Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept

Thipphavong, David P.

doi:10.2514/6.2010-9372

Cited by 10 publications

(12 citation statements)

References 12 publications

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“…The model is an analytical implementation of a similar Monte-Carlo simulation model given in [8] and [9]. The analytical implementation uses a combination of fault trees and dynamic event trees.…”

Section: Discussionmentioning

confidence: 99%

“…The AAC model in this paper is similar to and inspired by analyses given in [8], [9], and [10]. A higher level analysis (not at the sub-component level) was given in [11].…”

Section: Relation To Previous Workmentioning

confidence: 99%

“…References [8] and [9] use Monte-Carlo simulation to evaluate a safety model of the AAC. One challenge with Monte-Carlo simulation is that many replications are necessary to estimate very small probabilities.…”

Section: Relation To Previous Workmentioning

confidence: 99%

“…One approach to handle this issue is to use a rare-event acceleration technique. For example, [9] uses importance sampling to accelerate the simulation performance of the same model.…”

Section: Relation To Previous Workmentioning

confidence: 99%

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Safety and sensitivity analysis of the advanced airspace concept for nextgen

Shortle

Sherry

Yousefi

et al. 2012

2012 Integrated Communications, Navigation and Surveillance Conference

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This paper presents a model and methodology for a safety and sensitivity analysis of the Advanced Airspace Concept. This analysis is part of a larger effort to analyze safety-capacity tradeoffs in NextGen concepts. A key part of the model is the definition of a dynamic event tree, which is like a standard event tree, but also includes the dimension of time in the state-space description. The model is constructed and evaluated in an automated fashion based on a set of input tables. Thus, changes to the model are easily implemented and results are automatically re-computed. The analytical implementation can be evaluated fairly quickly (a couple seconds per evaluation). A systematic sensitivity analysis shows that the transponder failure probability is a critical model parameter.

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Section: Discussionmentioning

confidence: 99%

“…The AAC model in this paper is similar to and inspired by analyses given in [8], [9], and [10]. A higher level analysis (not at the sub-component level) was given in [11].…”

Section: Relation To Previous Workmentioning

confidence: 99%

Section: Relation To Previous Workmentioning

confidence: 99%

“…One approach to handle this issue is to use a rare-event acceleration technique. For example, [9] uses importance sampling to accelerate the simulation performance of the same model.…”

Section: Relation To Previous Workmentioning

confidence: 99%

See 2 more Smart Citations

Safety and sensitivity analysis of the advanced airspace concept for nextgen

Shortle

Sherry

Yousefi

et al. 2012

2012 Integrated Communications, Navigation and Surveillance Conference

View full text Add to dashboard Cite

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“…The fault-tolerance of the AutoResolver algorithm given trajectory prediction errors was evaluated via simulation in [17]. Other forms of safety analysis for the AAC were studied in previous papers [1], [4], [22], [21], all of which focus on the impact of hardware failures on the safety of the AAC. In [1], system safety is defined as a combination of basic events and modeled using fault trees.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic model checking for comparative analysis of automated air traffic control systems

Zhao¹,

Rozier²

2014

2014 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

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Ensuring aircraft stay safely separated is the primary consideration in air traffic control. To achieve the required level of assurance for this safety-critical application, the Automated Airspace Concept (AAC) proposes a network of components providing multiple levels of separation assurance, including conflict detection and resolution. In our previous work, we conducted a formal study of this concept including specification, validation, and verification utilizing the NuSMV and CadenceSMV model checkers to ensure there are no potentially catastrophic design flaws remaining in the AAC design before the next stage of production. In this paper, we extend that work to include probabilistic model checking of the AAC system. 1 We are motivated by the system designers requirement to compare different design options to optimize the functional allocation of the AAC components. Probabilistic model checking provides quantitative measures for evaluating different design options, helping system designers to understand the impact of parameters in the model on a given critical safety requirement. We detail our approach to modeling and probabilistically analyzing this complex system consisting of a real-time algorithm, a logic protocol, and human factors. We utilize both Discrete Time Markov Chain (DTMC) and Continuous Time Markov Chain (CTMC) models to capture the important behaviors in the AAC components. The separation assurance algorithms, which are defined over specific time ranges, are modeled using a DTMC. The emergence of conflicts in an airspace sector and the reaction times of pilots, which can be simplified as Markov processes on continuous time, are modeled as a CTMC. Utilizing these two models, we calculate the probability of an unresolved conflict as a measure of safety and compare multiple design options.

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Mathematical Models for Air Traffic Conflict and Collision Probability Estimation

Mitici

Blom

2019

IEEE Trans. Intell. Transport. Syst.

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Increasing traffic demands and technological developments provide novel design opportunities for future Air Traffic Management (ATM). In order to evaluate current air traffic operations and future designs, over the past decades several mathematical models have been proposed for air traffic conflict and collision probability estimation. However, few comparative evaluations of these models with respect to their mathematical core exist. Such comparative evaluations are particularly difficult since different authors employ different model definitions, notations and assumptions, even when using the same modeling techniques. The aim of this paper is: i) to present the mathematical core of the existing approaches for air traffic conflict and collision probability estimation using the same body of notations and definitions; ii) to outline the advances in estimating the probability of air traffic conflict and collision using a unified mathematical framework; iii) to various air traffic applications and their use of directed mathematical models for air traffic conflict and collision probability estimation; and iv) to provide insight into the capabilities and restrictions of the mathematical models in the evaluation of future ATM designs.

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Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept

Cited by 10 publications

References 12 publications

Safety and sensitivity analysis of the advanced airspace concept for nextgen

Safety and sensitivity analysis of the advanced airspace concept for nextgen

Probabilistic model checking for comparative analysis of automated air traffic control systems

Mathematical Models for Air Traffic Conflict and Collision Probability Estimation

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