Aircraft Sequencing Research Articles

Research on Mechanical Operation with Sequencing Optimization of Arrival Aircraft in Terminal Area

In order to ensure flight safety and efficiently sequence arrival aircrafts in terminal area, a sequencing model for scheduling the sequence of arrival aircrafts in the terminal area was discussed. Model's objective is minimizing the loss of delays due to meeting separation which is used to keep the safety of aircrafts before and afterwards. Then the model is transferred to pure integer nonlinear program model so that the model can be solved by some program software like Lingo. At last, a numerical example is used to illustrate the process of solving the model. The numerical example shows that the model proposed in this paper is extremely efficient in scheduling the sequence of arrival flights compared with the FCFS (first come first served) algorithm and model used for the aircraft sequencing in the terminal area is feasible.

Greedy algorithms and metaheuristics for a multiple runway combined arrival-departure aircraft sequencing problem

This paper examines the Aircraft Sequencing Problem (ASP) over multiple runways, under mixed mode operations with the objective of minimizing the total weighted tardiness of aircraft landings and departures simultaneously. The ASP can be modeled as a parallel machine scheduling problem with unequal ready-times, target times and deadlines. Furthermore, sequence-dependent separation times on each runway are considered to prevent the dangers associated with wake-vortex effects. Due to the problem being NP-hard, greedy heuristics and metaheuristics are applied in this paper to obtain solutions in reasonable computation times. The algorithms' solutions are compared to optimal solutions and their performances are evaluated in terms of solution quality and CPU time.

Predictable Flow Monitor for Overlapping Airspace Using Repetitive Flight Plans

Frequent flights have made Taipei Terminal Control Area (TCA) into flow congestion and conflict threat to two close airports. A flow monitor is proposed to provide the predicted sequence of inbound and outbound aircraft with minimum separation in the intersected 10 nautical miles airport circles in Taipei TCA. The repetitive flight plans (RFP) from flight data processor (FDP) data are applied to estimate the time of metering fix until landing. Air traffic control (ATC) indicates vectoring aircraft according to predict sequence by executing ground holding and speed adjustment to avoid airborne holding or conflict. Based on daily schedules and their RFP, flow monitor is designed to forecast the next 60 minutes of inbound flights and to ease possible congestion within 30 minutes in Taipei TCA. Dynamic rescheduling is applied to change delay flights in flow queuing periodically. A case study is simulated to focus on current flow condition. The flow monitor can be used in approach control region and can efficiently reduce the probability of congestion in the busy TCA.

Runway Capacity Model for Multiple Crossing Runways and Impact of Tactical Sequencing

The purpose of this paper is primarily to develop an analytical model for estimating runway capacity of Haneda airport in Tokyo which will have new 4th runway in late 2010. We also analyzed the impact of the sequencing of the departure/arrival aircrafts considering wake turbulence category by using more heuristic model which consider the feasibility of arrival spacing on final approach in practice. Haneda airport will have two set of open- parallel runways with crossing layout (16/34 L/R, 04/22 L/R). Consequently, the departure and arrival traffics will operate dependently with higher complexity than current condition. By using the developed model, we analyze the necessary constraints on aircraft sequencing and spacing for attaining the runway capacity planned by the government and for expanding the capacity.

Application of Genetic Algorithms in the New Air Ttraffic Management Simulation System

Abstract The air traffic control systems are facing more and more serious congestions because of the increasing of air traffic flow in China. To solve the problem we have developed a New Air Traffic Management Simulation System that is according to the ideology of the New Air Traffic Management and the concept of Free Flight. First this paper analyses the mass design idea and the module functions, and then use the genetic algorithms to give the detail methods to solve the airline conflicts on airlines and aircraft sequence takeoff-landfall sorting schedule in the terminal airport area at last we has achieved anticipative effect by use stimulant data compute in the system

Joint Metering and Conflict Resolution in Air Traffic Control

This paper describes a novel optimization-based approach to conflict resolution in air traffic control, based on geometric programming. A key feature of this approach is its ability to also take into account various metering directives issued by the traffic flow management level, in contrast to most methods that focus purely on aircraft separation issues. Moreover, the proposed methodology can account for some of the nonlinearities present in the formulationsofconflictresolutionproblems,whileincurringonlyasmallpenaltyincomputationtimewithrespectto the fastest linear-programming-based approaches. Integer variables can be introduced to improve the quality of the solutions and to include combinatorial choices, for example, to optimize over aircraft sequences in merging streams. Simulation results demonstrate the efficiency of the approach on various aircraft separation problems, including miles-in-trail and minutes-in-trail restrictions through airspace fixes and boundaries.

