Air Traffic Management and Systems II

ENRI organized the fourth ENRI International Workshop on ATM/CNS (EIWAC 2015) to share comprehensive information on the latest ATM/CNS technologies and operations among EIWAC participants. In this chapter, the overview of EIWACs, summaries of each keynote speech and invited speech are presented. The discussion in the EIWAC has demonstrated the problems that present aviation systems are facing and the perspective for future global aviation systems. Harmonization between current and future ATM/CNS systems, R&D and implementation, and different modernization plans are also discussed.

To sustain the continuously increasing air traffic demand, the future air traffic management system will rely on a so-called trajectory-based operations concept that will increase air traffic capacity by reducing the controller workload. This will be achieved by transferring tactical conflict detection and resolution tasks to the strategic planning phase. In this future air traffic management paradigm context, this paper presents a methodology to address such trajectory planning at nationwide and continent scale. The proposed methodology aims at minimizing the global interaction between aircraft trajectories by allocating alternative departure times, alternative horizontal flight paths, and alternative flight levels to the trajectories involved in the interaction. To improve robustness of the strategic trajectory planning, uncertainty of aircraft position and aircraft arrival time to any given position on the trajectory are considered. This paper presents a mathematical formulation of this strategic trajectory planning problem leading to a mixed-integer optimization problem, whose objective function relies on the new concept of interaction between trajectories. A computationally efficient algorithm to compute interaction between trajectories for large-scale applications is presented and implemented. Resolution method based on hybrid-metaheuristic algorithm has been developed to solve the above large-scale optimization problem. Finally, the overall methodology is implemented and tested with real air traffic data taking into account uncertainty over the French and the European airspace, involving more than 30,000 trajectories. Conflict-free and robust 4D trajectory planning is produced within computational time acceptable for the operation context, which shows the viability of the approach.

Air Traffic Management (ATM) ensures the safety of flights by optimizing flows and maintaining separation between aircraft. Many ATM applications involve some aircraft trajectory optimization in order to improve the performance of the overall system. Trajectories are objects belonging to spaces with infinite dimensions. Widely used approaches are based on discretization, sampling trajectories at some regular points, and then using appropriate representations to reduce the dimension of the search space. We propose an approach in which trajectories in a two-dimensional space are designed with the help of convex hull generation. By using static as well as moving obstacles for which the position and the size are controlled by artificial evolution, we propose a new algorithm for efficient trajectory planning in Terminal Maneuvering Areas.

Although advance future avionics will enable full compliance with the given trajectory, there are many uncertainty sources that can deflect aircraft from their intended positions. In this article, we investigate potential of robust trajectory planning, considered as an additional demand management action, as a means to alleviate the en route congestion in airspace. Robust trajectory planning (RTP) involves generation of congestion-free trajectories with minimum operating cost taking into account uncertainty of trajectory prediction and unforeseen event. The model decision variables include ground delay, change of horizontal route, and vertical profile (flight level) to resolve congestion problem. The article introduces a novel approach for route generation (3D trajectory) based on homotopic feature of continuous functions. It is shown that this approach is capable of generating a large number of route shapes with a reasonable number of decision variables. RTP problem is modeled as a mixed-variable optimization problem, and it is solved using stochastic methods. The model is tested on a real-life example from the French airspace. The results indicate that, under certain conditions, at the expense of a small increase of total planned costs, it is possible to increase robustness of the proposed solution providing a good alternative to the solutions given by existing conflict-free trajectory planning models.

This paper evaluates the usability of two direct optimization methods: the Piecewise Linear Approximation Dynamic Programming method and the gradient-based method for a practical trajectory optimization problem based on the trajectory-based operation concept. As a practical application, the longitudinal fuel minimal trajectory of a passenger aircraft is continuously designed for all flight phases. The computational features of each method are investigated in terms of computational time, convergence to a realistic solution, and applicability for the practical model. The two kinds of optimal trajectories show a great agreement indicating that an optimal solution close to a global optimum could be obtained by the gradient-based method. The results have demonstrated that gradient-based methods have a potential to provide an optimal solution close to a global optimum with a reasonable computational time. The gradient-based method is expected to be utilized for designing a practically preferable reference trajectory toward the realization of more efficient operations in the air traffic management system.

