of the ant colony algorithm is rebuilt and used as the algorithm to plan the air routes.The effectiveness of the new air route planning model is verified through the logistical distribution scenario on urban airspace.The results indicate that the new air route planning model considering safety factor can greatly improve the overall safety of air route under small increase of the total flight time.

Multi-objective Collaborative Optimization for Scheduling Aircraft Landing on Closely Spaced Parallel Runways Based on Genetic Algorithms

A scheduling model of closely spaced parallel runways for arrival aircraft was proposed,with multi-objections of the minimum flight delay cost,the maximum airport capacity,the minimum workload of air traffic controller and the maximum fairness of airlines′scheduling.The time interval between two runways and changes of aircraft landing order were taken as the constraints.Genetic algorithm was used to solve the model,and the model constrained unit delay cost of the aircraft with multiple flight tasks to reduce its delay influence range.Each objective function value or the fitness of particle unsatisfied the constrain condition would be punished.Finally,one domestic airport hub was introduced to verify the algorithm and the model.The results showed that the genetic algorithm presented strong convergence and timeliness for solving constraint multi-objective aircraft landing problem on closely spaced parallel runways,and the optimization results were better than that of actual scheduling.

Homogeneity Analysis of Multiairport System Based on Airport Attributed Network Representation Learning

The homogeneity analysis of multi-airport system can provide important decision-making support for the route layout and cooperative operation.Existing research seldom analyzes the homogeneity of multi-airport system from the perspective of route network analysis,and the attribute information of airport nodes in the airport route network is not appropriately integrated into the airport network.In order to solve this problem,a multi-airport system homogeneity analysis method based on airport attribute network representation learning is proposed.Firstly,the route network of a multi-airport system with attribute information is constructed.If there are flights between airports,an edge is added between airports,and regional attribute information is added for each airport node.Secondly,the airport attributes and the airport network vector are represented respectively.The airport attributes and the airport network vector are embedded into the unified airport representation vector space by the network representation learning method,and then the airport vector integrating the airport attributes and the airport network characteristics is obtained.By calculating the similarity of the airport vectors,it is convenient to calculate the degree of homogeneity between airports and the homogeneity of the multi-airport system.The experimental results on the Beijing-Tianjin-Hebei multi-airport system show that,compared with other existing algorithms,the homogeneity analysis method based on attributed network representation learning can get more consistent results with the current situation of Beijing-Tianjin-Hebei multi-airport system.

Collaboration Optimization of Flight Schedule in Beijing⁃Tianjin⁃Hebei Airport Group

The coordinated and integrated development of regional airport group system has been identified as an important research topic in the field of air traffic management in China.However,due to the clear limitation on airspace resources and severe traffic congestion,it is necessary to further study the problem of flight schedule coordination optimization for airport clusters.We take the Beijing-Tianjin-Hebei airport Group as an example and construct an optimization model of flight schedule with the minimum adjustment and delay.The design of the implementation algorithm is proposed.As demonstrated by the simulation results,the flight delay in the Beijing-Tianjin-Hebei multi-airport system is noticeably reduced by applying both the optimization model and the algorithm proposed in this paper.

Comparison on Vulnerability of European and Chinese Air Transport Networks under Spatial Hazards

European air transport network(EATN)and Chinese air transport network(CATN),as two important air transport systems in the world,are facing increasingly spatial hazards,such as extreme weathers and natural disasters. In order to reflect and compare impact of spatial hazards on the two networks in a practical way,a new spatial vulnerability model(SVM)is proposed in this paper,which analyzes vulnerability of a network system under spatial hazards from the perspectives of network topology and characteristics of hazards. Before introduction of the SVM,two abstract networks for EATN and CATN are established with a simple topological analysis by traditional vulnerability method. Then,the process to study vulnerability of an air transport network under spatial hazards by SVM is presented. Based on it,a comparative case study on EATN and CATN under two representative spatial hazard scenarios,one with an even spatial distribution,named as spatially uniform hazard,and the other with an uneven spatial distribution that takes rainstorm hazard as an example,is conducted. The simulation results show that both of EATN and CATN are robust to spatially uniform hazard,but vulnerable to rainstorm hazard. In the comparison of the results of the two networks that only stands from the points of network topology and characteristics of hazard without considering certain unequal factors,including airspace openness and flight safety importance in Europe and China,EATN is more vulnerable than CATN under rainstorm hazard. This suggests that when the two networks grow to a similar developed level in future,EATN needs to pay more attention to the impact of rainstorm hazard.

