Hybrid Strategy of Motion Planning with Kinematic Optimization for Autonomous Driving

Autonomous driving has revolutionized the conventional driving. In this paper, the authors present a motion planner for autonomous driving. Two main issues of motion planning are addressed in the paper: kinematical feasibility and consistence of motion control. The kinematical feasibility is achieved by a prediction engine, which generates a reference path for vehicle to follow based on vehicle kinematic model. The core of the engine is based on a differential dynamic programming (DDP) optimization. The consistence of motion control is solved by a hybrid motion planning strategy, which also considers the previous reference path in the motion planning. The proposed method is verified on the authors' autonomous vehicle platform driving on a public road and performing vehicle avoidance.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 1666-1671
  • Monograph Title: 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 2015)

Subject/Index Terms

Filing Info

  • Accession Number: 01603040
  • Record Type: Publication
  • ISBN: 9781467365956
  • Files: TRIS
  • Created Date: May 2 2016 3:20PM