TR2024-079

Aircraft Approach Management using Reachability and Dynamic Programming

    •  Vinod, A.P., Yamazaki, S., Chakrabarty, A., Yoshikawa, N., Di Cairano, S., "Aircraft Approach Management using Reachability and Dynamic Programming", American Control Conference (ACC), June 2024.
      BibTeX TR2024-079 PDF
      • @inproceedings{Vinod2024jun,
      • author = {{Vinod, Abraham P. and Yamazaki, Sachiyo and Chakrabarty, Ankush and Yoshikawa, Nobuyuki and Di Cairano, Stefano}},
      • title = {Aircraft Approach Management using Reachability and Dynamic Programming},
      • booktitle = {American Control Conference (ACC)},
      • year = 2024,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2024-079}
      • }
  • MERL Contacts:
  • Research Areas:

    Control, Dynamical Systems, Machine Learning, Optimization

Abstract:

We study the problem of designing safe trajectories for aircraft approach management. Our tractable method designs aircraft trajectories that 1) use only limited admissible maneuvers near the airport, 2) maintains a user-specified separation between aircraft during the entire duration of the approach, and 3) minimizes deviations from user-specified times of arrival at the airport. We use a first-come, first-serve frame- work to design the trajectories for multiple aircraft by solving a collection of single-aircraft trajectory planning problems. We ensure the safety of the overall system by imposing reachability- based constraints on each planning problem. We identify the constraints as well as the trajectories for aircraft using dynamic programming in a three-dimensional space. We validate the efficacy and safety of our method using historical data from Japan’s Haneda International Airport.

 

  • Related News & Events

    •  NEWS    MERL researchers present 9 papers at ACC 2024
      Date: July 10, 2024 - July 12, 2024
      Where: Toronto, Canada
      MERL Contacts: Karl Berntorp; Ankush Chakrabarty; Vedang M. Deshpande; Stefano Di Cairano; Christopher R. Laughman; Arvind Raghunathan; Abraham P. Vinod; Yebin Wang; Avishai Weiss
      Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics
      Brief
      • MERL researchers presented 9 papers at the recently concluded American Control Conference (ACC) 2024 in Toronto, Canada. The papers covered a wide range of topics including data-driven spatial monitoring using heterogenous robots, aircraft approach management near airports, computation fluid dynamics-based motion planning for drones facing winds, trajectory planning for coordinated monitoring using a team of drones and a ground carrier vehicle, ensemble Kalman smoothing-based model predictive control for motion planning for autonomous vehicles, system identification for Lithium-ion batteries, physics-constrained deep Kalman filters for vapor compression systems, switched reference governors for constrained systems, and distributed road-map monitoring using onboard sensors.

        As a sponsor of the conference, MERL maintained a booth for open discussions with researchers and students, and hosted a special session to discuss highlights of MERL research and work philosophy.

        In addition, Abraham Vinod served as a panelist at the Student Networking Event at the conference. The student networking event provides an opportunity for all interested students to network with professionals working in industry, academia, and national laboratories during a structured event, and encourages their continued participation as the future leaders in the field.
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