End-to-end automated lane-change maneuvering considering driving style using a deep deterministic policy gradient algorithm

HIGHLIGHTS

  • who: Hongyu Hu et al. from the State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, China have published the research work: End-to-End Automated Lane-Change Maneuvering Considering Driving Style Using a Deep Deterministic Policy Gradient Algorithm, in the Journal: Sensors 2020, x of /2020/
  • what: Using a deep (DDPG) the authors propose an method for changing based on lidar data. The main research objective of this study was to design a deep deterministic policy gradient (DDPG) algorithm to control the lane-changing behavior of autonomous vehicles, and to characterize the . . .

     

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