IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v615y2023ics0378437123001450.html
   My bibliography  Save this article

Modelling and assessment of the arrival and departure process at the terminal area: A case study of Chennai international airport

Author

Listed:
  • Chandra, Aitichya
  • Verma, Ashish
  • Sooraj, K.P.
  • Padhi, Radhakant

Abstract

Airport and terminal area traffic congestion is a growing concern of the air traffic management (ATM) system. A major step towards mitigating the impacts of congestion is understanding the fluctuating arrival and departure process at airports. Exploring the intrinsic time-varying nature of the arrival and departure process enhances this understanding, hence, is instrumental in formulating operational policies for managing airport capacity and delays. This paper presents a data-driven statistical framework to investigate, understand, and model the time-varying fluctuations in the aircraft arrival and departure process. We have considered one-month data obtained from Chennai international airport operations for this study. The dynamic evolution and fluctuation characteristics of arrivals and departures are conducted using Seasonality and Multifractal Detrended Fluctuation Analysis. Six theoretical probability distributions were used to fit the observed aircraft arrivals and departures at different temporal scales using the maximum likelihood estimation method. This study also develops a G1(t)/G2(t)/KFirst Come First Serve dynamic queuing model for a day’s arrival and departure process. The results suggest that arrival and departure processes exhibit weak but visible multifractal characteristics. Fluctuations are higher at a smaller temporal scale compared to a larger scale, and the probability distributions of arrival and departure are also time-varying. The framework has universal applicability, and the insights have important implications for operational policies on the air transportation workforce and infrastructure management.

