Reports de recerca
http://hdl.handle.net/2117/4963
2024-03-29T02:11:35ZCREATE - D5.2: Procedures validation identifying potential benefits and risks and stakeholders implementation suggestions - Exercise Results
http://hdl.handle.net/2117/390834
CREATE - D5.2: Procedures validation identifying potential benefits and risks and stakeholders implementation suggestions - Exercise Results
Sáez García, Raúl; Cabrera Ramírez, Bryan Gustavo; Melgosa Farrés, Marc; Prats Menéndez, Xavier
This report is the deliverable “D5.2 - Procedures validation identifying potential benefits and risks and stakeholders implementation suggestions” of the H2020 SESAR CREATE project. The purpose of this document is to provide the exercise results of the “proof-of-concept” exercise of the CREATE concept of operations (CONOPS) and its solutions (SOL) developed under the previous work packages: • CREATE-SOL-1: Multi-scale multi-pollutant air quality system (AQS); • CREATE-SOL-2: Framework for multi-aircraft environmentally-scored weather-resilient optimized 4D-trajectories in the flight execution phase, WAAP = Weather Avoidance for extended air traffic control (ATC) planning. • CREATE-SOL-3: CO2 and non-CO2 balanced environmental scores module. The main exercise objective was to test the integrated concept of the various computational modules related to the CREATE solutions, and to investigate if the solutions provide operational benefits for the following use-cases; • TMA Naples ¿ reduced local air quality (LAQ) impacts and efficient thunderstorm evasion; • En-Route North-Atlantic tracks extending into the European Civil Aviation Conference (ECAC) area ¿ reduced environmental impacts in terms of CO2 and non-CO2 combined metric in climate sensitive areas (CSA) related to contrail formation regions (CFR), and efficient contrail and thunderstorm evasion. The methodology for the exercise was provided in the exercise plan, i.e. “D5.1 - software design for validation scenarios execution”.[4] The exercises were set up to assess the solutions for maturity level TRL1.
2023-07-14T08:12:59ZSáez García, RaúlCabrera Ramírez, Bryan GustavoMelgosa Farrés, MarcPrats Menéndez, XavierThis report is the deliverable “D5.2 - Procedures validation identifying potential benefits and risks and stakeholders implementation suggestions” of the H2020 SESAR CREATE project. The purpose of this document is to provide the exercise results of the “proof-of-concept” exercise of the CREATE concept of operations (CONOPS) and its solutions (SOL) developed under the previous work packages: • CREATE-SOL-1: Multi-scale multi-pollutant air quality system (AQS); • CREATE-SOL-2: Framework for multi-aircraft environmentally-scored weather-resilient optimized 4D-trajectories in the flight execution phase, WAAP = Weather Avoidance for extended air traffic control (ATC) planning. • CREATE-SOL-3: CO2 and non-CO2 balanced environmental scores module. The main exercise objective was to test the integrated concept of the various computational modules related to the CREATE solutions, and to investigate if the solutions provide operational benefits for the following use-cases; • TMA Naples ¿ reduced local air quality (LAQ) impacts and efficient thunderstorm evasion; • En-Route North-Atlantic tracks extending into the European Civil Aviation Conference (ECAC) area ¿ reduced environmental impacts in terms of CO2 and non-CO2 combined metric in climate sensitive areas (CSA) related to contrail formation regions (CFR), and efficient contrail and thunderstorm evasion. The methodology for the exercise was provided in the exercise plan, i.e. “D5.1 - software design for validation scenarios execution”.[4] The exercises were set up to assess the solutions for maturity level TRL1.Pilot3 - D5.2: Verification and validation report
http://hdl.handle.net/2117/387389
Pilot3 - D5.2: Verification and validation report
Kuljanin, Jovana; Prats Menéndez, Xavier; Homdedeu i Muñiz, Júlia de; Villardi de Montlaur, Adeline de; Delgado Muñoz, Luis; De Falco, Paolino; Argerich, Clara; Valput, Damir; Schultz, Ralph
The deliverable provides the outcomes from the verification and validation activities carried during the course of work package 5 of the Pilot3 project, and according to the verification and validation plan defined in deliverable D5.1 (Pilot3 Consortium, 2020c). Firstly, it presents the main results of the verification activities performed during the development and testing of the different software versions. Then, this deliverable reports on the results of internal and external validation activities, which aimed to demonstrate the operational benefit of the Pilot3 tool, assessing the research questions and hypothesis that were defined at the beginning of the project.
