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Physical model and machine learning combined method to simulate autonomous vehicle movement

  • US 10,343,685 B2
  • Filed: 09/28/2016
  • Issued: 07/09/2019
  • Est. Priority Date: 09/28/2016
  • Status: Active Grant
First Claim
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1. A computer-implemented method for operating an autonomous vehicle, the method comprising:

  • identifying a driving scenario of the autonomous vehicle for a next movement, wherein the driving scenario is represented by a set of one or more predetermined parameters;

    calculating a first next movement of the autonomous vehicle under the driving scenario using a physical model;

    generating planning and control data based on the first next movement, the planning and control data describing a path to drive the autonomous vehicle from a first point to a second point;

    applying a sideslip predictive model to the set of predetermined parameters to determine a sideslip of the autonomous vehicle given a set of driving conditions, the sideslip representing a difference between a first position of the autonomous vehicle and a second position of the autonomous vehicle, wherein the first position is an expected position of the autonomous vehicle calculated using the physical model and the set of predetermined parameters, and wherein the second position is a position where the autonomous vehicle actually ends up due to the set of driving conditions;

    determining a second next movement of the autonomous vehicle based on the first next movement and the determined sideslip of the autonomous vehicle, including adjusting at least one position within the path between the first point and the second point based on the determined sideslip of the autonomous vehicle;

    modifying the planning and control data based on the second next movement; and

    controlling and driving the autonomous vehicle from the first point to the second point according to the path based on the modified planning and control data.

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