The air traffic management(ATM)system is an intelligent system,which integrates the ground computer network,airborne network and space satellite(communication and navigation)network by the ground-air data link system....The air traffic management(ATM)system is an intelligent system,which integrates the ground computer network,airborne network and space satellite(communication and navigation)network by the ground-air data link system.Due to the openness and widely distribution of ATM system,the trust relationship of all parties in the system is pretty complex.At present,public key infrastructure(PKI)based identity authentication method is more and more difficult to meet the growing demand of ATM service.First,through the analysis of the organizational structure and operation mode of ATM system,this paper points out the existing identity authentication security threats in ATM system,and discusses the advantages of adopting blockchain technology in ATM system.Further,we briefly analyze some shortcomings of the current PKI-based authentication system in ATM.Particularly,to address the authentication problem,this paper proposes and presents a trusted ATM Security Authentication Model and authentication protocol based on blockchain.Finally,this paper makes a comprehensive analysis and simulation of the proposed security authentication scheme,and gets the expected effect.展开更多
The air traffic management system(ATM)has the task of ensuring safe,orderly and expeditious flow of air traffic.The ATM system architecture is very much dependent on the concept of operations(ConOps).Over the years th...The air traffic management system(ATM)has the task of ensuring safe,orderly and expeditious flow of air traffic.The ATM system architecture is very much dependent on the concept of operations(ConOps).Over the years the evolution in ConOps has resulted in changes in the ATM′s physical architecture,improving its physical infrastructure,increasing the levels of automation and making operational changes to improve air traffic flow,to cope with increasing demand for air travel.However,what is less clear is the impact of such changes in ConOps on the ATM′s functional architecture.This is vital for ensuring optimality in the implementation of the physical architecture components to support the ATM functions.This paper reviews the changes in the ConOps over the years,proposes a temporally invariant ATM functional model,and discusses some of the main key technologies expected to make significant improvements to the ATM system.展开更多
Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the opera...Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the operational efficiency of air transport systems. Thus,objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment,and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary,we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast,the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models,we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.展开更多
The main objective of this study is to evaluate the effectiveness of using active traffic management （ATM） strategies on freeways in terms of the driver＇s behavior and operational impacts. A few test beds were sele...The main objective of this study is to evaluate the effectiveness of using active traffic management （ATM） strategies on freeways in terms of the driver＇s behavior and operational impacts. A few test beds were selected to evaluate the impacts of ATM such as speed harmonization, shoulder utilization, and ramp metering. Test beds used in this study were at places where an ATM is either proposed or previously implemented, i.e., where data exists for condi- tions prior to and after the implementation of ATM. Data collected from the test beds were used in a simulation model to evaluate the impacts of each ATM strategy on speed, travel time, and crash rates. Simulation results indicated that the implementation of speed harmonization on US 90 showed a 14% reduction in crashes and a 2%-3% increase in freeway speed; the implementation of hard shoulders on US 90 showed a 39% increase in travel time, 22% increase in freeway capacity and 60% decrease in delays; and the implementation of ramp metering on US 59 between Bissonnet St. and Fondern road showed a decrease of 23 % in freeway travel time, a 14% increase in freeway speed and 11% decrease in accident rates.展开更多
This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)f...This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.展开更多
In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of ...In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of arrival and departure flights is studied systematically.According to the matching degree of capacity and flow,it is determined that the traffic state of arrival/departure operation in a certain period is peak or off-peak.The demands of all parties in each traffic state are analyzed,and the mathematical models of arrival/departure flight scheduling in each traffic state are established.Aiming at the four kinds of joint operation traffic scenarios of arrival and departure,the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established,respectively,and the elitism genetic algorithm is designed to solve the models.The results show that:Compared with the first-come-firstserved method,in the scenarios of arrival peak&departure off-peak and arrival peak&departure peak,the departure flight equilibrium satisfaction is improved,and the runway occupation time of departure flight flow is reduced by 38.8%.In the scenarios of arrival off-peak&departure off-peak and departure peak&arrival off-peak,the arrival flight equilibrium delay time is significantly reduced,the departure flight equilibrium satisfaction is improved by 77.6%,and the runway occupation time of departure flight flow is reduced by 46.6%.Compared with other four kinds of strategies,the optimal scheduling method can better balance fairness and efficiency,so the scheduling results are more reasonable.展开更多