The Agile principle adopted in the project accompanying with the five five-level hierarchy approach on the definition of scenarios and case studies enabled the flexibility and tractability in the selection of experiments through different versions of prototype development. As a result of this iterative development of the tool, some of the research questions initially defined have been revisited to better reflect the validation results.
The deliverable also reports the feedback received from the experts during the internal and external meetings, workshops and dedicated (on-line) site visits. During the validation campaign, both subjective qualitative information and objective quantitative data were collected and analysed to assess the Pilot3 tool. The document also summarises the results of the survey that were distributed to the external experts to assess the human-machine interface (HMI) mock-up developed in the project.
2023-05-12T10:29:39ZKuljanin, JovanaPrats Menéndez, XavierHomdedeu i Muñiz, Júlia deVillardi de Montlaur, Adeline deDelgado Muñoz, LuisDe Falco, PaolinoArgerich, ClaraValput, DamirSchultz, RalphThe deliverable provides the outcomes from the verification and validation activities carried during the course of work package 5 of the Pilot3 project, and according to the verification and validation plan defined in deliverable D5.1 (Pilot3 Consortium, 2020c). Firstly, it presents the main results of the verification activities performed during the development and testing of the different software versions. Then, this deliverable reports on the results of internal and external validation activities, which aimed to demonstrate the operational benefit of the Pilot3 tool, assessing the research questions and hypothesis that were defined at the beginning of the project.
The Agile principle adopted in the project accompanying with the five five-level hierarchy approach on the definition of scenarios and case studies enabled the flexibility and tractability in the selection of experiments through different versions of prototype development. As a result of this iterative development of the tool, some of the research questions initially defined have been revisited to better reflect the validation results.
The deliverable also reports the feedback received from the experts during the internal and external meetings, workshops and dedicated (on-line) site visits. During the validation campaign, both subjective qualitative information and objective quantitative data were collected and analysed to assess the Pilot3 tool. The document also summarises the results of the survey that were distributed to the external experts to assess the human-machine interface (HMI) mock-up developed in the project.NOSTROMO - D4.2: Final Specification of Case Studies
http://hdl.handle.net/2117/387382
NOSTROMO - D4.2: Final Specification of Case Studies
Kuljanin, Jovana; Pons Prats, Jordi; Prats Menéndez, Xavier
This deliverable provides the final specification of the case studies that will be used in the third (last) iteration to demonstrate and evaluate the maturity of the NOSTROMO approach as well as the capabilities of the methodology defined in WP3 and the tools developed in WP5 and WP6. Following the incremental approach adopted in the project and based on the results of the metamodel methodology obtained in the second iteration (using the preliminary specification of case studies), the third iteration will be performed by using the final specification of case studies. Whereas the preliminary specification was more focused on the understanding and development of the single concepts, the final specification of case studies further exploits additional mechanisms that can be incorporated in a particular concept as well as their potential combinations. The potential improvement in the combination of solutions resides in additional implementation of the credit mechanisms within the UPDD concept, which in combination, with add-on capabilities developed for the E-AMAN concept go beyond the current solution descriptions. In addition, the deliverable also outlines the potential combination of PJ.08-02 (Dynamic Airspace Configurations) and PJ.02-08
(Traffic Optimisation on single and multiple runway airports) solutions. This would be the first attempt to combine these two solutions, as their combination has not been acknowledged yet in the PAGAR relationship matrix.
The deliverable also summarises the feedback received from the experts from SJU and PJ.19-04 during the Case Study Workshop held in March, 2022.
