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For the current development of green civil aviation, this study aims to optimize the green four-dimensional (4D) trajectory of commercial flight by taking into account conventional cost and environmental cost. Some fundamental models, efficient processing methodologies, and conventional objectives are proposed to construct the framework of trajectory optimization. Based on the environmental cost including greenhouse gas cost and harmful gas cost, green objective functions are presented. The $\text{A}^\ast $ algorithm and the trapezoidal collocation method are employed to optimize the lateral path and vertical profile for 4D optimization trajectory generation. A case study for the A320 from Barcelona Airport to Frankfurt Airport yields the results that the optimal costs can be obtained under different objectives and the total cost can be more optimized by adjusting the weights of environmental cost and conventional cost. The study builds an aided tool for 4D trajectory optimization and demonstrates that environmental factors and conventional factors should be taken into comprehensive consideration when constructing the flight trajectory in the future, as well as it can underpin the green and sustainable development of the air transport industry.

The flow corridor is a tube-shape class of airspace designed for the future air transportation system, which aims to reduce complexity, restructuring the airspace to provide more system capacity. In order to support operational procedures design towards increased operational efficiency in the flow corridor, an accurate assessment of alternative procedures is a pre-requisite. This paper proposes a dynamic stochastic simulation framework including various microscopic behaviors for the assessment of distributed self-separation procedures for the air traffic in flow corridors. We first specify three prominent self-separation modes which distinguish flow corridors from today’s airways system, and present detailed self-separation procedures and algorithms in a parallel-lane flow corridor incorporating self-separating, lane-passing and lane-switch behaviors based on the aircraft dynamic model and the proportional derivative control theory. Then, incorporating these self-separation algorithms, a dynamic stochastic simulation modeling framework is constructed to assess and compare the alternative distributed self-separation procedures. The framework is applied to a parallel-lane flow corridor deployed from Beijing nearby airports (ZBAA, ZBTJ and ZBNY) to Guangzhou nearby airports (ZGGG, ZGSZ and ZGSD) in China, and the self-separation procedures were thoroughly assessed with both realistic and simulated data for benefits assessment and sensitivity analysis. Results show that the speed-based operational procedure is more suitable for high-density operations while the other two procedures have more flexibility which can be used for air traffic flow contingency management and/or trajectory management.

Although the concept of sustainable development has made certain achievements in many fields, airport sustainability (AS) has not yet formed a unified and comprehensive theory and evaluation method. According to the connotation of sustainable development, this paper proposes the definition of airport sustainability by considering China&rsquo, s national conditions and airport characteristics. Secondly, this paper identifies four AS dimensions of economy, environment, society, and operation and selects and screens evaluation indicators for each dimension. Thirdly, a synthetic evaluation index model of AS is constructed based on the benefit of the doubt (BoD) model, and the process of evaluation method is planned according to a synthetic evaluation method. Finally, Guangzhou Baiyun International Airport (CAN) is selected as a case study to evaluate the AS from 2008 to 2017, and the influencing factors of AS are discussed to predict AS in 2018. The evaluation and prediction results are consistent with the actual operational characteristics of CAN.

With the rapid development of the air transport industry, the problem of airspace congestion and flight delay in the terminal area (TMA) becomes more and more serious. In order to improve the efficiency of flight operations in TMA, point merge procedure had been devised. This paper takes the approach routes in TMA as the research object, taking into account such conditions as obstacle clearance, flight interval, and procedure area. Based on the flight time, fuel consumption, pollutant emission, and noise impact, an optimization model of point merge procedure is constructed. Genetic algorithm is used to optimize the structure of procedure. The Shanghai Hongqiao International Airport is selected for simulation verification, and the actual flow distribution of the airport is analyzed as an example. The results show that the average flight time was reduced by 0.26 min, the average fuel consumption was reduced by 1,240.64 kg, the average NOx emissions were reduced by 1.09 kg, and the noise impact range was contracted by 55 km2 after optimization. The point merge procedure optimization method can be expected to reduce the flight time, fuel consumption, and environmental impact of flights in TMA, so as to optimize the aircraft approach trajectory.