In order to improve the accuracy and stability of terminal traffic flow prediction in convective weather,a multi-input deep learning(MICL)model is proposed.On the basis of previous studies,this paper expands the set o...In order to improve the accuracy and stability of terminal traffic flow prediction in convective weather,a multi-input deep learning(MICL)model is proposed.On the basis of previous studies,this paper expands the set of weather characteristics affecting the traffic flow in the terminal area,including weather forecast data and Meteorological Report of Aerodrome Conditions(METAR)data.The terminal airspace is divided into smaller areas based on function and the weather severity index(WSI)characteristics extracted from weather forecast data are established to better quantify the impact of weather.MICL model preserves the advantages of the convolution neural network(CNN)and the long short-term memory(LSTM)model,and adopts two channels to input WSI and METAR information,respectively,which can fully reflect the temporal and spatial distribution characteristics of weather in the terminal area.Multi-scene experiments are designed based on the real historical data of Guangzhou Terminal Area operating in typical convective weather.The results show that the MICL model has excellent performance in mean squared error(MSE),root MSE(RMSE),mean absolute error(MAE)and other performance indicators compared with the existing machine learning models or deep learning models,such as Knearest neighbor(KNN),support vector regression(SVR),CNN and LSTM.In the forecast period ranging from 30 min to 6 h,the MICL model has the best prediction accuracy and stability.展开更多
Air traffic controllers are the important parts of air traffic management system who are responsible for the safety and efficiency of the system.They make traffic management decisions based on information acquired fro...Air traffic controllers are the important parts of air traffic management system who are responsible for the safety and efficiency of the system.They make traffic management decisions based on information acquired from various sources.The understanding of their information seeking behaviors is still limited.We aim to identify controllers′ behavior through the examination of the correlations between controllers′eye movements and air traffic.Sixteen air traffic controllers were invited to participate real-time simulation experiments,during which the data of their eye ball movements and air traffic were recorded.Tweny-three air traffic complexity metrics and six eye movements metrics were calculated to examine their relationships.Two correlational methods,Pearson′s correlation and Spearman′s correlation,were tested between every eye-traffic pair of metrics.The results indicate that controllers′two kinds of information-seeking behaviors can be identified from their eye movements:Targets tracking,and confliction recognition.The study on controllers′ eye movements may contribute to the understanding of information-seeking mechanisms leading to the development of more intelligent automations in the future.展开更多
A simulation network model was established using VISSIM software and verified by the T- test. The model took into consideration the road conditions, pedestrian crossing, traffic composi- tion, bus stops and traffic si...A simulation network model was established using VISSIM software and verified by the T- test. The model took into consideration the road conditions, pedestrian crossing, traffic composi- tion, bus stops and traffic signal. The operating characteristics of buses and cars under different flow conditions were studied using the simulation model, and the speed-flow models of buses and cars were established based on the simulation results. Finally, the threshold values of traffic flow for the provision of exclusive bus lanes was determined with the target of optimal travel benefits （per capi- ta） , which would provide a basis for the planning and design of exclusive bus lanes on urban roads.展开更多
Travel time estimation is an integral part of Intelligent Transportation Systems, and has been an important component in traffic management and operations for many years. Travel time, being spatial in nature, requires...Travel time estimation is an integral part of Intelligent Transportation Systems, and has been an important component in traffic management and operations for many years. Travel time, being spatial in nature, requires spatial sensors to measure it accurately. Bluetooth is emerging as a promising technology for the direct measurement of travel time, and is reported in a few studies from homogenous traffic conditions. At the same time, there have been no studies on the applicability of Bluetooth for travel time estimation in heterogeneous traffic seen in Istanbul and even that Turkey. Bluetooth data collected from a busy urban road in Istanbul city have been analyzed and the penetration rate was found to be about 5 %. Two wheelers and light motor vehicles have been detected using the Bluetooth sensor and the data have been extrapolated to estimate travel times of other classes of vehicles. The study developed linear relationships between speeds of different classes of vehicles through weighted linear regression methods and were used for the estimation of stream travel time. The results obtained were promising and show that Bluetooth is a cost-effective technology for estimation of travel time for heterogeneous traffic conditions.展开更多