2023-05-12T10:21:35ZKuljanin, JovanaPons Prats, JordiPrats Menéndez, XavierThis deliverable provides the final specification of the case studies that will be used in the third (last) iteration to demonstrate and evaluate the maturity of the NOSTROMO approach as well as the capabilities of the methodology defined in WP3 and the tools developed in WP5 and WP6. Following the incremental approach adopted in the project and based on the results of the metamodel methodology obtained in the second iteration (using the preliminary specification of case studies), the third iteration will be performed by using the final specification of case studies. Whereas the preliminary specification was more focused on the understanding and development of the single concepts, the final specification of case studies further exploits additional mechanisms that can be incorporated in a particular concept as well as their potential combinations. The potential improvement in the combination of solutions resides in additional implementation of the credit mechanisms within the UPDD concept, which in combination, with add-on capabilities developed for the E-AMAN concept go beyond the current solution descriptions. In addition, the deliverable also outlines the potential combination of PJ.08-02 (Dynamic Airspace Configurations) and PJ.02-08
(Traffic Optimisation on single and multiple runway airports) solutions. This would be the first attempt to combine these two solutions, as their combination has not been acknowledged yet in the PAGAR relationship matrix.
The deliverable also summarises the feedback received from the experts from SJU and PJ.19-04 during the Case Study Workshop held in March, 2022.CADENZA - D3.2: Final Airspace Users and Air Navigation Service Provider models
http://hdl.handle.net/2117/387376
CADENZA - D3.2: Final Airspace Users and Air Navigation Service Provider models
Melgosa Farrés, Marc; Kuljanin, Jovana; Pavlovic, Goran; Stanojevic, Milan
Airspace Users (AUs) and Air Navigation Service Providers (ANSPs) are two of the most important key operational stakeholders in the Air Traffic Management (ATM) value-chain: AUs generate air traffic demand, while ANSPs (and airports) provide capacity (supply). Since the goal of the CADENZA project is to improve overall network performance by exploring different advanced demand-capacity balancing options, it is necessary to understand business models, decision-making processes and practices of AUs and ANSPs.
The majority of air traffic demand is constituted by commercially oriented AUs (airlines), and while we could argue that the vast majority of airlines seek to maximise profits, we can clearly observe the differences between different business models and strategies to achieve that goal. Traditional network carriers usually operate in a hub and spoke network, sometimes with a significant share of transfer passengers on board. On the other hand, low-cost carriers in most cases operate in a so-called point-to-point network (usually without transfer passengers). There are other AU business models as well, with their own intrinsic characteristics. What is of particular interest for the CADENZA project is to
understand how AUs plan their operations, with an emphasis on trajectories (flight planning), and how they react and respond to disturbances in schedules and operations.
ANSPs are, unlike AUs, in most cases non-for profit and government agencies. They provide, what is usually considered, an (essential) public service (subject to various regulations), with a requirement to deliver enough capacity to accommodate airspace users’ needs, while maintaining safe, sustainable and cost-efficient provision of services. This is why capacity planning principles and practices are very important, especially knowing that traffic is inherently variable both in terms of total volume and spatio-temporal distribution in the network. The CADENZA team seeks to understand the capacity planning process in detail, as well as deployment of available capacity, since these practices differ from
ANSP to ANSP.
In this deliverable, we present the most relevant aspects of AU/ANSP business and operations (in nominal and non-nominal conditions) which we account for in the overall network optimisation (mathematical) model. Our goal is to have a better representation of key operational stakeholders (decisions) in our experiments, aiming to obtain more realistic results.
2023-05-12T10:09:53ZMelgosa Farrés, MarcKuljanin, JovanaPavlovic, GoranStanojevic, MilanAirspace Users (AUs) and Air Navigation Service Providers (ANSPs) are two of the most important key operational stakeholders in the Air Traffic Management (ATM) value-chain: AUs generate air traffic demand, while ANSPs (and airports) provide capacity (supply). Since the goal of the CADENZA project is to improve overall network performance by exploring different advanced demand-capacity balancing options, it is necessary to understand business models, decision-making processes and practices of AUs and ANSPs.
The majority of air traffic demand is constituted by commercially oriented AUs (airlines), and while we could argue that the vast majority of airlines seek to maximise profits, we can clearly observe the differences between different business models and strategies to achieve that goal. Traditional network carriers usually operate in a hub and spoke network, sometimes with a significant share of transfer passengers on board. On the other hand, low-cost carriers in most cases operate in a so-called point-to-point network (usually without transfer passengers). There are other AU business models as well, with their own intrinsic characteristics. What is of particular interest for the CADENZA project is to
understand how AUs plan their operations, with an emphasis on trajectories (flight planning), and how they react and respond to disturbances in schedules and operations.
