Modeling and Control of Queuing Networks

Long queues of aircraft taxiing on the surface contribute significantly to the fuel burn and emissions at airports. Motivated by the problem of airport surface congestion, we develop data-driven modeling approaches for queuing networks, and use them to build congestion management algorithms.

Hamsa Balakrishnan

Collaborators/alums: Sandeep Badrinath, Harshad Khadilkar, Ioannis Simaiakis, Emily Joback, Tom Reynolds

  1. S. Badrinath and H. Balakrishnan. “Robust Control of Arrivals into a Queuing Network,” IEEE Transactions on Intelligent Transportation Systems, Early Access, January 2021. [pdf]
  2. S. Badrinath, H. Balakrishnan, J. Ma, and D. Delahaye. “Comparative Analysis of Departure Metering at United States and European Airports,” AIAA Journal of Air Transportation, Vol. 28, No. 3, pp. 93-104, July-September 2020. [pdf]
  3. S. Badrinath, H. Balakrishnan, E. Joback, and T.G. Reynolds. “Impact of Uncertainty on the Control of Airport Surface Operations,” Transportation Science, Vol. 54, No. 4, pp. 920-943, July-August 2020. [pdf]
  4. I. Simaiakis and H. Balakrishnan. “A Queuing Model of the Airport Departure Process,” Transportation Science, Vol. 50, No. 1, pp. 94-109, February 2016. [pdf]
  5. I. Simaiakis, H. Khadilkar, H. Balakrishnan, T. G. Reynolds, and R. J. Hansman. “Demonstration of Reduced Airport Congestion through Pushback Rate Control,” Transportation Research Part A: Policy and Practice, Vol. 66, August 2014. [pdf]
  6. H. Khadilkar and H. Balakrishnan, “Network Congestion Control of Airport Surface Operations,” AIAA Journal of Guidance, Control and Dynamics, Vol. 37, No. 3, pp. 933-940, May-June 2014. [pdf]
  7. H. Khadilkar and H. Balakrishnan, “Metrics to Characterize Airport Operational Performance Using Surface Surveillance Data,” Air Traffic Control Quarterly, Vol. 21, No. 2, July 2013. [pdf]