The enhancement of air traffic management (ATM) system performance by management of aircraft trajectories, commonly referred to as 4D trajectory-based operations (TBO), is one of the key technologies in the Japan Civil Aviation Bureau’s “Collaborative Actions for Renovation of Air Traffic Systems (CARATS)” plan. The release of “CARATS Open Data,” aircraft track data for all scheduled commercial instrument rule flights in Japan’s en route airspace, has enabled the understanding of performance in present flight operations on a broad scale and assesses the potency of possible benefits toward a futuristic ATM system. This paper focuses on potential benefits in a 4D TBO system through operational performance on existing flight operations based on trajectory optimization. A trajectory optimization model developed by the authors is used to investigate the potential benefits by exerting the maximum performance of the aircraft in respect to highly regulated restrictions used in current flight procedures. Quantitative results show that weather conditions have a significant impact on conventional operational performance. Optimized results denote that substantial benefits could be obtained by more relaxed flight planning which vary according to arrival time assignment and weather conditions.

The International Civil Aviation Organization (ICAO) has created a long-term plan for a harmonized global future air traffic management (ATM) system to be achieved by the year 2030. A key element of this plan is four-dimensional trajectory-based operations (4D TBO), where aircraft fly along optimal trajectories defined in space and time and agreed to between the aircraft and air traffic controllers and operators. One issue is how to minimize the uncertainty of predicted arrival time, which increases in proportion to flight distance from the destination airport. To clarify and help resolve this issue, this study investigates design principles and algorithms for a novel ground advisory system which smoothes arrival air traffic by providing coverage for both en route and terminal airspaces. Defined as “Extended Arrival MANager (E-AMAN),” operational concepts to be used to collaborate with 4D TBO are proposed in this paper. Information sharing, air-ground harmonization, and the design of human-system interactions are discussed as three main technologies for supporting efficient arrival operations in the future. Furthermore, future arrival scheduling should not only follow the current first-come first-served (FCFS) protocol but should also consider performance-based operations (PBO) targeting the mixed equipage situation in a future ATM environment. This paper presents a future vision of 4D TBO-based arrival management and clarifies policies for developing technologies to support the ATM system of 2030.

As the demand for air traffic increases, new air traffic management systems are needed. In the system, it is expressly necessary to avoid conflict between aircraft. Efficient methods to prevent conflict are currently based on the expertise of air traffic controllers. Hence, a two-step analysis method is described in this study. First, it is shown using a proposed method with en route radar track data that no conflicts occurred in the airspace over Japan during the period in question. Second, instructions provided to pilots by the air traffic controllers to solve conflicts are estimated from the same radar data, and the results allow some groups to be rearranged in terms of avoidance procedures. These results will be useful references when developing an automated system of conflict detection and resolution in the future.

The sharp increase in air traffic flow causes traffic congestion in airspaces near airports, called Terminal Maneuvering Areas (TMA). The departure and arrival traffic of airports follow predesigned routes named standard instrument departure (SID) routes and standard terminal arrival routes (STAR). Optimizing these routes is crucial to regulate air traffic. Currently, SIDs and STARs are designed manually, based on the airport layout and nearby constraints. The objective of this research is to propose a methodology for designing an arrival/departure route in TMA, taking into account some constraints including obstacle avoidance. The shape of a route in horizontal plan is a succession of arcs of circles and segments. The originality of our study is, on the one hand, that the horizontal route is associated with a cone in vertical plan enveloping all ascent (or descent) aircraft profiles, and on the other hand, a branching strategy in a branch and bound (B&B) framework tailored on the problem is proposed.