ANSPs are, unlike AUs, in most cases non-for profit and government agencies. They provide, what is usually considered, an (essential) public service (subject to various regulations), with a requirement to deliver enough capacity to accommodate airspace users’ needs, while maintaining safe, sustainable and cost-efficient provision of services. This is why capacity planning principles and practices are very important, especially knowing that traffic is inherently variable both in terms of total volume and spatio-temporal distribution in the network. The CADENZA team seeks to understand the capacity planning process in detail, as well as deployment of available capacity, since these practices differ from
ANSP to ANSP.
In this deliverable, we present the most relevant aspects of AU/ANSP business and operations (in nominal and non-nominal conditions) which we account for in the overall network optimisation (mathematical) model. Our goal is to have a better representation of key operational stakeholders (decisions) in our experiments, aiming to obtain more realistic results.Dispatcher3 - D5.2: Verification and validation report
http://hdl.handle.net/2117/387373
Dispatcher3 - D5.2: Verification and validation report
Delgado Muñoz, Luis; Kuljanin, Jovana; Mas Pujol, Sergi; Skorobogatov, Georgy; Argerich, Clara; Gregori, Ernesto
The deliverable provides the results from the verification and validation activities within Dispatcher3 project. The document reviews the internal and external validation activities that were carried out during the course of Dispatcher3 project according to the plan defined in D5.1. Dispatcher3 is organised in three layers: data acquisition and preparation, predictive layer, with machine learning models, and prospective models, with the integration of the individual machine learning models in an interactive Advice Generator and an estimator of rotation/reactionary delay. This deliverable presents the verification and validation activities performed on these three components. For the data acquisition and preparation layer the data-pipelines, including the transformation verification and validation activities are described. In the predictive layer both the models developed for the first release and their evolution for the final prototype are described and presented. Finally, for the prospective layer, the interactive interface with its functional requirements is presented and verified, while the reactionary delay model is described, and different scenarios evaluated for its validation.
The deliverable also describes the different internal and external activities and meetings, workshops and dedicated online site visits that have been performed during the duration of the project. Finally, the document assesses the verification of the high-level system-wide requirements identified at the beginning of the project in D1.1 – Technical resources and problem definition, and the research questions identified in the Verification and validation plan (D5.1).
2023-05-12T10:02:09ZDelgado Muñoz, LuisKuljanin, JovanaMas Pujol, SergiSkorobogatov, GeorgyArgerich, ClaraGregori, ErnestoThe deliverable provides the results from the verification and validation activities within Dispatcher3 project. The document reviews the internal and external validation activities that were carried out during the course of Dispatcher3 project according to the plan defined in D5.1. Dispatcher3 is organised in three layers: data acquisition and preparation, predictive layer, with machine learning models, and prospective models, with the integration of the individual machine learning models in an interactive Advice Generator and an estimator of rotation/reactionary delay. This deliverable presents the verification and validation activities performed on these three components. For the data acquisition and preparation layer the data-pipelines, including the transformation verification and validation activities are described. In the predictive layer both the models developed for the first release and their evolution for the final prototype are described and presented. Finally, for the prospective layer, the interactive interface with its functional requirements is presented and verified, while the reactionary delay model is described, and different scenarios evaluated for its validation.
The deliverable also describes the different internal and external activities and meetings, workshops and dedicated online site visits that have been performed during the duration of the project. Finally, the document assesses the verification of the high-level system-wide requirements identified at the beginning of the project in D1.1 – Technical resources and problem definition, and the research questions identified in the Verification and validation plan (D5.1).SIMBAD - D6.1: Evaluation of the SIMBAD performance modelling framework and implementation guidelines
http://hdl.handle.net/2117/387372
SIMBAD - D6.1: Evaluation of the SIMBAD performance modelling framework and implementation guidelines
Pons Prats, Jordi; Kuljanin, Jovana; Prats Menéndez, Xavier; Melgosa Farrés, Marc; Torre Sangrà, David de la
This deliverable aims to describe the evaluation activities of the SIMBAD project. The document contains the results of WP6, whose objective is to demonstrate and evaluate the SIMBAD performance modelling network. This involves the evaluation of the three main technical WPs of the project; namely WP3, WP4 and WP5.