Suggested Citation

  • Chandra, Aitichya & Verma, Ashish & Sooraj, K.P. & Padhi, Radhakant, 2023. "Modelling and assessment of the arrival and departure process at the terminal area: A case study of Chennai international airport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    • Handle: RePEc:eee:phsmap:v:615:y:2023:i:c:s0378437123001450
    DOI: 10.1016/j.physa.2023.128590
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123001450
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2023.128590?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Hongzhi & Zhang, Xingchen & Zhang, Xie, 2020. "Multiscale complexity analysis on airport air traffic flow volume time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    2. Alonso Tabares, Diego & Mora-Camino, Felix & Drouin, Antoine, 2021. "A multi-time scale management structure for airport ground handling automation," Journal of Air Transport Management, Elsevier, vol. 90(C).
    3. Jiang, Xurui & Wen, Xiangxi & Wu, Minggong & Song, Min & Tu, Congliang, 2019. "A complex network analysis approach for identifying air traffic congestion based on independent component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 364-381.
    4. Rodríguez-Sanz, à lvaro & Fernández de Marcos, Alberto & Pérez-Castán, Javier A. & Comendador, Fernando Gómez & Arnaldo Valdés, Rosa & París Loreiro, à ngel, 2021. "Queue behavioural patterns for passengers at airport terminals: A machine learning approach," Journal of Air Transport Management, Elsevier, vol. 90(C).
    5. D Worthington, 2009. "Reflections on queue modelling from the last 50 years," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 83-92, May.
    6. Honghai Zhang & Yan Xu & Lei Yang & Hao Liu, 2014. "Macroscopic Model and Simulation Analysis of Air Traffic Flow in Airport Terminal Area," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-15, August.
    7. Liu, Hongzhi & Zhang, Xingchen & Zhang, Xie, 2018. "Exploring dynamic evolution and fluctuation characteristics of air traffic flow volume time series: A single waypoint case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 560-571.
    8. Link, Heike & Götze, Wolfgang & Himanen, Veli, 2009. "Estimating the marginal costs of airport operation using multivariate time series models with correlated error terms," Journal of Air Transport Management, Elsevier, vol. 15(1), pages 41-46.
    9. Arnaldo Scarpel, Rodrigo & Pelicioni, Luciele Cristina, 2018. "A data analytics approach for anticipating congested days at the São Paulo International Airport," Journal of Air Transport Management, Elsevier, vol. 72(C), pages 1-10.
    10. Lunacek, Monte & Williams, Lindy & Severino, Joseph & Ficenec, Karen & Ugirumurera, Juliette & Eash, Matthew & Ge, Yanbo & Phillips, Caleb, 2021. "A data-driven operational model for traffic at the Dallas Fort Worth International Airport," Journal of Air Transport Management, Elsevier, vol. 94(C).
    11. Caccavale, Maria Virginia & Iovanella, Antonio & Lancia, Carlo & Lulli, Guglielmo & Scoppola, Benedetto, 2014. "A model of inbound air traffic: The application to Heathrow airport," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 116-122.
    12. Linda Green & Peter Kolesar & Anthony Svoronos, 1991. "Some Effects of Nonstationarity on Multiserver Markovian Queueing Systems," Operations Research, INFORMS, vol. 39(3), pages 502-511, June.
    13. Laura Raisa Miloş & Cornel Haţiegan & Marius Cristian Miloş & Flavia Mirela Barna & Claudiu Boțoc, 2020. "Multifractal Detrended Fluctuation Analysis (MF-DFA) of Stock Market Indexes. Empirical Evidence from Seven Central and Eastern European Markets," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
    14. Itoh, Eri & Mitici, Mihaela, 2020. "Analyzing tactical control strategies for aircraft arrivals at an airport using a queuing model," Journal of Air Transport Management, Elsevier, vol. 89(C).
    15. Gwiggner, Claus & Nagaoka, Sakae, 2014. "Data and queueing analysis of a Japanese air-traffic flow," European Journal of Operational Research, Elsevier, vol. 235(1), pages 265-275.
    16. Liu, Hongzhi & Zhang, Xingchen & Zhang, Xie, 2020. "Multiscale multifractal analysis on air traffic flow time series: A single airport departure flight case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    17. Michael D. Peterson & Dimitris J. Bertsimas & Amedeo R. Odoni, 1995. "Models and Algorithms for Transient Queueing Congestion at Airports," Management Science, INFORMS, vol. 41(8), pages 1279-1295, August.
    18. Zhang, Xie & Liu, Hongzhi & Zhao, Yifei & Zhang, Xingchen, 2019. "Multifractal detrended fluctuation analysis on air traffic flow time series: A single airport case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    19. Dube, Kaitano & Nhamo, Godwell & Chikodzi, David, 2021. "COVID-19 pandemic and prospects for recovery of the global aviation industry," Journal of Air Transport Management, Elsevier, vol. 92(C).
    20. Abdel-Aty, Mohamed & Lee, Chris & Bai, Yuqiong & Li, Xin & Michalak, Martin, 2007. "Detecting periodic patterns of arrival delay," Journal of Air Transport Management, Elsevier, vol. 13(6), pages 355-361.
    21. Scarpel, Rodrigo Arnaldo, 2014. "A demand trend change early warning forecast model for the city of São Paulo multi-airport system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 23-32.
    22. Tu, Yufeng & Ball, Michael O. & Jank, Wolfgang S., 2008. "Estimating Flight Departure Delay DistributionsA Statistical Approach With Long-Term Trend and Short-Term Pattern," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 112-125, March.