This paper proposes a simulation-based framework for assessing airborne self-separation procedures in flow corridors with consideration of different performance metrics, including air traffic operations, corridor capacity, safety, and environmental impacts. Firstly, the airborne self-separation concept in flow corridors is introduced, followed by an agent-based flow corridor simulation model. Then, data were collected to initialize a parallel-lane flow corridor model connecting A461 upper air route from Beijing to Guangzhou in China which can also simulate aircraft self-separating in the flow corridor. The total control delay, flow corridor throughput, breakout rate, and the CO2 emissions of traffic flow were considered as the impact measurements, and the TOPSIS and entropy method was used to rank the performances of different self-separation procedures. We found that combining multiple objectives into one, the optimum scheme can be obtained to guide the design of self-separation procedures for flow corridors. The research results can be used by airspace managers to dynamically develop appropriate operational procedures and rules for flow corridors given different operational conditions and constraints. Also, the framework proposed in the research may be used to evaluate the design of airspace structure with consideration of multiple objectives.

The rapid growth in air traffic has resulted in increased emission and noise levels in terminal areas, which brings negative environmental impact to surrounding areas. This study aims to optimize terminal area operations by taking into account environmental constraints pertaining to emission and noise. A multi-objective terminal area resource allocation problem is formulated by employing the arrival fix allocation (AFA) problem, while minimizing aircraft holding time, emission, and noise. The NSGA-II algorithm is employed to find the optimal assignment of terminal fixes with given demand input and environmental considerations, by incorporating the continuous descent approach (CDA). A case study of the Shanghai terminal area yields the following results: (1) Compared with existing arrival fix locations and the first-come-first-serve (FCFS) strategy, the AFA reduces emissions by 19.6%, and the areas impacted by noise by 16.4%. AFA and CDA combined reduce the emissions by 28% and noise by 38.1%; (2) Flight delays caused by the imbalance of demand and supply can be reduced by 72% (AFA) and 81% (AFA and CDA) respectively, compared with the FCFS strategy. The study demonstrates the feasibility of the proposed optimization framework to reduce the environmental impact in terminal areas while improving the operational efficiency, as well as its potential to underpin sustainable air traffic management.

The emission and contrail of flights at high altitude sector have a great impact on the environment. The paper establishes the multi-objective optimization method of high altitude sector operation based on environmental protection, which can reduce the impact of sector air traffic operation on the environment and enhance the operation efficiency of the high altitude sector. According to the operation characteristics of the sector, the aviation meteorological data of the sector are analyzed, and the forming conditions of the contrail are calculated. Considering the air traffic control rules and aircraft flight characteristics, a multi-objective optimization model of sector flight allocation strategy is established, and the influence of aviation meteorological conditions and different allocation strategy combinations on the optimal operation of sector is analyzed. To solve the multi-objective optimization model, the paper uses an evolutionary computation method in intelligence computing and takes non-dominated sorted genetic algorithm-II with elitist strategy (NSGA-II). Shanghai Area No.20 sector (ZSSSAR20) is selected as the case in this paper. Example verification reveals that taking number of contrails, fuel consumption and flight delays as the optimization targets, aircraft are more likely to rely on altitude deployment strategy so as to better reduce the impact of air traffic operation en route on environment, and improve sector operation efficiency en route.

This paper first calculates the departure delay and arrival delay of each flight by mining historical flight data. Then, a new method based on density clustering for identification and visualization of restricted airspace units that considers this activity is proposed. The main objective is to identify the restricted airspace units by calculating the average delay time according to the accumulative delay time of airspace units and the accumulative delay flight. Therefore, the density-based spatial clustering of applications with noise (DBSCAN) clustering method is utilized to match the latitude and longitude coordinates of each spatial domain unit with its delay time to construct a feature matrix, and then clustering analysis is conducted according to the time period. The method aims at identifying the most severe restricted units in each period. The reliability and applicability of the proposed method are validated through a real case study with flight information from Beijing Capital International Airport, Hongqiao International Airport, and Baiyun International Airport during a typical day. The investigation shows that the DBSCAN clustering method can identify the restricted spatial units intuitively on the six flight paths between Beijing Capital International Airport, Hongqiao International Airport, and Baiyun International Airport.

