Predicting Passenger Flow at Charles De Gaulle Airport Security Checkpoints Philippe Monmousseau, Gabriel Jarry, Florian Bertosio, Daniel Delahaye, Marc Houalla
Predicting Passenger Flow at Charles De Gaulle Airport Security Checkpoints Philippe Monmousseau, Gabriel Jarry, Florian Bertosio, Daniel Delahaye, Marc Houalla To cite this version: Philippe Monmousseau, Gabriel Jarry, Florian Bertosio, Daniel Delahaye, Marc Houalla. Predicting Passenger Flow at Charles De Gaulle Airport Security Checkpoints. AIDA-AT 2020, 1st International Conference on Artificial Intelligence and Data Analytics for Air Transportation, Feb 2020, Singapore, Singapore. 10.1109/AIDA-AT48540.2020.9049190. hal-02506611v2 HAL Id: hal-02506611 https://hal-enac.archives-ouvertes.fr/hal-02506611v2 Submitted on 9 Jun 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Predicting Passenger Flow at Charles De Gaulle Airport Security Checkpoints Philippe Monmousseau∗, Gabriel Jarry∗, Florian Bertosio∗y, Daniel Delahaye∗, Marc Houallay ∗ ENAC, Université de Toulouse, 7 Avenue Edouard Belin, 31400 Toulouse Email: {jarry.gabriel, philippe.monmousseau, daniel.delahaye}@enac.fr y Groupe ADP, Email: {florian.bertosio}@gmail.com Abstract—Airport security checkpoints are critical areas in air- port operations. Airports have to manage an important passenger flow at these checkpoints for security reason while maintaining service quality. The cost and quality of such an activity depend on the human resource management for these security operations.
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