Polynomial-Time Feasibility Condition for Multiclass Aircraft Sequencing on a Single-Runway Airport

In this paper, we consider the airport-landing problem of scheduling different types of aircraft on a single runway. Since the minimum allowable landing separation time between two consecutive aircraft depends on the relative weight of both aircraft, this is a state-dependent scheduling problem, which, in the general case, is NP-hard. We attempt to modify the aircraft landing sequence from the traditionally used “first-come-first-served” (FCFS) order to be able to land more aircraft in a given period of time. Given a set of planes, the goal is to find a sequence such that no plane can land before it is actually available for landing, the minimum safety separation between two consecutive planes is always satisfied, and the total landing time (makespan) is minimized. Based on the Federal Aviation Administration (FAA) partition of aircraft into weight categories, our algorithm provides a polynomial-time feasibility condition for scheduling a set of planes in a given time interval. It ensures that the Aircraft Scheduling Problem (ASP) presented earlier is not NP-complete and allows us to develop possible practical real-time air traffic control (ATC) execution policies.

Merging of Air Traffic Flows

The problem of merging two or more flows of aircraft in a horizontal plane is considered. The aircraft aim to reach a target flow with the minimal amount of turning, while maintaining a given separation between them. Neither a priori sequencing nor scheduling of the merging aircraft is assumed. The individual trajectories for each aircraft are computed using optimization, and a subset of these optimal trajectories serve as a basis for merging multiple aircraft. A second optimization step produces trajectories for each aircraft to ensure both effective merging into the flow and sufficient separation. This generates the sequencing of the merging aircraft. Simulations of several merging scenarios illustrate the approach and show its results. A statistical study of the influence of the problem parameters on the success of the merging algorithm provides a guideline for the design of the airspace around the merging area. The proposed algorithm can be used for automatic en route and terminal area merging tasks within future more automated air traffic control systems.

A Ripple-Spreading Genetic Algorithm for the Aircraft Sequencing Problem

When genetic algorithms (GAs) are applied to combinatorial problems, permutation representations are usually adopted. As a result, such GAs are often confronted with feasibility and memory-efficiency problems. With the aircraft sequencing problem (ASP) as a study case, this paper reports on a novel binary-representation-based GA scheme for combinatorial problems. Unlike existing GAs for the ASP, which typically use permutation representations based on aircraft landing order, the new GA introduces a novel ripple-spreading model which transforms the original landing-order-based ASP solutions into value-based ones. In the new scheme, arriving aircraft are projected as points into an artificial space. A deterministic method inspired by the natural phenomenon of ripple-spreading on liquid surfaces is developed, which uses a few parameters as input to connect points on this space to form a landing sequence. A traditional GA, free of feasibility and memory-efficiency problems, can then be used to evolve the ripple-spreading related parameters in order to find an optimal sequence. Since the ripple-spreading model is the centerpiece of the new algorithm, it is called the ripple-spreading GA (RSGA). The advantages of the proposed RSGA are illustrated by extensive comparative studies for the case of the ASP.

Mass Casualty Tracking with Air Traffic Control Methodologies

An intrahospital casualty throughput system modeled after air traffic control (ATC) tracking procedures was tested in mass casualty exercises. ATC uses a simple tactile process involving informational progress strips representing each aircraft, which are held in bays representing each stage of flight to prioritize and manage aircraft. These strips can be reordered within the bays to indicate a change in priority of aircraft sequence. In this study, a similar system was designed for patient tracking. We compared the ATC model and traditional casualty tracking methods of paper and clipboard in 18 four-hour casualty scenarios, each with 5 to 30 mock casualties. The experimental and control groups were alternated to maximize exposure and minimize training effects. Results were analyzed with Mann-Whitney statistical analysis with p value < 0.05 (two-sided). The ATC method had significantly (p = 0.017) fewer errors in critical patient data (eg, name, social security number, diagnosis). Specifically, the ATC method better tracked the mechanism of injury, working diagnosis, and disposition of patients. The ATC method also performed considerably better with patient accountability during mass casualty scenarios. Data strips were comparable with the control method in terms of ease of use. In addition, participants preferred the ATC method to the control (p = 0.003) and preferred using the ATC method (p = 0.003) to traditional methods in the future. The ATC model more effectively tracked patient data with fewer errors when compared with the clipboard method. Application of these principles can enhance trauma management and can have application in civilian and military trauma centers and emergency rooms.