Airport Aviation Noise Prediction Based on an Optimized Neural Network

In order to alleviate noise pollution and improve the sustainability of airport operation,it is of great significance to develop an effective method to predict airport aviation noise. A three-layer neural network is constructed to gain computational simplicity and execution economy. With the preferred node number and transfer functions obtained in comparative tests,the constructed network is further optimized through the genetic algorithm for performance improvements in prediction. Results show that the proposed model in this paper is superior in accuracy and stability for airport aviation noise prediction,contributing to the assessment of future environmental impact and further improvement of operational sustainability for civil airports.

Seasonal Variations of Terrestrial OC Sources in Aerosols over the East China Sea: The Influence of Long-Range Air Mass Transport

Aerosols represent an important source of terrestrial organic carbon(OC)from the East Asian continent to the China marginal seas,thus their provenance and transport play important roles in the global carbon cycle.Fifty samples of total suspended particle were collected seasonally from the nearshore Huaniao Island(HNI)in East China Sea(ECS)from April 2018 to January 2019;and they were analyzed for total organic carbon(TOC)content and stable carbon isotope(δ^(13)C),as well as terrestrial bio-markers including n-alkanes(C_(20)-C_(33)),n-alkanols(C_(20)-C32)and n-fatty acids(n-FAs,C_(20)-C30),to distinguish the seasonal variabili-ties of terrestrial OC sources and reveal the influence of the long-range air mass transport on these sources.The TOC-δ^(13)C values(range from−27.3‰to−24.3‰)and molecular distributions of terrestrial biomarkers both suggested that terrestrial OC contribu-tions to aerosols had significant seasonal variations.The source indices of terrestrial biomarkers(e.g.,Fossil%=82.8%for n-alkanes)revealed that the fossil fuel OC contributions,including coal burning and vehicular emission,were higher in winter,mainly because of the long-range air mass transport from the north of the East Asian continent.The terrestrial plant OC contributions were higher in summer(e.g.,Wax%=32.4%for n-alkanes),likely due to local vegetation sources from HNI and East Asian continental air masses.Cluster analysis of air mass backward-trajectories clearly showed that transport pathway plays an important role in determining the organic constituents of aerosols in China marginal seas.A comparison of these terrestrial OC contributions from different air mass origins suggested that fossil fuel OC showed less variations among various air mass origins from northern China in winter,while terrestrial plant OC sources from northern and southern China in summer contributed more than that from the air masses transported through the ECS.These results provided a basis for future quantification of terrestrial OC from different origins in marine aerosols,by combining biomarker index and carbon isotopes.

Mass Tourism and Air Transport, an Inevitable Relationship： The Case of Canary Islands

The tourist industry, as global mass phenomenon, is inextricably linked to the evolution of air transport systems and air carriers, in turn, depends on tourism to ensure stability in routes and prices. Therefore, both sectors must face the new challenges together, the transport industry is heading a problem of energy and cost overruns, that inevitably will affect tourism in the short term. The first energy crisis that they are starting to live, has been mitigated by changes in three parameters： （1） the international regulation of commercial aviation; （2） the connectivity and business （birth of low cost companies） models; and （3） the new policies for climate change and gas emission. So far, the rapid growth of the tourist industry has being held on a fast and cheap access to transport energy resources based on the false belief of unlimited access to energy. The article is a review of the state of the art, and the research papers published on air transportation, relating to tourism and the emergence of low cost airlines, in order to give a global vision for the decision makers of mass destinations, as it is the case of the Canary Islands that we will use as a reference.

An Analysis of the Air Parcel Trajectories of Long-Range Transport at Shanghai

1.INTRODUCTION Acid rain observations show that acid cloud water in Shanghai region appears not only

Factor Analysis on Industrial International Competitiveness： An Empirical Study on China Air Transport Industry

After China＇s entry into WTO, our industries will be confronted with fiercer competition. How to strengthen their international competitiveness to seek for survival and development has become a very urgent problem. This paper first simply discusses the meaning and theo^es of industrial international competitiveness, then chooses proper indexes according to some principles, explains the factor analysis method of industrial international competitiveness, and finally makes empirical analysis on China air transport industry.

Regulations of Business Licensing for Route of Foreign Air Transport Enterprises

Regulations of Busi- ness Licensing for Route of Foreign Air Transport Enterprises(CCAR- 287),which were passed at the executive meeting of Civil Aviation Ad- ministration of China on May 19,2008,were hereby promulgated and became effective as of July 11,2008.