    23. Ioannis Simaiakis & Hamsa Balakrishnan, 2016. "A Queuing Model of the Airport Departure Process," Transportation Science, INFORMS, vol. 50(1), pages 94-109, February.
    24. Rosselló, Jaume & Sansó, Andreu, 2017. "Yearly, monthly and weekly seasonality of tourism demand: A decomposition analysis," Tourism Management, Elsevier, vol. 60(C), pages 379-389.
    25. Öttl, Gerald & Böck, Philipp & Werpup, Nadja & Schwarze, Malte, 2013. "Derivation of representative air traffic peaks as standard input for airport related simulation," Journal of Air Transport Management, Elsevier, vol. 28(C), pages 31-39.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chandra, Aitichya & Choubey, Nipun & Verma, Ashish & Sooraj, K.P., 2024. "Quasi-stochastic optimization model for time-based arrival scheduling considering Standard Terminal Arrival (STAR) track time and a new delay-conflict relationship," Journal of Air Transport Management, Elsevier, vol. 115(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Hongzhi & Zhang, Xie & Hu, Huaqing & Zhang, Xingchen, 2022. "Exploring the impact of flow values on multiscale complexity quantification of airport flight flow fluctuations," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    2. Chen, Yunxiang & Zhao, Yifei & Wu, Yexin, 2024. "Recent progress in air traffic flow management: A review," Journal of Air Transport Management, Elsevier, vol. 116(C).
    3. Arnaldo Scarpel, Rodrigo & Pelicioni, Luciele Cristina, 2018. "A data analytics approach for anticipating congested days at the São Paulo International Airport," Journal of Air Transport Management, Elsevier, vol. 72(C), pages 1-10.
    4. Olivares, Felipe & Sun, Xiaoqian & Wandelt, Sebastian & Zanin, Massimiliano, 2023. "Measuring landing independence and interactions using statistical physics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    5. Shone, Rob & Glazebrook, Kevin & Zografos, Konstantinos G., 2019. "Resource allocation in congested queueing systems with time-varying demand: An application to airport operations," European Journal of Operational Research, Elsevier, vol. 276(2), pages 566-581.
    6. Chandra, Aitichya & Choubey, Nipun & Verma, Ashish & Sooraj, K.P., 2024. "Quasi-stochastic optimization model for time-based arrival scheduling considering Standard Terminal Arrival (STAR) track time and a new delay-conflict relationship," Journal of Air Transport Management, Elsevier, vol. 115(C).
    7. Pérez-Campuzano, Darío & Rubio Andrada, Luis & Morcillo Ortega, Patricio & López-Lázaro, Antonio, 2022. "Visualizing the historical COVID-19 shock in the US airline industry: A Data Mining approach for dynamic market surveillance," Journal of Air Transport Management, Elsevier, vol. 101(C).
    8. Birolini, Sebastian & Jacquillat, Alexandre, 2023. "Day-ahead aircraft routing with data-driven primary delay predictions," European Journal of Operational Research, Elsevier, vol. 310(1), pages 379-396.
    9. Rodríguez-Sanz, à lvaro & Comendador, Fernando Gómez & Valdés, Rosa Arnaldo & Pérez-Castán, Javier A., 2018. "Characterization and prediction of the airport operational saturation," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 147-172.
    10. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    11. Zheng, Hongfeng & Wang, Ziming & Zheng, Chuanpan & Wang, Yanjun & Fan, Xiaoliang & Cong, Wei & Hu, Minghua, 2024. "A graph multi-attention network for predicting airport delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    12. Sternberg, Alice & Carvalho, Diego & Murta, Leonardo & Soares, Jorge & Ogasawara, Eduardo, 2016. "An analysis of Brazilian flight delays based on frequent patterns," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 282-298.
    13. Gwiggner, Claus & Nagaoka, Sakae, 2014. "Data and queueing analysis of a Japanese air-traffic flow," European Journal of Operational Research, Elsevier, vol. 235(1), pages 265-275.
    14. Memon, Bilal Ahmed & Yao, Hongxing & Naveed, Hafiz Muhammad, 2022. "Examining the efficiency and herding behavior of commodity markets using multifractal detrended fluctuation analysis. Empirical evidence from energy, agriculture, and metal markets," Resources Policy, Elsevier, vol. 77(C).
    15. Lambelho, Miguel & Mitici, Mihaela & Pickup, Simon & Marsden, Alan, 2020. "Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions," Journal of Air Transport Management, Elsevier, vol. 82(C).
    16. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    17. Li, Chi & Mao, Jianfeng & Li, Lingyi & Wu, Jingxuan & Zhang, Lianmin & Zhu, Jianyu & Pan, Zibin, 2024. "Flight delay propagation modeling: Data, Methods, and Future opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    18. Liu, Hongzhi & Zhang, Xingchen & Zhang, Xie, 2020. "Multiscale multifractal analysis on air traffic flow time series: A single airport departure flight case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    19. Chen, Zhenhua & Wang, Yuxuan & Zhou, Lei, 2021. "Predicting weather-induced delays of high-speed rail and aviation in China," Transport Policy, Elsevier, vol. 101(C), pages 1-13.
    20. Zhan, Cun & Liang, Chuan & Zhao, Lu & Zhang, Yaling & Cheng, Long & Jiang, Shouzheng & Xing, Liwen, 2021. "Multifractal characteristics analysis of daily reference evapotranspiration in different climate zones of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:615:y:2023:i:c:s0378437123001450. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.