Fatigue Crack Growth Prediction under Spectrum Load Sequence in an Aluminum Alloy by K*-RMS Approach

Constant amplitude fatigue crack growth (FCG) tests were performed at various stress ratios in D16 (2024-T3 equivalent) aluminum alloy using single edge notched tension specimens. Empirical FCG law was derived in terms of crack driving force parameter, K*. The spectrum load sequence of a combat aircraft was approximated as an equivalent constant amplitude (CA) load sequence with maximum and minimum stresses as root-mean-square (RMS) maximum and minimum stresses of the spectrum, respectively. The fatigue crack growth behavior was then predicted under this apparent CA load sequence using the K*-RMS approach. For comparison, the conventional method of FCG prediction using crack closure concept was also performed. In this method, empirical FCG law in terms of effective stress intensity factor range, ▵Keff was obtained from the constant amplitude FCGR data. Assuming a constant K op level for spectrum sequence, FCG behavior was predicted through cycle-by-cycle method. Experimental FCG behavior under spectrum load sequence was determined and compared with predicted results. It was observed that the K*-RMS approach provided a fairly good correlation with results obtained from experimental as well as those predicted by the crack closure concept. The predicted fatigue life was conservative and the fatigue life ratio, N pred/Nexpt, was about 0.87. The simplicity of the proposed K*-RMS approach and the reasonable accuracy in fatigue life predictions are quite encouraging.

Toward Time-Based Separation Rules for Landing Aircraft

Aircraft landing on the same runway are potentially exposed to a similar wake vortex hazard, under either instrument meteorological conditions (IMC) or visual meteorological conditions (VMC) when the air traffic control (ATC) distance-based instrument flight rules (IFR) and visual flight rules (VFR) are applied, respectively. Since IFR are stricter than VFR, the runway landing capacity is lower under IMC than under VMC. Possibilities are investigated for introducing time-based ATC separation rules instead of the current distance-based ATC separation rules between landing aircraft as an option for increasing the runway landing capacity under IMC and consequently decreasing the existing gap between IFR and VFR capacity. A model for calculating the landing capacity of a single runway on the basis of ATC time-based separation rules was developed. In addition to these rules, which would be set up by using the current ATC distance-based separation rules and the advanced knowledge on the current and predicted behavior of the wake vortex influenced by the weather conditions, the model uses other inputs, such as the structure of fleet mix in terms of the proportion of particular aircraft categories, which are represented by their wake vortex parameters (the approach speed, wingspan, and weight), and the geometry of the approach corridor, which enables landing on a given runway. The model output is the matrix of the standardized time-based separation rules for different combinations of landing aircraft sequences, which would be applicable to both VMC and IMC, and the runway landing capacity calculated for combinations of the time-based separation rules depending on the current and predicted wake vortex characteristics and behavior. The model is applied to calculating the landing capacity of a single airport runway.

Improving Aircraft Sequencing and Separation at a Small Aircraft Transportation System Airport

Ever-increasing traffic levels at the nation’s major airports have led to traffic congestion and flight delays. Capacity must be increased by building more airports at a great cost or by expanding services to some of the 4,500 airports not currently served by scheduled air carriers. A system must be developed to handle the increased traffic at these non-controlled airports, especially when instrument meteorological conditions prevail. Much work has been performed under the NASA Small Aircraft Transportation System program to determine the feasibility of aircraft operation under instrument flight rules in an air-traffic control free environment. This paper presents research, performed as an extension of the SATS program, into self-separation of general aviation aircraft in a self-controlled airport environment. The research focused on two specific areas: (1) improving automatic sequencing of aircraft of different speeds to make the airspace more efficient, saving time, fuel, and money, and (2) assisting the pilot with approach timing decisions to assure safe aircraft spacing while proceeding in an efficient manner. The primary evaluation method was a real-time distributed simulation with test cases performed by multiple pilots flying simultaneously in the simulation environment. Simulations and test scenarios were performed in the Engineering Flight Simulator, a modular, real-time, nonlinear, six degreeof-freedom fixed base simulator, at Texas A&M University. The pilots flew various general aviation aircraft with differing approach speeds under instrument meteorological conditions. Approach speeds ranged from 80 kts. to 140kts. to encompass the majority of aircraft from small trainers up to light jets that will use the potential SATS airports. New spacing rules were implemented to reduce holding times, and Total Holding Time was used as a metric to validate these new rules. Simulations were performed both with and without automated sequencing to validate the new spacing rules and compare the effects of automated sequencing. A human factors analysis was performed to determine the benefits of shifting some spacing functions from the pilot to the onboard systems, and reductions in pilot workload and improvements in pilot performance were measured to assess the safety improvements due to the increased automation. Based on the results presented in the paper, it was concluded that by changing the sequencing procedure to assign airspace entries once the aircraft are closer to the airport, potential bottlenecks can be avoided and holding times reduced. Furthermore, as a result of the increased avionics functionality and a change in approach spacing guidelines, safety is improved, and holding times are reduced. With these two improvements combined, significant holding time reductions are achieved resulting in fuel and cost savings and further make the self-controlled airport a safe and viable transportation alternative.