Japanese airspace capacity must expand in order to accommodate the increased air traffic expected in the near future. Efficient air congestion management is a promising approach for achieving this goal. Arrival management for inbound flights to Tokyo International Airport, the busiest airport in Japan, is considered to be the most demanding challenge for efficient air congestion management. In this paper, a concept of arrival management based on multiple aircraft trajectory optimization is proposed and examined using the actual flight track data. At first, free-flight trajectory optimization is applied to the inbound flights landing on one of the two runways to simulate the most efficient ideal flights. Next, time separation constraints at a merging point on the boundary of the terminal area are imposed in order to avoid conflicts among the aircraft in the terminal area. As a result of the optimization, optimal sequencing and flight time adjustments are generated. Benefits of the proposed concept are evaluated by comparing the optimal trajectories with the corresponding actual flight trajectories. Dynamic programming is used for the optimization of each flight trajectory and scheduling of the arrival times. The obtained results reveal that in addition to safe arrival time separation, trajectory optimization with arrival time assignment produces substantial benefits in terms of fuel consumption and flight time.

Estimating the capacity of an airport network system is an NP-hard problem. It is defined as the maximum traffic that can be accommodated by a network of airports subjected to resource constraints, such as fleet mix and node/link capacity. Mathematically, the problem is modeled as a classical multi-commodity flow (MCF) problem. In MCF it is generally considered that the resources required by the commodities at a node or link cannot change over time and must be independent of the interaction among the commodities. However, in an airport network, the local resource requirements for aircrafts usually change over time due to different weather condition, runway configurations, and different aircraft mix. In addition, in a given airport network, the flow requires a certain amount of time to travel through each link and can’t be assumed to travel instantaneously through the network as in the case of an electricity network. These complexities deem existing MCF algorithms inapplicable to estimate the flow capacity of an airport network. To address this problem, we propose a new method to estimate the capacity of an airport network and develop a dynamic multi-commodity flow optimization algorithm. The proposed optimization algorithm is augmented by an iterative Hill-Climber algorithm to solve the network capacity model in which all flow constraints of air traffic are preserved. Experimental results show that the proposed model is not only capable of realistically estimating the airport network capacity under different levels of aircraft mix but also in identifying individual flows at different links and amount of delay for each aircraft.

With the rapid increase in air traffic demands, the more accurate and reliable tracking systems for aircraft surveillance are required to improve the capacity, safety, and efficiency of air traffic control (ATC) services. As a suboptimal hybrid filter, the Interacting Multiple Model (IMM) estimator has been applied in the practical aircraft tracking systems. However, it is difficult for the standard IMM filter to precisely estimate the aircraft state when the target is maneuvering since the detection of maneuvers is often delayed by the response of Kalman filters. On the other hand, in the Mode S radar Enhanced Surveillance (EHS), the downlink aircraft parameters (DAPs) are available for obtaining the updated states of aircraft; however, this information of aircraft parameters has not been used systematically to improve the performance of current tracking systems. In this paper, a DAPs-based tracking system which is able to dynamically revise the mode probabilities of the IMM estimator according to the real-time change in the aircraft motion is proposed. The results of computer simulations and practical experiments show the effectiveness of the proposed system by comparing it with the standard IMM-based tracking system.

This paper describes a concept and evaluation results of a Foreign Object of Debris (FOD) detection radar system using Radio on Fiber technologies. Demands for FOD detection system for airports runway is increasing due to explosive growth of air traffic. Since very short wavelength and wide frequency band allocation, 90 GHz-band Frequency-Modulated Continuous-Wave (FMCW) radar with RoF technology is a good candidate for FOD detection system for runway. We have started a R&D project for 90 GHz-band FMCW radar in 2012 and demonstrated in Sendai Airport using the licensed proto-type radar system. Our demonstration system consists of two radar transmitter/receiver unit with rotating antenna and one control unit with signal generation and data analysis capability. These radar unit and control unit are connected with RoF technology. Precision FMCW signal can be shared and transmitted through optical fiber. On Sendai airport runways, we have demonstrated sample FOD (one inch metallic cylinder, etc.) detection from150 m distance range.