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Consideration of Passenger Interactions for the Prediction of Aircraft Boarding Time

Schultz, Michael and Reitmann, Stefan (2018) Consideration of Passenger Interactions for the Prediction of Aircraft Boarding Time. Aerospace, 5, p. 101. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/aerospace5040101 ISSN 2226-4310

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Official URL: https://www.mdpi.com/2226-4310/5/4/101

Abstract

In this paper we address the prediction of aircraft boarding using a machine learning approach. Reliable process predictions of aircraft turnaround are an important element to further increase the punctuality of airline operations. In this context, aircraft turnaround is mainly controlled by operational experts, but the critical aircraft boarding is driven by the passengers' experience and willingness or ability to follow the proposed procedures. Thus, we used a developed complexity metric to evaluate the actual boarding progress and a machine learning approach to predict the final boarding time during running operations. A validated passenger boarding model is used to provide reliable aircraft status data, since no operational data are available today. These data are aggregated to a time-based complexity value and used as input for our recurrent neural network approach for predicting the boarding progress. In particular we use a Long Short-Term Memory model to learn the dynamical passenger behavior over time with regards to the given complexity metric.

Item URL in elib:https://elib.dlr.de/123473/
Document Type:Article
Title:Consideration of Passenger Interactions for the Prediction of Aircraft Boarding Time
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schultz, MichaelMichael.Schultz (at) dlr.dehttps://orcid.org/0000-0003-4056-8461
Reitmann, StefanStefan.Reitmann (at) dlr.dehttps://orcid.org/0000-0003-0283-8272
Date:September 2018
Journal or Publication Title:Aerospace
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:No
Volume:5
DOI :10.3390/aerospace5040101
Page Range:p. 101
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2226-4310
Status:Published
Keywords:prediction; passenger Boarding; aircraft turnaround
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:air traffic management and operations
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Air Traffic Concepts and Operation
Location: Braunschweig
Institutes and Institutions:Institute of Flight Control > Air traffic systems
Deposited By: Schultz, Dr. Michael
Deposited On:27 Nov 2018 12:00
Last Modified:27 Nov 2018 12:00

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