Working Papers

INTUIT White Paper: Understanding Trade-offs in ATM Performance, March 2016 - Download

 

INTUIT Project Summary - Download

Public Deliverables

D1.3 Final Project Results Report - Download

D2.1 Performance Data Inventory and Quality Assessment  - Download

D2.2 Qualitative Analysis of ATM Performance Drivers and Tradeoffs - Download

D3.1 Visual Analytics Exploration of Performance Data - Download

D4.1 Performance Metrics and Predictive Models - Download

D5.1 Performance Monitoring and Management Toolset - Download

D5.2 Performance Monitoring and Management Toolset Evaluation Report - Download

Scientific Papers

R. Marcos, O.G. Cantú Ros and R. Herranz (2017) "Combining Visual Analytics and Machine Learning for Route Choice Prediction: Application to Pre-Tactical Traffic Forecast", in D. Schaefer (Ed.) Proceedings of the SESAR Innovation Days 2017, EUROCONTROL - Download

 

G. Andrienko, N. Andrienko, W. Chen, R. Maciejewski and Y. Zhao (2017) “Visual Analytics of Mobility and Transportation: State of the Art and Further Research Directions”, IEEE Transactions on Intelligent Transportation Systems,  vol. 18(8), pp.2232-2249 - Download

G. Andrienko, N. Andrienko, G. Fuchs and J. M. Cordero (2017) “Clustering Trajectories by Relevant Parts for Air Traffic Analysis”, IEEE Transactions on Visualization and Computer Graphics, vol. PP, no. 99, pp. 1–1 - Download

 

R. Marcos, D. Toribio, N. Alsina, L. Garrigó, N. Andrienko, G. Andrienko, L. Piovano, T. Blondiau and R. Herranz (2016) "Visual Analytics and Machine Learning for ATM Performance Modelling: Preliminary Findings of the INTUIT Project and Prospects for Future Research", in D. Schaefer (Ed.) Proceedings of the SESAR Innovation Days 2016, EUROCONTROL - Download

Presentations

 

R. Marcos (2017) "Combining Visual Analytics and Machine Learning for Route Choice Prediction: Application to Pre-Tactical Traffic Forecast", presentation at the SESAR Innovation Days 2017, Belgrade, Serbia, November 2017 - Download

 

R. Marcos (2016) "The INTUIT Project", poster presented at the SESAR Innovation Days 2016, Delft, The Netherlands, November 2016 - Download

 

R. Marcos (2016) "Visual Analytics and Machine Learning for ATM Performance Modelling: Preliminary Findings of the INTUIT Project and Prospects for Future Research", presentation at the SESAR Innovation Days 2016, Delft, The Netherlands, November 2016 - Download

 

 

 

 

This project has received funding from the SESAR JU under grant agreement No 699303 under European Union’s Horizon 2020 research and innovation programme

© 2016 INTUIT Consortium. All rights reserved