The document is divided in three main parts, one for each WP. In each section, the methodological approach and the evaluation results are described. References to previous deliverables of the project are present along the document, since those documents are an important source of information, both for the methodology description and for the results of each WP.
The evaluation activities have been successfully accomplished. For each WP, the results obtained have been compared with the results obtained by the simulation tools or the ATM experts. The validation results confirm that the proposed machine learning techniques are able to accurately capture the behaviour of the air traffic system, while reducing the computational cost. Even considering the training costs, one can realize that the computational costs are considerably reduced, but if only the execution costs are considered, the costs are further reduced.
2023-05-12T09:57:18ZPons Prats, JordiKuljanin, JovanaPrats Menéndez, XavierMelgosa Farrés, MarcTorre Sangrà, David de laThis deliverable aims to describe the evaluation activities of the SIMBAD project. The document contains the results of WP6, whose objective is to demonstrate and evaluate the SIMBAD performance modelling network. This involves the evaluation of the three main technical WPs of the project; namely WP3, WP4 and WP5.
The document is divided in three main parts, one for each WP. In each section, the methodological approach and the evaluation results are described. References to previous deliverables of the project are present along the document, since those documents are an important source of information, both for the methodology description and for the results of each WP.
The evaluation activities have been successfully accomplished. For each WP, the results obtained have been compared with the results obtained by the simulation tools or the ATM experts. The validation results confirm that the proposed machine learning techniques are able to accurately capture the behaviour of the air traffic system, while reducing the computational cost. Even considering the training costs, one can realize that the computational costs are considerably reduced, but if only the execution costs are considered, the costs are further reduced.Dispatcher3 - D5.1: Verification and validation plan
http://hdl.handle.net/2117/387370
Dispatcher3 - D5.1: Verification and validation plan
Homdedeu i Muñiz, Júlia de; Kuljanin, Jovana; Valput, Damir; Delgado Muñoz, Luis
In this deliverable, we present a verification and validation plan designed to carry out all necessary activities along Dispatcher3 prototype development. Given the nature of the project, the deliverable points to a data-centric approach to machine learning that treats training and testing models as an important production asset, together with the algorithm and infrastructure used throughout the development. The verification and validation activities will be presented in the document.
The proposed framework will support the incremental development of the prototype based on the principle of iterative development paradigm. The core of the verification and validation approach is structured around three different and inter-related phases including data acquisition and preparation, predictive model development and advisory generator model development which are combined iteratively and in close coordination with the experts from the consortium and the Advisory Board. For each individual phase, a set of verification and validation activities will be performed to maximise the benefits of Dispatcher3. Thus, the methodological framework proposed in this deliverable attempts to address the specificities of the verification and validation approach in the domain of machine learning, as it differs from the canonical approach which are typically based on standardised procedures, and in the domain of the final prospective model. This means that the verification and validation of the machine learning models will also be considered as a part of the model development, since the tailoring and enhancement of the model highly relies on the verification and validation results.
The deliverable provides an approach on the definition of preliminary case studies that ensure the flexibility and tractability in their selection through different machine learning model development.
The deliverable finally details the organisation and schedule of the internal and external meetings, workshops and dedicated activities along with the specification of the questionnaires, flow-type diagrams and other tool and platforms which aim to facilitate the validation assessments with special focus on the predictive and prospective models.
2023-05-12T09:52:12ZHomdedeu i Muñiz, Júlia deKuljanin, JovanaValput, DamirDelgado Muñoz, LuisIn this deliverable, we present a verification and validation plan designed to carry out all necessary activities along Dispatcher3 prototype development. Given the nature of the project, the deliverable points to a data-centric approach to machine learning that treats training and testing models as an important production asset, together with the algorithm and infrastructure used throughout the development. The verification and validation activities will be presented in the document.