In the performance based navigation（PBN）,the flight technical error（FTE）and the navigation system error（NSE）are two main parts of total system error（TSE）.The implementation of PBN requires pre-flight predictio...In the performance based navigation（PBN）,the flight technical error（FTE）and the navigation system error（NSE）are two main parts of total system error（TSE）.The implementation of PBN requires pre-flight prediction and en-route short-term dynamical prediction of TSE.Once the sum of predicted FTE and NSE is greater than the specified PBN value,PBN cannot operate.Thus,it requires accurate modeling and thorough analysis of the two main contributors.Multiple-input multiple-output（MIMO）longitudinal flight control system of ARIC model is designed using the linear quadratic Gaussian and loop transfer recovery（LQG/LTR）method,and FTE in symmetrical plane of aircraft is analyzed during the turbulence disturbed approach.The error estimation mapping function of FTE in symmetrical plane and its bound estimation model are proposed based on the singular value theory.The model provides an approach based on the forming mechanism of FTE,rather than the costly flight test and the data fitting.Real-data based simulation validates the theoretical analysis of FTE in symmetrical plane.It also shows that FTE is partially caused by the turbulence fluctuation disturbance when the automatic flight control system（AFCS）is engaged and increases with escalating the environmental turbulence intensity.展开更多
Airway networks are the basic carriers of air traffic.Characterizing airway networks will significantly improve the operating efficiency of aviation.This study is targeted at the airway network composed of 1479 waypoi...Airway networks are the basic carriers of air traffic.Characterizing airway networks will significantly improve the operating efficiency of aviation.This study is targeted at the airway network composed of 1479 waypoints in 2018 of China.Together with spatial structures,traffic flow characteristics,and the dominating traffic flow,four airway network models are constructed from the perspective of complex networks,including physical airway network,airway traffic network,directed airway traffic network,and dominance-based directed airway traffic network.Then the topological characteristics of different networks are statistically analyzed by using typical network measure indices,and the differences of these indices among different networks are investigated.Thereby,composite indices are proposed.Statistical results show that the airway network under the influence of traffic flows exhibits richer heterogeneity and asymmetrical between-node relationship,and the distributions of indices among different networks are significantly different.Comparative analysis of composite indices and traffic flows show that some waypoints yield great results in multiple composite indices and traffic volumes;some waypoints display large results in multiple composite indices but low traffic flows,and other waypoints only perform well in certain composite indices.The importance levels of waypoints are divided,by the K-means method based on degree composite index,betweenness composite index and closeness composite index,into three levels,and the reasonableness of clustering results is validated by the statistical results of traffic flows,airport number,and flight delay.展开更多
A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport s...A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport system is defined through in-depth analysis of the characteristics of arrival and departure operations.Then,several constraints are taken into account,such as wake vortex separation,transfer separation,release separation,and separation in different runway operational modes.Furthermore,the scheduling model is constructed and simulated annealing algorithm is proposed by minimizing the total delay.Finally,Shanghai multi-airport system is chosen to conduct the simulation and validation.And the simulation results indicate that the proposed method is able to effectively improve the efficiency of arrival and departure operations for multi-airport system.展开更多
During railway operations,trains normally run as scheduled,but the occurrence of unexpected events will disrupt traffic flow and cause train deviation from the original timetable.In order to assist dispatchers in resc...During railway operations,trains normally run as scheduled,but the occurrence of unexpected events will disrupt traffic flow and cause train deviation from the original timetable.In order to assist dispatchers in rescheduling trains,this paper introduces an innovative Human-Computer Interaction framework.This framework enables train dispatchers to propose different timetable adjustment instructions to the original or adjusted timetable.These instructions will be processed,stored,analyzed,and digested by computer program,which finally lead to the modification and calculation of the embedded mathematical model,then a new adjusted timetable will be produced and provided to dispatchers for checking and modifying.This framework can iterate for unlimited times based on dispatchers'intentions,until the final results satisfy them.A demonstration system named RTARS(Real-time Timetable Automatic Rescheduling System)is developed based on this framework and it has been applied in Beijing Railway Administration,which shows its effectiveness in reality.展开更多
