..... Research Directions .....

Distributed Scheduling Algorithm in Air Traffic Flow Management

  • An extended Eulerian-Lagrangian flow model is proposed to describe the network dynamics with possibly different aircraft types
  • A quadratic integer programming problem is formulated for delay reduction under constraints of limited link capacities along with possibility of flight rerouting and diversion
  • A distributed approach and a heuristic algorithm is developed to reduce the computational complexity

References

  1. Y. Zhang, R. Su, G.G.N. Sandamali, Y. Zhang and C.G. Cassandras. “A Hierarchical Approach for Air Traffic Routing and Scheduling.” in 56th IEEE Conference on Decision and Control, 2017.
  2. Y. Zhang, R. Su, G.G.N.Sandamali, Y. Zhang, C. G. Cassandras and L. Xie. "A Hierarchical Heuristic Approach for Solving Air Traffic Scheduling and Routing Problem with a Novel Air Traffic Model." IEEE Transactions on Intelligent Transportation Systems(Aug 2017).
  3. Y. Zhang, R. Su, Q. Li, C. G. Cassandras, and L. Xie. “Distributed flight routing and scheduling in air traffic flow management.” IEEE Transactions on Intelligent Transportation Systems (2017).
  4. Y. Zhang, R. Su, Q. Li, C. G. Cassandras, and L. Xie. “Distributed Flight Routing and Scheduling in Air Traffic Flow Management.” In Decision and Control (CDC), 2016 IEEE 55th Conference on, pp. 1080-1085. (2016).
  5. Y. Zhang, Q. Li, and R. Su. “Sector-based Distributed Scheduling Strategy in Air Traffic Flow Management.” IFAC-PapersOnLine 49, no. 3: 365-370. (2016)
  6. Q. Li, Y. Zhang, and R. Su. “A Flow-based Flight Scheduler for En-route Air Traffic Management.” IFAC-PapersOnLine 49, no. 3: 353-358. (2016)

Flight Trajectories Generation

  • A model aims at optimizing flight plan for the traffic system, i.e. assign route and schedule for individual aircraft
  • With considerations of Dispatching constraint, Sequence constraint, Separation constraint, Capacity constraint Speed constraint

References

  1. Q. Li, Y. Zhang, and R. Su. “A Flow-based Flight Scheduler for En-route Air Traffic Management.” IFAC-PapersOnLine 49, no. 3: 353-358. (2016)

Fixed time multi-party cluster consensus in Air Traffic Network

  • Intend to design a finite time consensus protocol for an air traffic network
  • Higher level control strategy will provide us routine and scheduling of the aircrafts
  • Different way points in a network we will have a fixed arrival time
  • The objective is to design a distributed fixed time multi-party consensus algorithm to support the routine and scheduling
  • Consensus will help to maintain a fixed safe separation while crossing the way points at specified time
  • Fixed time consensus will enable to design point graph to realize an air traffic network

References

  1. F. A. Yaghmaie, R. Su, F. L. Lewis, L. Xie. “Multi-party consensus of linear heterogeneous multi-agent systems.” IEEE Transactions on Automatic Control (2017).
  2. S. Mondal, R. Su, and L. Xie. “Heterogeneous consensus of higher‐order multi‐agent systems with mismatched uncertainties using sliding mode control.” International Journal of Robust and Nonlinear Control (2016).
  3. S. Mondal, and R. Su. “Finite time tracking control of higher order nonlinear multi agent systems with actuator saturation.” IFAC-PapersOnLine 49, no. 3: 165-170. (2016).
  4. S. Mondal, and R. Su. “Disturbance observer based consensus control for higher order multi-agent systems with mismatched uncertainties.” In American Control Conference (ACC), 2016, pp. 2826-2831. (2016).

Sector or En-route Capacity Estimation

  • Air traffic capacity is estimated from AirTOp simulation data
  • Proposed methodology will be extended to the experimental flight data to predict the air traffic capacity
  • Developed the capacity model building algorithm in MATLAB

Flight Routing and Scheduling with Uncertainties

  • Proposed a flight routing and scheduling algorithm while considering demand uncertainty due to departure deviation
  • Considered each flight’s maximum possible existence on the route to eliminate the capacity violation completely from the system (Robust Optimization)
  • Developing a new model for flight routing and scheduling under departure and en-route speed uncertainty with optimum flight level assignment

References

  1. G. G. N. Sandamali, R. Su, Y. Zhang, and Q. Li, “Flight Routing and Scheduling with Departure Uncertainties in Air Traffic Flow Management” in IEEE 13th International Conference on Control and Automation (ICCA) (2017).

Simulation Package Design

  • Combined the ATFM, flight trajectories generation module with simulation platform
  • Developed based on AirTOp, a real-time air traffic simulator
 

..... Demos .....

Air Traffic Flow Management Simulation on AirTOp platform

Simulation shown during our presentation at CDC’16, Las Vegas, Dec 2016