This article describes a unified solution to three types of separation-assurance problems that occur in en-route airspace: separation conflicts, arrival sequencing, and weather-cell avoidance. Algorithms for solving these problems play a key role in the design of future air traffic management systems such as the US's NextGen. Because these problems can arise simultaneously in any combination, it is necessary to develop integrated algorithms for solving them. A unified and comprehensive solution to these problems provides the foundation for a future air traffic management system that requires a high level of automation in separation assurance. This article describes the three algorithms developed for solving each problem and then shows how they are used sequentially to solve any combination of these problems. The first set of algorithms resolves loss-of-separation conflicts. It generates multiple resolutions for each conflict and then selects the one giving the least delay. Two new algorithms, one for sequencing and merging of arrival traffic, referred to as the arrival manager, and the other for weather-cell avoidance are presented. Because these three problems constitute a substantial fraction of the workload of en-route controllers, integrated algorithms to solve them is a basic requirement for automated separation assurance. This article also reviews the advanced airspace concept, a proposed design for a ground-based system that postulates redundant systems for automated separation assurance in order to achieve both high levels of safety and airspace capacity. It is proposed that automated separation assurance be introduced operationally in several steps, each step reducing controller workload further while increasing airspace capacity. A fast time simulation was used to determine performance statistics of the algorithm at up to 3× current traffic levels.
In this article we present recent work towards the development of an autonomous system that performs conflict resolution and arrival scheduling for aircraft in the terminal airspace around an airport. An autonomous air traffic control system is defined as a system that can safely solve the major traffic management problems currently handled by human controllers. It has the potential to handle higher traffic levels and a mix of conventional and unmanned aerial vehicles with reduced dependency on controllers. The main objective of this paper is to describe the fundamental trajectory algorithms that must be incorporated in such a system. These algorithms generate arrival trajectories that are free of conflicts with other traffic, and meet scheduled times of arrival for landing with specified in-trail spacings. The maneuvers the system employs to resolve separation and spacing conflicts include speed control, horizontal maneuvers, and altitude changes. Furthermore, the system can reassign arrival aircraft to a different runway in order to reduce delays. Examples of problems solved and performance statistics from a fast-time simulation using simulated traffic of arrivals and departures at the Dallas/Fort Worth International Airport and Dallas Love Field Airport are also provided.
Abstract-A digital random return-to-zero technique is presented to improve the dynamic performance of current-steering digital-to-analog converters (DACs). To demonstrate the proposed technique, a CMOS 8-bit 1.6-GS/s DAC was fabricated in a 90-nm CMOS technology. The DAC achieves a spurious-free dynamic range better than 60 dB for a sine-wave input up to 460 MHz and better than 55 dB up to 800 MHz. The DAC consumes 90 mW of power.Index Terms-Current steering, digital-to-analog converter (DAC), digital random return-to-zero (DRRZ), return-tozero (RZ).
This paper presents a design approach and basic algorithms for a future system that can perform aircraft conflict resolution, arrival scheduling and convective weather avoidance with a high level of autonomy in terminal area airspace. Such a system, located on the ground, is intended to solve autonomously the major problems currently handled manually by human controllers. It has the potential to accomodate higher traffic levels and a mix of conventional and unmanned aerial vehicles with reduced dependency on controllers. The main objective of this paper is to describe the fundamental trajectory and scheduling algorithms that provide the foundation for an autonomous sytem of the future. These algorithms generate trajectories that are free of conflicts with other traffic, avoid convective weather if present, and provide scheduled times for landing with specified in-trail spacings. The maneuvers the algorithms generate to resolve separation and spacing conflicts include speed, horizontal path, and altitude changes. Furthermore, a method for reassigning arrival aircraft to alternate runways in order to reduce delays is also included. The algorithms generate conflict free trajectories for terminal area traffic, comprised primarily of arrivals and departures to and from multiple airports. Examples of problems solved and performance statistics from a fast-time simulation using simulated traffic of arrivals and departures at the Dallas/Fort Worth International Airport and Dallas Love Field are described.
This paper examines the performance of a system that performs automated conflict resolution and arrival scheduling for aircraft in the terminal airspace around major airports. Such a system has the potential to perform separation assurance and arrival sequencing tasks that are currently handled manually by human controllers. The performance of the system is tested against several simulated traffic scenarios that are characterized by the rate at which air traffic is metered into the terminal airspace. For each traffic scenario, the levels of performance that are examined include: number of conflicts predicted to occur, types of resolution maneuver used to resolve predicted conflicts, and the amount of delay for all flights. The simulation results indicate that the percentage of arrivals that required a maneuver that changes the flight's horizontal route ranged between 11% and 15% in all traffic scenarios. That finding has certain implications if this automated system were to be implemented simply as a decision support tool. It is also found that arrival delay due to purely wake vortex separation requirements on final approach constituted only between 29% and 35% of total arrival delay, while the remaining major portion of it is mainly due to delay back propagation effects.
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