In order to obtain accurate conflict risks in terminal airspace design,the concept and calculation model of potential conflict frequency for intersected routes are proposed.Conflict frequency is represented by the pro...In order to obtain accurate conflict risks in terminal airspace design,the concept and calculation model of potential conflict frequency for intersected routes are proposed.Conflict frequency is represented by the product of horizontal conflict frequency and vertical conflict probability.The horizontal conflict frequency is derived from the probability density distribution of conflicts in a period of time.Based on the recorded radar trajectory data,the concept and model of ROUTE distance are proposed,and the probability density function of aircraft height at a specified ROUTE distance is deduced by kernel density estimation.Furthermore,vertical conflict probability and its horizontal distribution are achieved.Examples of three intersected arrival and departure route design schemes are studied.Compared with scheme 1,the conflict frequency values of the other two improved schemes decrease to53% and 24%,respectively.The results show that the model can quantify potential conflict frequency of intersected routes.展开更多
A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers(ATCOs)with decision support. For arrival pattern recognition,a clustering-based method is proposed to ...A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers(ATCOs)with decision support. For arrival pattern recognition,a clustering-based method is proposed to cluster arrival patterns by control intentions. For arrival pattern prediction,two predictors are trained to estimate the most possible command issued by the ATCOs in a particular traffic situation. Training the arrival pattern predictor could be regarded as building an ATCOs simulator. The simulator can assign an appropriate arrival pattern for each arrival aircraft,just like real ATCOs do. Therefore,the simulator is considered to be able to provide effective advice for part of the work of ATCOs. Finally,a case study is carried out and demonstrates that the convolutional neural network(CNN)-based predictor performs better than the radom forest(RF)-based one.展开更多
As the air traffic demand is anticipated to be increased significantly in the near future,dynamic and effective allocation of the airspace resource is becoming a world-wide focus in the research field of air traffic m...As the air traffic demand is anticipated to be increased significantly in the near future,dynamic and effective allocation of the airspace resource is becoming a world-wide focus in the research field of air traffic management（ATM）.Taking the U.S.targeting the en-route airsapce,a dynamic airspace configuration（DAC） algorithm to reconfigure the airspace in consideration of higher efficiency and safety is presented.First,a modeling technique based on graph theory is proposed to generate a mathematical model for the airspace,and then,the graph model is partitioned into subgraphs for the purpose of sectorizatoin.The final step generates sector configuration with desirable geometry shape.Through analysis on the Cleveland airspace center（ZOB） in the U.S.,the algorithm is proved to be robust to time-varying traffic load.展开更多
Terminal airspace(TMA)is the airspace centering several military and civil aviation airports with complex route structure,limited airspace resources,traffic flow,difficult management and considerable airspace complexi...Terminal airspace(TMA)is the airspace centering several military and civil aviation airports with complex route structure,limited airspace resources,traffic flow,difficult management and considerable airspace complexity.A scientific and rational sectorization of TMA can optimize airspace resources,and sufficiently utilize the control of human resources to ensure the safety of TMA.The functional sectorization model was established based on the route structure of arriving and departing aircraft as well as controlling requirements.Based on principles of sectorization and topological relations within a network,the arrival and departure sectorization model was established,using tree based ant colony algorithm(ACO)searching.Shanghai TMA was taken as an example to be sectorizaed,and the result showed that this model was superior to traditional ones when arrival and departure routes were separated at dense airport terminal airspace.展开更多
Software Defined Networking(SDN) provides a flexible and convenient way to support fine-grained traffic-engineering(TE). Besides, SDN also provides better Quality of Experience(QoE) for customers. However, the policy ...Software Defined Networking(SDN) provides a flexible and convenient way to support fine-grained traffic-engineering(TE). Besides, SDN also provides better Quality of Experience(QoE) for customers. However, the policy of the evolution from legacy networks to the SDNs overemphasizes the controllability of the network or TE while ignoring the customers' benefit. Standing in the customers' position, we propose an optimization scheme, named as Optimal Migration Schedule based on Customers' Benefit(OMSB), to produce an optimized migration schedule and maximize the benefit of customers. Not only the quality and quantity of paths availed by migration, but also the number of flows from the customers that can use these multi-paths are taken into consideration for the scheduling. We compare the OMSB with other six migration schemes in terms of the benefit of customers. Our results suggest that the sequence of the migration plays a vital role for customers, especially in the early stages of the network migration to the SDN.展开更多
基金This work was supported in part by the National Key R&D Program of China(No.2022YFB3904503)National Natural Science Foundation of China(No.62172418).
