A distributionally robust optimization model for vehicle platooning under stochastic disturbances

HIGHLIGHTS

• What: The aims of this study are to develop a DRMPC modelling framework for vehicle platooning when V2V communication has stochastic noise and to improve driving safety, string stability, and robustness of a string of autonomous vehicles in an uncertain communication environment. To demonstrate the efficacy of the control method, the authors compare the performance of the DRMPC, NMPC, RMPC, and SMPC algorithms in uncertain scenarios for vehicle platoon control. To improve the robustness of the system, the authors propose the DRMPC controller to cope with the effect of random perturbations on the formation system. As shown . . .
  

   

  

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