Continuous descent approach (CDA) is an aircraft operating technique enabling the execution of a flight profile optimized with low engine thrust and drag configuration, thereby reducing fuel burn and emissions during descent. However, due to lack of consideration of aircraft type, gross mass and meteorological parameters, the current generic design criteria does not allow the fuel saving potential of CDA to be efficiently utilized. In this paper, we propose an Aircraft-specific Trajectory Optimization Model to reduce CDA routes fuel consumption given different aircraft states and meteorological conditions. The model defines a transition airspace concept for generating alternative CDA routes, and incorporates a classic point mass flight dynamics model to determine the aircraft trajectory and fuel consumption. Subsequently, the simulated annealing algorithm with Monte Carlo simulation are used to evaluate the average fuel burn before and after optimization. To gain insight on fuel saving efficiency, a comprehensive transition area length and aircraft states sensitivity analysis is conducted. We found that the transition area plays an important role in CDA optimization, with the increasing of the transition area length from 5 nm to 20 nm, the average fuel savings percentages could be increased by 10.76% to 22.62%.

Generating safe, environment-friendly and viable air traffic operation strategy is a key means to guarantee the healthy and sustainable development of air transportation. Taking into account operation characteristics of the en route control sectors, as well as meteorological conditions, aircraft type and control modes, the paper sets up flight deployment optimization model with greenhouse effect, fuel consumption and flight delay as the targets, and analyzes the impact of deployment strategy such as altitude change, speed variation and heading change on sector operation en route. Example verification reveals that taking contrail and fuel consumption as the optimization targets, aircraft are more likely to rely on altitude maneuver deployment strategy so as to better reduce the impact of air traffic operation on environment, and improve the operation efficiency of en route control sector.

In order to reduce the environmental impact of aircraft operation in the terminal area, this paper researched the route optimization method. Firstly, this paper constructed the air pollutant emission and noise assessment model, and the flight performance model. Secondly, aiming at reducing air emissions and noise level, the multi-objective terminal area route optimization model is established based on the principles of flight safety and flight procedure construction. Then this paper puts forward the path optimization method of emission and noise reduction of terminal area route network, through the research on the priority setting method of terminal area approach and departure route planning. The route segmentation method and NSGA-II algorithm are employed to solve the problem. Finally, a numerical case study is carried out for the Shanghai terminal area, and yields the following results: (1) Compared with the original route network, the optimized route network in the terminal area can significantly reduce emission and noise by reducing pollutant emission by 51.4% and noise influence by 21.5%, (2) The method can also reduce fuel consumption by 60.5% and the total route length by 21.1%.

The continuous and strong growth of the civil aviation in the world combined with the severe adverse weather problem have made necessary the collaboration between the different civil aviation agents to improve the management of the capacity-demand imbalances in the airspace. In this paper, we consider a stochastic simulation optimization problem for air route selection strategy based on flight delay cost. The problem takes consideration of airspace capacity and demand uncertainty, three strategies, including collaborative reroute strategy (CRS), full information reroute strategy (FIRS) and hybrid stated route preference strategy (HSR), are employed to mitigate the flight delay cost. To find the best strategy, a discrete event simulation model is built by Arena Software, and the Monte Carlo method combined with the OCBA simulation optimization technique is employed for assessing a common severe convective weather scenario in the Central and Southern China airspace. Simulation results imply that HSR schemes show better system-wide performance than CRS and FIRS, these benefits are supposed to come from the batch allocations method. Although the airline can receive full information in advance, FIRS does not show obvious advantage in reducing the total airborne waiting time than CRS. For the system-wide performance FIRS is better than CRS, but not as good as HSR.

Air traffic capacity is a prerequisite and foundation of air traffic flow management (TFM). The sector capacity is usually given a static value in traditional TFM. In fact, it is time varying because it is always affected by weather, airspace status, and many other factors. A more refined TFM requires dynamic sector capacity. How to accurately evaluate dynamic capacity is the difficulty and development trend of sector capacity evaluation. The paper firstly presents the definition and the influential factors of the sector dynamic capacity. Then the characteristic of dynamic sector capacity affected by the main dynamic factor of severe weather is analyzed. In considering sector structure, civil aviation regulation, controller workload and airborne weather radar, sector dynamic capacity estimation model is set up. At last a prototype example is given to evaluate the sector dynamic capacity. The results verify the model is valid and practical.