文摘The air traffic management(ATM)system is an intelligent system,which integrates the ground computer network,airborne network and space satellite(communication and navigation)network by the ground-air data link system.Due to the openness and widely distribution of ATM system,the trust relationship of all parties in the system is pretty complex.At present,public key infrastructure(PKI)based identity authentication method is more and more difficult to meet the growing demand of ATM service.First,through the analysis of the organizational structure and operation mode of ATM system,this paper points out the existing identity authentication security threats in ATM system,and discusses the advantages of adopting blockchain technology in ATM system.Further,we briefly analyze some shortcomings of the current PKI-based authentication system in ATM.Particularly,to address the authentication problem,this paper proposes and presents a trusted ATM Security Authentication Model and authentication protocol based on blockchain.Finally,this paper makes a comprehensive analysis and simulation of the proposed security authentication scheme,and gets the expected effect.
文摘The air traffic management system(ATM)has the task of ensuring safe,orderly and expeditious flow of air traffic.The ATM system architecture is very much dependent on the concept of operations(ConOps).Over the years the evolution in ConOps has resulted in changes in the ATM′s physical architecture,improving its physical infrastructure,increasing the levels of automation and making operational changes to improve air traffic flow,to cope with increasing demand for air travel.However,what is less clear is the impact of such changes in ConOps on the ATM′s functional architecture.This is vital for ensuring optimality in the implementation of the physical architecture components to support the ATM functions.This paper reviews the changes in the ConOps over the years,proposes a temporally invariant ATM functional model,and discusses some of the main key technologies expected to make significant improvements to the ATM system.
基金supported by the National Natural Science Foundation of China (Nos.U1833103, 71801215, U1933103)the Fundamental Research Funds for the Central Universities (No.3122019129)。
文摘Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the operational efficiency of air transport systems. Thus,objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment,and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary,we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast,the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models,we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.
文摘The main objective of this study is to evaluate the effectiveness of using active traffic management （ATM） strategies on freeways in terms of the driver＇s behavior and operational impacts. A few test beds were selected to evaluate the impacts of ATM such as speed harmonization, shoulder utilization, and ramp metering. Test beds used in this study were at places where an ATM is either proposed or previously implemented, i.e., where data exists for condi- tions prior to and after the implementation of ATM. Data collected from the test beds were used in a simulation model to evaluate the impacts of each ATM strategy on speed, travel time, and crash rates. Simulation results indicated that the implementation of speed harmonization on US 90 showed a 14% reduction in crashes and a 2%-3% increase in freeway speed; the implementation of hard shoulders on US 90 showed a 39% increase in travel time, 22% increase in freeway capacity and 60% decrease in delays; and the implementation of ramp metering on US 59 between Bissonnet St. and Fondern road showed a decrease of 23 % in freeway travel time, a 14% increase in freeway speed and 11% decrease in accident rates.
文摘This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.
基金supported by Nanjing University of Aeronautics and Astronautics Graduate Innovation Base(Laboratory)Open Fund(No.kfjj20200717).
文摘In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of arrival and departure flights is studied systematically.According to the matching degree of capacity and flow,it is determined that the traffic state of arrival/departure operation in a certain period is peak or off-peak.The demands of all parties in each traffic state are analyzed,and the mathematical models of arrival/departure flight scheduling in each traffic state are established.Aiming at the four kinds of joint operation traffic scenarios of arrival and departure,the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established,respectively,and the elitism genetic algorithm is designed to solve the models.The results show that:Compared with the first-come-firstserved method,in the scenarios of arrival peak&departure off-peak and arrival peak&departure peak,the departure flight equilibrium satisfaction is improved,and the runway occupation time of departure flight flow is reduced by 38.8%.In the scenarios of arrival off-peak&departure off-peak and departure peak&arrival off-peak,the arrival flight equilibrium delay time is significantly reduced,the departure flight equilibrium satisfaction is improved by 77.6%,and the runway occupation time of departure flight flow is reduced by 46.6%.Compared with other four kinds of strategies,the optimal scheduling method can better balance fairness and efficiency,so the scheduling results are more reasonable.
