TR2018-172

Positive Invariant Sets for Safe Integrated Vehicle Motion Planning and Control


This paper describes a method for real-time integrated motion planning and control of autonomous vehicles. Our method leverages feedback control, positive invariant sets, and equilibrium trajectories of the closed-loop system to guarantee collision-free closed-loop trajectory tracking. Our method jointly steers the vehicle to a target region and controls the velocity while satisfying constraints associated with the future motion of the obstacles with respect to the vehicle. We develop a receding-horizon implementation and verify the method in a simulated road scenario. The results show that our method generates safe dynamically feasible trajectories while accounting for obstacles in the environment and modeling errors. In addition, the computation times indicate that the method is sufficiently efficient for real-time implementation.

 

  • Related News & Events

    •  NEWS   Stefano Di Cairano to give invited address at 3rd IAVSD Workshop on Dynamics of Road Vehicles: Connected and Automated Vehicles.
      Date: April 28, 2019
      Where: 3rd IAVSD Workshop on Dynamics of Road Vehicles: Connected and Automated Vehicles
      MERL Contact: Stefano Di Cairano
      Research Areas: Control, Optimization, Robotics
      Brief
      • Stefano Di Cairano, Distinguished Scientist and Senior Team Leader in the Control and Dynamical Systems Group, will give an invited talk entitled: "Modularity, integration and synergy in architectures for autonomous driving" that covers recent work in the lab concerning building a modular, robust control framework for autonomous driving.
    •  
    •  NEWS   MERL researcher Stefano Di Cairano taught short course for European Embedded Control Institute.
      Date: June 10, 2019 - June 14, 2019
      Where: Paris
      MERL Contact: Stefano Di Cairano
      Research Areas: Control, Dynamical Systems, Optimization
      Brief
      • MERL researcher Stefano Di Cairano and Prof. Ilya Kolmanovsky, Dept. Aerospace Engineering, the University of Michigan, were invited to teach a class on "Predictive and Optimization Based Control for Automotive and Aerospace Application" at the 2019 International Graduate School in Control, of the European Embedded Control Institute (EECI). Every year EECI invites world renown experts to teach 21-hours class modules, mostly for PhD students but also for professionals, on selected control subjects. Stefano and Ilya's class was attended by 30 "students" from both academia and industry, from all around the world, interested in automotive and aerospace control. The module described the fundamentals of modeling and control design in automotive and aerospace through lectures, real world examples and exercises, and placed particular emphasis on techniques such as MPC, reference governors, and optimal control.
    •  
  • Related Publication

  •  Berntorp, K., Danielson, C., Weiss, A., Di Cairano, S., Erliksson, K., Bai, R., "Positive Invariant Sets for Safe Integrated Vehicle Motion Planning and Control", Transactions on Intelligent Vehicles, DOI: 10.1109/TIV.2019.2955371, Vol. 5, No. 1, pp. 112-126, August 2019.
    BibTeX TR2019-086 PDF
    • @article{Berntorp2019aug,
    • author = {Berntorp, Karl and Danielson, Claus and Weiss, Avishai and Di Cairano, Stefano and Erliksson, Karl and Bai, Richard},
    • title = {Positive Invariant Sets for Safe Integrated Vehicle Motion Planning and Control},
    • journal = {Transactions on intelligent vehicles},
    • year = 2019,
    • volume = 5,
    • number = 1,
    • pages = {112--126},
    • month = aug,
    • doi = {10.1109/TIV.2019.2955371},
    • url = {https://www.merl.com/publications/TR2019-086}
    • }