Determination of Lateral Flight Adherence in Recorded Air Traffic Data

Oaks, Robert D.; Paglione, Mike; Hughes, W. J.

doi:10.2514/6.2005-5823

Cited by 6 publications

(4 citation statements)

References 2 publications

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“…The aircraft which does not follow its flight plan, otherwise called non-conforming aircraft, is quite prevalent not only because the pilots misunderstand the controller's instructions via voice communications but also because the controllers do not update the currently issued clearances into their computer systems; in the latter case, a decision support tool may need to declare the aircraft as non-conforming its plan although the aircraft is following exactly to the voice clearance. Although more reliable and frequently updated information on flight plan is available in near future thank to the advanced data-link technologies such as Automatic Dependent Surveillance Broadcast (ADS-B), the needs for detecting non-conformance aircraft is still exist due to the following reasons: [10][11][12][13] 1) The filed or broadcasted flight plan information still needs to be independently verified for the safety and security reasons. Furthermore, an additional source of uncertainty on how the pilots actually execute the planned trajectory, e.g., "slow" to "fast" climb or descent to the cleared altitude, exists and needs to be identified.…”

Section: Ia 4-dimension Trajectory Prediction and Managementmentioning

confidence: 99%

A Bayesian Approach for Conformance Monitoring

Lee

Fukuda

2011

11th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference

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For safe and efficient management of air traffic, the prediction of aircraft trajectories into the future is necessary. Conformance monitoring is one of important functions in trajectory prediction to ensure that aircraft adhere to the assigned flight plan. One of challenges for timely detection of a non-conforming aircraft is that its trajectories cannot be fully specified due to uncertainty on how the aircraft executes the currently applied flight plan. This uncertainty, together with noisy measurements, can create a series of data poor situations which often results in a high level of false detection or detection delay. To overcome this problem, our paper proposes a new method of conformance monitoring by using a Bayesian formulation. A prior available information can be utilized in the proposed method to reduce false detections without an arbitrary increase in detection delay. Furthermore, the proposed method can provide actual probability of conformance which can bring various capabilities to trajectory prediction. The proposed method is illustrated with examples.Nomenclature z(k) measurement of aircraft's state at time k Z(k) a set of all measurements up to time k T CT trajectory change time for a non-conforming aircraft Ω a set two conformance statuses; ω 0 -conformance and ω 1 -non-conformance H a set of TCT hypotheses

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Section: Ia 4-dimension Trajectory Prediction and Managementmentioning

confidence: 99%

A Bayesian Approach for Conformance Monitoring

Lee

Fukuda

2011

11th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference

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“…Flight conformance is the determination of how well an aircraft is adhering to these constraints. There have been many approaches to characterizing out-of-conformance aircraft, [13][14][15] and its impact on the performance of air traffic control systems has been measured. 16 These approaches were too restrictive in their classification of out-of-conformance, or were too advanced for separation assurance applications.…”

Section: A Flight Conformancementioning

confidence: 99%

A Trajectory Management Strategy for Nonconforming Flights and Multi-Agent Separation Assurance

Santiago

2013

2013 Aviation Technology, Integration, and Operations Conference

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This paper presents an enhancement for use in advanced trajectory management automation systems for addressing issues associated with aircraft not conforming to their route and altitude assignments. It also addresses integration issues when tactical and strategic conflict resolution services are provided by different sources. The enhancement is being added to an automation concept referred to as the Advanced Airspace Concept (AAC) that is being developed to meet the needs of the air transportation system beyond NextGen. A flight plan route and assigned altitude conformance monitor is added to the AAC. In addition, a mechanism to define out-of-conformance tolerance thresholds, and a solution, referred to as Recapture, to resolve out-of-conformance flights is proposed. Furthermore, this paper introduces a trajectory refinement concept for rejoining an aircraft with its route or assigned altitude especially following an open-ended separation maneuver such as a single heading vector or temporary altitude. These new capabilities enable the integration of the Autoresolver and Tactical Separation-Assured Flight Environment, or any other separation agent, so the transition of strategic and tactical separation assurance responsibility is seamless. A set of fast-time simulations are performed to support the proof of concept, and a survey of operational applications are explored.

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“…This error can be detected in post processing or even operationally by measuring the difference between the automation's known horizontal position and the coincident surveillance position. In a study conducted in [9] and in another in [10], the overall adherence to the current air traffic control clearance is defined as the status of whether the aircraft is following its known clearance at each instance of time during its flight. As with any definition, this definition is subject to interpretation, but focusing only on the lateral dimension discussed in [10], it is interpreted to mean that the surveillance radar position (or global positioning satellite position if available) for an aircraft should be declared out of lateral adherence when it is determined that the aircraft's intent was to deviate laterally from its known cleared route.…”

Section: Lateral Deviation Metricsmentioning

confidence: 99%

“…Figure 5. Geometry of Lateral Deviation -Adapted from [10] Although the calculation of all five metrics completely and accurately defines the lateral geometry involved, it is proposed that only two are actually necessary to adequately determine if an aircraft is laterally deviating from its route. If a combination of the normal distance, d r , and the angle β are within certain predetermined thresholds, it could be stated that the aircraft is in lateral adherence to the current known route.…”

Section: R -mentioning

confidence: 99%

Lateral Intent Error’s Impact on Aircraft Prediction

Paglione

Bayraktutar

McDonald³

et al. 2010

Air Traffic Control Quarterly

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Unprecedented global initiatives have begun to redesign the aviation systems that provide for the efficient and safe transport of civilian aircraft. Success of these initiatives is only possible through global collaborations that allow broader analyses and data to be shared. The paper reports on just such a study that examines the lateral deviations from the automation's known horizontal route of flight to the actual aircraft position. These errors are due to the typical navigation and surveillance errors, as well as the larger atypical errors that are mainly caused by purposeful changes in the route of flight that are not updated. Large data analyses within the ground automation systems of the United States and Europe indicated errors from 20 to 30 nautical miles are common, while airborne Australian and more samples in the United States had errors from 100 to 800 times smaller. Further analysis illustrated the direct impact these errors have on safety critical separation management functions. It was concluded that airborne derived data via Automatic Dependent Surveillance Contract reports offer a major opportunity to improve the groundbased automation functions.

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Determination of Lateral Flight Adherence in Recorded Air Traffic Data

Cited by 6 publications

References 2 publications

A Bayesian Approach for Conformance Monitoring

A Bayesian Approach for Conformance Monitoring

A Trajectory Management Strategy for Nonconforming Flights and Multi-Agent Separation Assurance

Lateral Intent Error’s Impact on Aircraft Prediction

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