Distributed scheduling for air traffic throughput maximization during the terminal phase of flight

Chipalkatty, Rahul; Twu, Philip; Rahmani, Amir; Egerstedt, Magnus

doi:10.1109/cdc.2010.5717934

Cited by 6 publications

(9 citation statements)

References 11 publications

(13 reference statements)

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“…Feasibility conditions for Phases I, II, and III will each be treated separately. Note that 2.C.1-6 only the main feasibility results will be stated and that for a more rigorous derivation of the conditions, the reader is referred to [15].…”

Section: Feasibility Conditions For Separationmentioning

confidence: 99%

“…A dual optimization version of Problem 5.2 can then be formed. The new problem is split up such that each aircraft will update its estimate of the other aircraft's arrival time based on information it receives from the other aircraft, as seen in [15]. An artifact of the dual optimization problem are the parameters: 1 and 2 , associated with the mismatch between estimates of arrival times.…”

Section: Distributed Solutionmentioning

confidence: 99%

“…Thorough formulations of the subproblems in the dual problem that are solved at each of these steps are detailed in [15]. In order to solve these problems, Aircraft must communicate 3 and 1 to…”

Section: Dual Decomposition Solutionmentioning

confidence: 99%

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Air traffic maximization for the terminal phase of flight under FAA's NextGen framework

Twu

Chipalkatty

Rahmani

et al. 2010

29th Digital Avionics Systems Conference

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The NextGen program is the FAA's response to the ever increasing air traffic, that provides tools to increase the capacity of national airspace, while ensuring the safety of aircraft. In support of this vision, this paper provides a decentralized algorithm based on dual decomposition for safe merging and spacing of aircraft at the terminal phase of the flight. Aircraft negotiate optimal merging times that ensure safety, while penalizing deviations from the nominal path. We provide feasibility conditions for the safe merging of all incoming legs of flight and put the viability of the proposed algorithm to the test through simulations.

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Section: Feasibility Conditions For Separationmentioning

confidence: 99%

Section: Distributed Solutionmentioning

confidence: 99%

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Air traffic maximization for the terminal phase of flight under FAA's NextGen framework

Twu

Chipalkatty

Rahmani

et al. 2010

29th Digital Avionics Systems Conference

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“…This paper, however, states it was not successful in its attempt to devise an autonomous algorithm. The paper [5] derives sufficient conditions on incoming aircraft spacing and set of arrival times to guarantee feasible arrival times at a merge point. The method is extended to more general scenarios by means of a binary tree.…”

Section: Literature Surveymentioning

confidence: 99%

An Elementary Algorithm for Autonomous Air Terminal Merging and Interval Management

White

2017

AIAA Modeling and Simulation Technologies Conference

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A central element of air traffic management is the safe merging and spacing of aircraft during the terminal area flight phase. This paper derives and examines an algorithm for the merging and interval managing problem for Standard Terminal Arrival Routes. It describes a factor analysis for performance based on the distribution of arrivals, the operating period of the terminal, and the topology of the arrival routes; then presents results from a performance analysis and from a safety analysis for a realistic topology based on typical routes for a runway at Phoenix International Airport. The heart of the safety analysis is a statistical derivation on how to conduct a safety analysis for a local simulation when the safety requirement is given for the entire airspace I. INTRODUCTION This study develops and examines an algorithm for the merging and interval managing problem for Standard Terminal Arrival Routes (STARS). Once the algorithm is derived, there are two parts to this study. The first part consists of a factor analysis for performance that considers the distribution of arrivals, the operating period of the terminal, and the topology of the arrival routes. The second part conducts a performance analysis and a safety analysis for a realistic topology based on the routes for one of the runways at Phoenix International Airport. The overall objective is to increase understanding of air traffic by creating algorithms and models. The merging and interval management of aircraft in a terminal appears to be a topic that can evolve into other areas. Secondary objectives include:  Simulation for part of or all of the national airspace-such simulations can contribute to more efficient and safer routing and operations, and such simulations depend on accurate and efficient models of terminal operations.  Operation of autonomous aircraftautonomous aircraft can perform routine and boring tasks such as monitoring a forest for fires, and they can perform dangerous tasks such as crop dusting. We are more willing to send an autonomous craft instead of a piloted airplane into hazardous conditions. In the near future, we may see the autonomous operation of cargo carriers.  Layout of arrival routesthere may or may not be two different criteria. One is the efficient and safe conduction of autonomous procedures. The other is to ease the burden of an air traffic controller. For air traffic controllers, our conjecture is that easing the burden leads to more efficient and safer operation.  Extension to traffic outside the terminal areain the material below, when an aircraft arrives at the terminal area, the algorithm computes whether or not it can enter the queue. One possibility is the converse of this where the algorithm computes the range of arrival speeds and arrival times that allow it to enter the queue. This can be applied to aircraft in transit. It can possibly be extended to cover the entire flight including takeoff time.

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“…A great deal of previous research into the issue has focused on resolving the routing and scheduling problem using optimisation techniques. Determining a flight path consisting of a finite set of waypoints in the airspace network is often modelled as a directed graph, and a schedule as a chart that optimises the estimated time of arrival at each of the waypoints [3]- [8]. Such approaches only considers the flight schedule at a runway, not entire speed profiles.…”

Section: Introductionmentioning

confidence: 99%

A New Multiple Flights Routing and Scheduling Algorithm in Terminal Manoeuvring Area

Bae

Shin

Lee

et al. 2018

2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)

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We address multiple flights planning problems from its initial waypoint to its destination while satisfying the minimum separation requirement between each aircraft at all times in a Terminal Manoeuvring Area (TMA) to maintain or increase runway throughput. Due to operational constraints for safety, most of the current aircraft fly over or by waypoints, and along nominal routes in the airspace. Where the waypoints and routes in the airspace can be modelled as a weighted digraph, called airspace graph. We propose a problem that consists of determining a flight path (routing problem) and its speed profile (scheduling problem) in a given airspace graph in which a timebased weighting scheme of the airspace graph is proposed to reflect a speed-limitation-compliant schedule that satisfy the minimum separation requirement. For multiple flights cases, the flight paths and schedules are obtained by iteratively solving the problem for each flight by applying the First Come First Served (FCFS) algorithm to determine an arrival sequence. The main contributions of this paper are increasing a solution search space by solving two problems simultaneously, efficient computational time, and providing the separation-compliant flight path and speed profile within the speed limitation for each flight. We demonstrate the advantages of the proposed approach through a case study in which multiple flights arrive at a single airport, and we compare the results with Regulated Tactical Flight Model (RTFM) obtained from EUROCONTROL Demand Data Repository 2 (DDR2). Although, we consider only a single airport and make an assumption to simplify flight routes from holding stacks to a Final Approach Fix (FAF), the results show the potential usage of the proposed algorithm as a Decision Support Tool (DST) for Air Traffic Controllers (ATCOs) if the following considerations are taken into account: detailed routesbased flights after the holding stacks, multiple airports, departing aircraft, all possible aircraft types, and uncertainties produced by external sources.

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Distributed scheduling for air traffic throughput maximization during the terminal phase of flight

Cited by 6 publications

References 11 publications

Air traffic maximization for the terminal phase of flight under FAA's NextGen framework

Air traffic maximization for the terminal phase of flight under FAA's NextGen framework

An Elementary Algorithm for Autonomous Air Terminal Merging and Interval Management

A New Multiple Flights Routing and Scheduling Algorithm in Terminal Manoeuvring Area

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