The proposed framework will support the incremental development of the prototype based on the principle of iterative development paradigm. The core of the verification and validation approach is structured around three different and inter-related phases including data acquisition and preparation, predictive model development and advisory generator model development which are combined iteratively and in close coordination with the experts from the consortium and the Advisory Board. For each individual phase, a set of verification and validation activities will be performed to maximise the benefits of Dispatcher3. Thus, the methodological framework proposed in this deliverable attempts to address the specificities of the verification and validation approach in the domain of machine learning, as it differs from the canonical approach which are typically based on standardised procedures, and in the domain of the final prospective model. This means that the verification and validation of the machine learning models will also be considered as a part of the model development, since the tailoring and enhancement of the model highly relies on the verification and validation results.
The deliverable provides an approach on the definition of preliminary case studies that ensure the flexibility and tractability in their selection through different machine learning model development.
The deliverable finally details the organisation and schedule of the internal and external meetings, workshops and dedicated activities along with the specification of the questionnaires, flow-type diagrams and other tool and platforms which aim to facilitate the validation assessments with special focus on the predictive and prospective models.SIMBAD - D2.1: Specification of Case Studies
http://hdl.handle.net/2117/387366
SIMBAD - D2.1: Specification of Case Studies
Fabio, Adrián; Rodríguez, Rubén; Mocholí, David; Kuljanin, Jovana; Prats Menéndez, Xavier; Melgosa Farrés, Marc
This deliverable provides the specification of the case studies that will enable to achieve SIMBAD objectives: on one hand, the use of data-driven methods for the estimation of hidden variables and trajectory models within WP3; on the other hand, the multiscale traffic pattern classifier of WP4 and; finally, the application of active learning metamodeling to air traffic simulations in WP5. Besides, these case studies will be the context of WP6 for the demonstration of the performance modelling framework developed by SIMBAD.
Additionally, the criteria for the selection of proper case studies as framework for the development of SIMBAD goals are explained. Within this criteria, five main foundations are considered: (1) Compatibility with SIMBAD developments; (2) Matureness of the performance assessment; (3) Potential gap between the expected and the actual benefits; (4) SIMBAD simulator capabilities and; (5) Data availability. Also, and according to the added value that SIMBAD may imply, a complementary comment is considered: the existence of a mature report of the performance after
the deployment.
The document shows a detailed revision of the current air traffic simulation methodology, as well as of the indicators used to evaluate the results, which will be based on the SESAR Performance Framework for consistency. Furthermore, it also highlights the research questions that will be assessed in the different case studies, aimed at capturing the specific added value delivered by the proposed metamodeling methods
2023-05-12T09:43:22ZFabio, AdriánRodríguez, RubénMocholí, DavidKuljanin, JovanaPrats Menéndez, XavierMelgosa Farrés, MarcThis deliverable provides the specification of the case studies that will enable to achieve SIMBAD objectives: on one hand, the use of data-driven methods for the estimation of hidden variables and trajectory models within WP3; on the other hand, the multiscale traffic pattern classifier of WP4 and; finally, the application of active learning metamodeling to air traffic simulations in WP5. Besides, these case studies will be the context of WP6 for the demonstration of the performance modelling framework developed by SIMBAD.
Additionally, the criteria for the selection of proper case studies as framework for the development of SIMBAD goals are explained. Within this criteria, five main foundations are considered: (1) Compatibility with SIMBAD developments; (2) Matureness of the performance assessment; (3) Potential gap between the expected and the actual benefits; (4) SIMBAD simulator capabilities and; (5) Data availability. Also, and according to the added value that SIMBAD may imply, a complementary comment is considered: the existence of a mature report of the performance after
the deployment.
The document shows a detailed revision of the current air traffic simulation methodology, as well as of the indicators used to evaluate the results, which will be based on the SESAR Performance Framework for consistency. Furthermore, it also highlights the research questions that will be assessed in the different case studies, aimed at capturing the specific added value delivered by the proposed metamodeling methodsCADENZA - D3.1: Initial Airspace Users and Air Navigation Service Provider models
http://hdl.handle.net/2117/387363
CADENZA - D3.1: Initial Airspace Users and Air Navigation Service Provider models
Melgosa Farrés, Marc; Kuljanin, Jovana; Pavlovic, Goran; Fron, Xavier; Strauss, Arne; Ivanov, Nikola
Airspace Users (AUs) and Air Navigation Service Providers (ANSPs) are two of the most important key operational stakeholders in the Air Traffic Management (ATM) value-chain: AUs generate air traffic demand, while ANSPs (and airports) provide supply (capacity). Since the goal of CADENZA project is to improve overall network performance by exploring different advanced demand-capacity balancing options, it is necessary to understand business models, decision-making processes and practices of AUs and ANSPs.