基金supported by the Civil Aviation Safety Capacity Building Project.
文摘In order to improve the accuracy and stability of terminal traffic flow prediction in convective weather,a multi-input deep learning(MICL)model is proposed.On the basis of previous studies,this paper expands the set of weather characteristics affecting the traffic flow in the terminal area,including weather forecast data and Meteorological Report of Aerodrome Conditions(METAR)data.The terminal airspace is divided into smaller areas based on function and the weather severity index(WSI)characteristics extracted from weather forecast data are established to better quantify the impact of weather.MICL model preserves the advantages of the convolution neural network(CNN)and the long short-term memory(LSTM)model,and adopts two channels to input WSI and METAR information,respectively,which can fully reflect the temporal and spatial distribution characteristics of weather in the terminal area.Multi-scene experiments are designed based on the real historical data of Guangzhou Terminal Area operating in typical convective weather.The results show that the MICL model has excellent performance in mean squared error(MSE),root MSE(RMSE),mean absolute error(MAE)and other performance indicators compared with the existing machine learning models or deep learning models,such as Knearest neighbor(KNN),support vector regression(SVR),CNN and LSTM.In the forecast period ranging from 30 min to 6 h,the MICL model has the best prediction accuracy and stability.
基金supported by the National Natural Science Foundation of China (No.61304190)the Fundamental Research Funds for the Central Universities (No.NJ20150030)the Natural Science Foundation of Jiangsu Province of China (No.BK20130818)
文摘Air traffic controllers are the important parts of air traffic management system who are responsible for the safety and efficiency of the system.They make traffic management decisions based on information acquired from various sources.The understanding of their information seeking behaviors is still limited.We aim to identify controllers′ behavior through the examination of the correlations between controllers′eye movements and air traffic.Sixteen air traffic controllers were invited to participate real-time simulation experiments,during which the data of their eye ball movements and air traffic were recorded.Tweny-three air traffic complexity metrics and six eye movements metrics were calculated to examine their relationships.Two correlational methods,Pearson′s correlation and Spearman′s correlation,were tested between every eye-traffic pair of metrics.The results indicate that controllers′two kinds of information-seeking behaviors can be identified from their eye movements:Targets tracking,and confliction recognition.The study on controllers′ eye movements may contribute to the understanding of information-seeking mechanisms leading to the development of more intelligent automations in the future.
基金Supported by the National High Technology Research and Development Program of China("863"Program)(2011AA110304)
文摘A simulation network model was established using VISSIM software and verified by the T- test. The model took into consideration the road conditions, pedestrian crossing, traffic composi- tion, bus stops and traffic signal. The operating characteristics of buses and cars under different flow conditions were studied using the simulation model, and the speed-flow models of buses and cars were established based on the simulation results. Finally, the threshold values of traffic flow for the provision of exclusive bus lanes was determined with the target of optimal travel benefits （per capi- ta） , which would provide a basis for the planning and design of exclusive bus lanes on urban roads.
文摘Travel time estimation is an integral part of Intelligent Transportation Systems, and has been an important component in traffic management and operations for many years. Travel time, being spatial in nature, requires spatial sensors to measure it accurately. Bluetooth is emerging as a promising technology for the direct measurement of travel time, and is reported in a few studies from homogenous traffic conditions. At the same time, there have been no studies on the applicability of Bluetooth for travel time estimation in heterogeneous traffic seen in Istanbul and even that Turkey. Bluetooth data collected from a busy urban road in Istanbul city have been analyzed and the penetration rate was found to be about 5 %. Two wheelers and light motor vehicles have been detected using the Bluetooth sensor and the data have been extrapolated to estimate travel times of other classes of vehicles. The study developed linear relationships between speeds of different classes of vehicles through weighted linear regression methods and were used for the estimation of stream travel time. The results obtained were promising and show that Bluetooth is a cost-effective technology for estimation of travel time for heterogeneous traffic conditions.
