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E-book Risk Assessment in Air Traffic Management

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Penilaian

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Currently, complexity is derived from reports provided by the controllers andpilots involved in the incidents, from which the mid-air collision risk is estimated.These incidents are extremely rare events, which make them infeasible to deriveany reliable statistics. Furthermore, not all incidents are reported, making it diffi-cult to infer how many true incidents have really occurred. Finally, the used inci-dent classification is ranked according to how close the involved aircraft finallywere, omitting any associated kinematics, which could provide us with more rep-resentative information about risk.This chapter describes how to estimate the probability of mid-air collision plusadditional helpful information, used to estimate the safety level of given airspacewhen populated with a sample of air traffic. The process is based on an integratedhybrid approach, using flights stored in a database and a stochastic mathematicalcollision risk model. The database containing the trajectory description for the trafficsample is used to empirically determine the conflicts or encounters from which thefrequency of risks (FoR) and the kinematics of the aircraft involved in these encoun-ters can be determined. Whereas the mathematical model is used to estimate theprobability of collision associated with each aircraft encounter, and from them theglobal probability of air miss [10],Figure 1describes the whole process:Risk is here understood as any event that requires immediate reaction to avoida dangerous situation which has the potential to cause damage or harm. Inparticular, regarding mid-air collisions, it refers to any situation where two or moreaircraft are evolving toward a loss of separation; if not corrective action is taken.Nowadays there are different databases from which the encounter identificationand characterization can be derived. They can be grouped into two families:sur-veillance data files, describing the aircraft trajectories by a sequence of 3D + Tpositions for all flights at time intervals (around every 5 s), andon event data files,containing 3D + T positions or all flights at any time the aircraft speed vectorchanges, for example, the Demand Data Repository 2 (DDR2) of Eurocontrol. Thischapter applies the results to a particular case of use, with the purpose of showingthe value of the model as a powerful safety tool. There are different tools that allowus to identify and characterize the encounters from these databases, for example,the Eurocontrol’s Network Strategic Tool (NEST) uses DDR2 to this end. In thiswork, the used tool was developed by E. Garcia [3].

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

629.1 NIE r

Penerbit

London : InTechOpen., 2020

Deskripsi Fisik

178 hlm

Bahasa

English

ISBN/ISSN

9781838803704

Klasifikasi

629.1

Tipe Isi

text

Tipe Media

computer

Tipe Pembawa

online resource

Edisi

-

Subjek

Aerospace Engineering

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

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