Majority of air traffic demand is generated by commercially oriented AUs (airlines), and while we could argue that vast majority of airlines seek to maximise profits, we can clearly observe the differences between different business models and strategies to achieve that goal. Traditional network carries usually operate in a hub&spoke network, sometimes with a significant share of transfer passengers on board. On the other hand, low-cost carriers in most cases operate in a so-called point-to-point network (usually without transfer passengers). There are other AU business models as well, with their own intrinsic characteristics. What is of particular interest for CADENZA project is to understand how AU plan their operations, with an emphasis on trajectory (flight planning), and they react and respond to disturbances in schedules and operations.
ANSPs are, unlike AUs, in majority of cases non-for profit and government agencies. They provide, what is usually considered, (essential) public service (subject to various regulations), with a requirement to deliver enough capacity to accommodate airspace users’ needs, while maintaining safe, sustainable and cost-efficient provision of services. This is why capacity planning principles and practices are very important, especially knowing that traffic is inherently variable both in terms of total volume and spatio-temporal distribution in the network. The CADENZA team seeks to understand the capacity planning process in detail, as well as deployment of available capacity, since these practices differ from ANSP to ANSP.
2023-05-12T09:35:32ZMelgosa Farrés, MarcKuljanin, JovanaPavlovic, GoranFron, XavierStrauss, ArneIvanov, NikolaAirspace Users (AUs) and Air Navigation Service Providers (ANSPs) are two of the most important key operational stakeholders in the Air Traffic Management (ATM) value-chain: AUs generate air traffic demand, while ANSPs (and airports) provide supply (capacity). Since the goal of CADENZA project is to improve overall network performance by exploring different advanced demand-capacity balancing options, it is necessary to understand business models, decision-making processes and practices of AUs and ANSPs.
Majority of air traffic demand is generated by commercially oriented AUs (airlines), and while we could argue that vast majority of airlines seek to maximise profits, we can clearly observe the differences between different business models and strategies to achieve that goal. Traditional network carries usually operate in a hub&spoke network, sometimes with a significant share of transfer passengers on board. On the other hand, low-cost carriers in most cases operate in a so-called point-to-point network (usually without transfer passengers). There are other AU business models as well, with their own intrinsic characteristics. What is of particular interest for CADENZA project is to understand how AU plan their operations, with an emphasis on trajectory (flight planning), and they react and respond to disturbances in schedules and operations.
ANSPs are, unlike AUs, in majority of cases non-for profit and government agencies. They provide, what is usually considered, (essential) public service (subject to various regulations), with a requirement to deliver enough capacity to accommodate airspace users’ needs, while maintaining safe, sustainable and cost-efficient provision of services. This is why capacity planning principles and practices are very important, especially knowing that traffic is inherently variable both in terms of total volume and spatio-temporal distribution in the network. The CADENZA team seeks to understand the capacity planning process in detail, as well as deployment of available capacity, since these practices differ from ANSP to ANSP.SafeNcy - D5.3: Integrated capability test report V1
http://hdl.handle.net/2117/382698
SafeNcy - D5.3: Integrated capability test report V1
Viry, Benoît; Gonzalez, Patrice; Baillagou, Florian; Charpentier, Antoine; Sáez García, Raúl; Homdedeu i Muñiz, Júlia de
This document provides the results obtained during the execution of the formal integration and validation test plan for the SafeNcy system.
This document provides the results obtained during the execution of the formal integration and validation test plan for the SafeNcy system.
2023-02-08T15:03:30ZViry, BenoîtGonzalez, PatriceBaillagou, FlorianCharpentier, AntoineSáez García, RaúlHomdedeu i Muñiz, Júlia deThis document provides the results obtained during the execution of the formal integration and validation test plan for the SafeNcy system.