基金Supported by the National Basic Research Program of China("973"Program)(2010CB731805)theFoundation for Innovative Research Groups of the National Natural Science Foundation of China(60921001)+1 种基金the National Key Technologies R&D Program of China(2011BAH24B02)the Basic Scientific Research Fundation of Central Institutions of Higher Education(ZXH2009D006)~~
文摘In the performance based navigation（PBN）,the flight technical error（FTE）and the navigation system error（NSE）are two main parts of total system error（TSE）.The implementation of PBN requires pre-flight prediction and en-route short-term dynamical prediction of TSE.Once the sum of predicted FTE and NSE is greater than the specified PBN value,PBN cannot operate.Thus,it requires accurate modeling and thorough analysis of the two main contributors.Multiple-input multiple-output（MIMO）longitudinal flight control system of ARIC model is designed using the linear quadratic Gaussian and loop transfer recovery（LQG/LTR）method,and FTE in symmetrical plane of aircraft is analyzed during the turbulence disturbed approach.The error estimation mapping function of FTE in symmetrical plane and its bound estimation model are proposed based on the singular value theory.The model provides an approach based on the forming mechanism of FTE,rather than the costly flight test and the data fitting.Real-data based simulation validates the theoretical analysis of FTE in symmetrical plane.It also shows that FTE is partially caused by the turbulence fluctuation disturbance when the automatic flight control system（AFCS）is engaged and increases with escalating the environmental turbulence intensity.
基金This work was supported by the National Natural Science Foundations of China(Nos.U1833103,71801215,and U1933103)。
文摘Airway networks are the basic carriers of air traffic.Characterizing airway networks will significantly improve the operating efficiency of aviation.This study is targeted at the airway network composed of 1479 waypoints in 2018 of China.Together with spatial structures,traffic flow characteristics,and the dominating traffic flow,four airway network models are constructed from the perspective of complex networks,including physical airway network,airway traffic network,directed airway traffic network,and dominance-based directed airway traffic network.Then the topological characteristics of different networks are statistically analyzed by using typical network measure indices,and the differences of these indices among different networks are investigated.Thereby,composite indices are proposed.Statistical results show that the airway network under the influence of traffic flows exhibits richer heterogeneity and asymmetrical between-node relationship,and the distributions of indices among different networks are significantly different.Comparative analysis of composite indices and traffic flows show that some waypoints yield great results in multiple composite indices and traffic volumes;some waypoints display large results in multiple composite indices but low traffic flows,and other waypoints only perform well in certain composite indices.The importance levels of waypoints are divided,by the K-means method based on degree composite index,betweenness composite index and closeness composite index,into three levels,and the reasonableness of clustering results is validated by the statistical results of traffic flows,airport number,and flight delay.
基金supported by the National Natural Science Foundation of China(No.71401072)the National Natural Science Foundation of Jiangsu Province(No.BK20130814)the Foundation of Jiangsu Innovation Program for Graduate Education(the Fundamental Research Funds for the Central Universities,No.SJLX15_0128)
文摘A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport system is defined through in-depth analysis of the characteristics of arrival and departure operations.Then,several constraints are taken into account,such as wake vortex separation,transfer separation,release separation,and separation in different runway operational modes.Furthermore,the scheduling model is constructed and simulated annealing algorithm is proposed by minimizing the total delay.Finally,Shanghai multi-airport system is chosen to conduct the simulation and validation.And the simulation results indicate that the proposed method is able to effectively improve the efficiency of arrival and departure operations for multi-airport system.
基金supported by China Railway Research and Development(K2021x001)the Talent Fund of Beijing Jiaotong University(2023JBRC003).
文摘During railway operations,trains normally run as scheduled,but the occurrence of unexpected events will disrupt traffic flow and cause train deviation from the original timetable.In order to assist dispatchers in rescheduling trains,this paper introduces an innovative Human-Computer Interaction framework.This framework enables train dispatchers to propose different timetable adjustment instructions to the original or adjusted timetable.These instructions will be processed,stored,analyzed,and digested by computer program,which finally lead to the modification and calculation of the embedded mathematical model,then a new adjusted timetable will be produced and provided to dispatchers for checking and modifying.This framework can iterate for unlimited times based on dispatchers'intentions,until the final results satisfy them.A demonstration system named RTARS(Real-time Timetable Automatic Rescheduling System)is developed based on this framework and it has been applied in Beijing Railway Administration,which shows its effectiveness in reality.
