US 12,377,871 B2
Scheduling state transitions in an autonomous vehicle
John Hayes, Mountain View, CA (US); and Volkmar Uhlig, Cupertino, CA (US)
Assigned to Applied Intuition, Inc., Mountain View, CA (US)
Filed by GHOST AUTONOMY INC., Mountain View, CA (US)
Filed on Mar. 30, 2022, as Appl. No. 17/708,588.
Claims priority of provisional application 63/167,898, filed on Mar. 30, 2021.
Prior Publication US 2022/0315041 A1, Oct. 6, 2022
Int. Cl. B60W 60/00 (2020.01); G06N 20/00 (2019.01)
CPC B60W 60/001 (2020.02) [G06N 20/00 (2019.01); B60W 2420/403 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
detecting a transition signal for transitioning from a first state associated with a first machine learning model to a second state associated with a second machine learning model, wherein an autonomous vehicle is configured to use the first machine learning model instead of the second machine learning model when in the first state, and wherein the autonomous vehicle is configured to use the second machine learning model instead of the first machine learning model when in the second state;
detecting, subsequent to detecting the transition signal, that a precondition for generating output by the second machine learning model is unsatisfied, wherein the precondition comprises a predefined number of frames of image data input to the second machine learning model; and
delaying, until the precondition for generating output by the second machine learning model is satisfied, use of the second machine learning model instead of the first machine learning model by delaying a transition from the first state to the second state.