Conflict probability estimation between aircraft with dynamic importance splitting

Jacquemart, Damien; Mitard, J.

doi:10.1016/j.ssci.2012.05.010

Cited by 22 publications

(9 citation statements)

References 17 publications

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“…The FRAM is inherently a qualitative method, and so it cannot offer an empirical approach to express the effect of the parameters' variabilities 21 . To overcome these lacunae, the literature suggests using Monte Carlo simulation, through which the probability distribution of the imposed uncertainties on the functions' features could be used to measure and verify the variabilities 22‐24 . We argue that a delayed function affects the functions coupled to it by reducing their execution times and increasing the risk of accidents.…”

Section: A Functional Speed‐based Model For Risk Assessmentmentioning

confidence: 98%

A framework for the risk assessment of residual hazardous material in the dynamic environment of a composite production process considering operational time variation

Asgari

Kibala

Beauregard

2020

Process Safety Progress

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In the chemical product production process, activities relating to the transportation and storage of residual hazardous materials increase the risk of workplace contamination and associated negative impacts on worker health and safety. In this context, the dynamic nature of the process complicates the study of the parameters underlying the related operational risks. The current operational risks assessment standard, ISO 31000, cannot provide a practical pathway to assess risks in dynamic operational environments. We, therefore, model a dynamic environment to investigate the effect of functional time variation on risk assessment. Verification of the claimed effect will show that even with rigorous instruction when using the available equipment, the process cannot fully conform to current safety standards.

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Section: A Functional Speed‐based Model For Risk Assessmentmentioning

confidence: 98%

A framework for the risk assessment of residual hazardous material in the dynamic environment of a composite production process considering operational time variation

Asgari

Kibala

Beauregard

2020

Process Safety Progress

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“…For instance, Jacquemart and Morio (2013) generate trajectories to estimate collisions between en-route trajectories with constant altitude and heading. Henry et al (2013) create 1-dimensional altitude profiles for the study of airborne collisions between intersecting runways.…”

Section: Abbreviationsmentioning

confidence: 99%

“…Generative models allow generating an arbitrary large amount of trajectories based on the most recent observations, or even procedures that are rarely used, but potentially dangerous. Consequently, previous research such as Eckstein (2010), Henry, Schmitz, Revenko, and Kelbaugh (2013) and Jacquemart and Morio (2013) developed different analytic generators of random aircraft trajectories to be used in conjunction with Monte Carlo simulations. Nevertheless, the generation methods in the literature are often limited as they only generate simple or one-dimensional trajectories, which confines the collision risk analysis to sub-problems.…”

Section: Introductionmentioning

confidence: 99%

Deep Generative Modelling of Aircraft Trajectories in Terminal Maneuvering Areas

et al. 2022

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“…Moreover, some hierarchical IPS algorithms proposed in research are considered for Free Flight modeling described by advanced stochastic Petri nets [11]. In 2013, Damien Jacquemart [12] also used Markov chain model to simulate aircraft trajectories and applied the important splitting method to estimate conflict probabilities to overcome the flaw of Monte Carlo method which is not efficient to estimate small probabilities. In 2015, Qiao et al [13] proposed Hidden Markov model-based Trajectory Prediction (HMTP) method to overcome the difficulty of describing the position and behavior of moving objects in a network-constraint environment.…”

Section: Introductionmentioning

confidence: 99%

A SVM Approach of Aircraft Conflict Detection in Free Flight

Xurui

Wen

et al. 2018

Journal of Advanced Transportation

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Probabilistic conflict detection methods typically require high computational burden to deal with complex multiaircraft conflict detection. In this article, aircraft conflict detection is considered as a binary classification problem; therefore, it can be solved by a pattern recognition method. A potential conflict would be identified, as long as its flight data features are extracted and fed to a classifier which has been trained by a large number of flight datasets. Based on this, a new method based on support vector machine (SVM) is employed to detect multiaircraft conflict in “Free Flight” airspace and to estimate the conflict probability. For that purpose, the current positions, velocity vectors, and predicted look-ahead time are selected as detection factors, and the detection model is established by SVM to detect aircraft conflict within look-ahead time during short and medium terms. Moreover, conflict probabilities are determined by the sigmoid function mapping method. Nevertheless, false alarm rate is always a first and foremost problem that troubles air traffic controllers. For the purpose of reducing false alarm rates, Synthetic Minority Over-sampling Technique (SMOTE) method is used to handle imbalanced datasets. Extensive simulation results are presented to illustrate the rationality and accuracy of this method.

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Conflict probability estimation between aircraft with dynamic importance splitting

Cited by 22 publications

References 17 publications

A framework for the risk assessment of residual hazardous material in the dynamic environment of a composite production process considering operational time variation

A framework for the risk assessment of residual hazardous material in the dynamic environment of a composite production process considering operational time variation

Deep Generative Modelling of Aircraft Trajectories in Terminal Maneuvering Areas

A SVM Approach of Aircraft Conflict Detection in Free Flight

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