基金Supported by the National Natural Science Foundation of China(61039001)the State Technology Supporting Plan(2011BAH24B08)
文摘In order to obtain accurate conflict risks in terminal airspace design,the concept and calculation model of potential conflict frequency for intersected routes are proposed.Conflict frequency is represented by the product of horizontal conflict frequency and vertical conflict probability.The horizontal conflict frequency is derived from the probability density distribution of conflicts in a period of time.Based on the recorded radar trajectory data,the concept and model of ROUTE distance are proposed,and the probability density function of aircraft height at a specified ROUTE distance is deduced by kernel density estimation.Furthermore,vertical conflict probability and its horizontal distribution are achieved.Examples of three intersected arrival and departure route design schemes are studied.Compared with scheme 1,the conflict frequency values of the other two improved schemes decrease to53% and 24%,respectively.The results show that the model can quantify potential conflict frequency of intersected routes.
基金supported by the National Natural Science Foundation of China (Nos. U1933117,61773202,52072174)。
文摘A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers(ATCOs)with decision support. For arrival pattern recognition,a clustering-based method is proposed to cluster arrival patterns by control intentions. For arrival pattern prediction,two predictors are trained to estimate the most possible command issued by the ATCOs in a particular traffic situation. Training the arrival pattern predictor could be regarded as building an ATCOs simulator. The simulator can assign an appropriate arrival pattern for each arrival aircraft,just like real ATCOs do. Therefore,the simulator is considered to be able to provide effective advice for part of the work of ATCOs. Finally,a case study is carried out and demonstrates that the convolutional neural network(CNN)-based predictor performs better than the radom forest(RF)-based one.
基金Supported by the State Scholarship Foundation from China Scholarship Council(2008603024)
文摘As the air traffic demand is anticipated to be increased significantly in the near future,dynamic and effective allocation of the airspace resource is becoming a world-wide focus in the research field of air traffic management（ATM）.Taking the U.S.targeting the en-route airsapce,a dynamic airspace configuration（DAC） algorithm to reconfigure the airspace in consideration of higher efficiency and safety is presented.First,a modeling technique based on graph theory is proposed to generate a mathematical model for the airspace,and then,the graph model is partitioned into subgraphs for the purpose of sectorizatoin.The final step generates sector configuration with desirable geometry shape.Through analysis on the Cleveland airspace center（ZOB） in the U.S.,the algorithm is proved to be robust to time-varying traffic load.
基金supported by the National Natural Science Foundation of China(Nos.U1233101,71271113)the Fundamental Research Funds for the Central Universities(No.NS2016062)
文摘Terminal airspace(TMA)is the airspace centering several military and civil aviation airports with complex route structure,limited airspace resources,traffic flow,difficult management and considerable airspace complexity.A scientific and rational sectorization of TMA can optimize airspace resources,and sufficiently utilize the control of human resources to ensure the safety of TMA.The functional sectorization model was established based on the route structure of arriving and departing aircraft as well as controlling requirements.Based on principles of sectorization and topological relations within a network,the arrival and departure sectorization model was established,using tree based ant colony algorithm(ACO)searching.Shanghai TMA was taken as an example to be sectorizaed,and the result showed that this model was superior to traditional ones when arrival and departure routes were separated at dense airport terminal airspace.
基金supported by Joint Funds of National Natural Science Foundation of China and Xinjiang under code U1603261the Research Fund of Ministry of Education-China Mobile under Grant No. MCM20160304the Fundamental Research Funds for the Central Universities
文摘Software Defined Networking(SDN) provides a flexible and convenient way to support fine-grained traffic-engineering(TE). Besides, SDN also provides better Quality of Experience(QoE) for customers. However, the policy of the evolution from legacy networks to the SDNs overemphasizes the controllability of the network or TE while ignoring the customers' benefit. Standing in the customers' position, we propose an optimization scheme, named as Optimal Migration Schedule based on Customers' Benefit(OMSB), to produce an optimized migration schedule and maximize the benefit of customers. Not only the quality and quantity of paths availed by migration, but also the number of flows from the customers that can use these multi-paths are taken into consideration for the scheduling. We compare the OMSB with other six migration schemes in terms of the benefit of customers. Our results suggest that the sequence of the migration plays a vital role for customers, especially in the early stages of the network migration to the SDN.
