A data-driven operational model for traffic at the Dallas Fort Worth International Airport

Monte Lunacek, Lindy Williams, Joseph Severino, Karen Ficenec, Juliette Ugirumurera, Matthew Eash, Yanbo Ge and Caleb Phillips

Journal of Air Transport Management, 2021, vol. 94, issue C

Abstract: Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30Â minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement.

Keywords: Microsimulation; Congestion; Digital twin; Machine learning; Airport; Traffic (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0969699721000442
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:94:y:2021:i:c:s0969699721000442

DOI: 10.1016/j.jairtraman.2021.102061

Access Statistics for this article

Journal of Air Transport Management is currently edited by Anne Graham

More articles in Journal of Air Transport Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().