Genetic algorithms for solving the aircraft-sequencing problem: the introduction of departures into the dynamic model

The aircraft-sequencing problem is a well-known operations research problem. It is concerned with defining optimal strategies for the sequencing of arriving flights at an airport to optimize as part of the management of traffic flow during the final flight phase. The model here introduces departing flights into the aircraft sequence, sets up a dynamic model to take account of time-varying variables, and builds a specific genetic algorithm to solve the aircraft-sequencing problem.

An Analytical Approach Utilizing Monge Structure to Aircraft Sequencing Problem

In this paper we give an analytical method to the aircraft sequencing problem on a single runway so as to minimize the sum of the time interval called the time separation between successive landing aircraft in a final approach. If cost matrix of the separation time holds Monge properties, the optimum sequence of this problem is given by a non-heavier order of the types classed on aircraft take-off weight. The proposed analytical method is compared with other methods containing the First Come-First Served strategy.

Network-Based Simulation of Aircraft at Gates in Airport Terminals

Simulation is becoming an essential tool for planning, design, and management of airport facilities. A simulation of aircraft at gates at an airport can be applied for various periodically performed applications, relating to the dynamic behavior of aircraft at gates in airport terminals for analyses, evaluations, and decision supports. Conventionally, such simulations are implemented using an event-driven method. For a more efficient simulation, this paper proposes a network-based method. The basic idea is to transform all the sequence and constraint relations of aircraft at gates into a network. The simulation is done by calculating the longest path to all the nodes in the network. The effect of the algorithm of the proposed method has been examined by experiments, and the superiority of the proposed method over the event-driven method is revealed through comprehensive comparisons of their overall simulation performance.

Air traffic management: Optimization models and algorithms

AbstractCurrent air traffic control systems are mainly conceived to ensure the safety of flights by means of tactical interventions, because of the difficulty of accurately foreseeing the traffic evolution. In fact, in real traffic conditions, planes are often penalized since sometimes safety standards are redundant.Today, this management philosophy is no longer valid because of congestion phenomena which often occur in the most important terminal areas. Therefore, as to future control systems it is necessary to introduce not only more automated procedures to keep adequate safety levels, but also planning functions in order to increase the system capacity and to improve system efficiency.In recent years several studies have been carried out, new control concepts have been introduced and some optimization models and algorithms developed to improve air traffic management.In this paper a survey of our early works in this field is reported and a multilevel model of air traffic management is proposed and discussed. The functions corresponding to the on‐line control, that is flow control, strategic control of flights and aircraft sequencing in a terminal area, are examined and the optimization models and solution algorithms are illustrated. Finally, relevant problems coped by recent research are mentioned and new trends are indicated.

An algorithm for computer assisted sequencing and scheduling of terminal area operations

A methodology is proposed for sequencing and scheduling of aircraft in high density terminal areas. Termed Constrained Position Shifting (CPS), this methodology is examined and its effectiveness tested. Potential capacity improvements are noted over the First-Come, First-Served, Runway (FCFS-RW) strategy, especially during peak periods.

A simulation model for aircraft sequencing in the near terminal area

The objective of this study is the development of a simulation model to assist in aircraft sequencing operations in the terminal area. After the definition of the main characteristics of the model, a general structure of a terminal area is considered with a variable number of feeder fixes and alternative paths from the fixes to the runways. The model is designed so as to evaluate different operating policies. A discrete events simulation philosophy, using Fortran as simulation language, is employed. Finally a model application to the Rome terminal area is illustrated. The results obtained show that the model, here presented, is general enough to simulate the terminal area behaviour of any airport.

A Simulation Model for Aircraft Sequencing in the Near Terminal Area

The objective of this study is the development of a simulation model to assisting in aircraft sequencing operations in the near terminal area. After the definition of the main characteristics of the model, a general structure of a terminal area is considered with a variable number of feeder fixes and alternative paths from the fixes to the runways. The model is designed so as to evaluate different operating policies. A discrete events simulation philosophy, using Fortran as simulation language, is employed. Finally a model application to the Rome terminal area is illustrated. The results obtained show that the model, here presented, is general enough to simulate the terminal area behaviour of any airport.