Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints

A path planning and tracking framework is presented to maintain a collision-free path for autonomous vehicles. For path-planning approaches, a 3-D virtual dangerous potential field is constructed as a superposition of trigonometric functions of the road and the exponential function of obstacles, which can generate a desired trajectory for collision avoidance when a vehicle collision with obstacles is likely to happen. Next, to track the planned trajectory for collision avoidance maneuvers, the path-tracking controller formulated the tracking task as a multiconstrained model predictive control (MMPC) problem and calculated the front steering angle to prevent the vehicle from colliding with a moving obstacle…

• NN
  National Natural Science Foundation of China

  Award: 61304189
• NS
  Natural Sciences and Engineering Research Council of Canada
• FR
  Fundamental Research Funds for the Central Universities

  Award: XDJK2015B028