SYSTEM AND METHOD FOR IMPROVING AN AUTONOMOUS VEHICLE DRIVING MODEL BASED ON DRIVER ENGAGEMENT CONDITIONS
Systems and methods for implementing one or more autonomous features for autonomous and semi-autonomous control of one or more vehicles are provided. More specifically, image data may be obtained from an image acquisition device and processed utilizing one or more machine learning models to identify, track, and extract one or more features of the image utilized in decision making processes for providing steering angle and/or acceleration/deceleration input to one or more vehicle controllers. In some instances, techniques may be employed such that the autonomous and semi-autonomous control of a vehicle may change between vehicle follow and lane follow modes. In some instances, at least a portion of the machine learning model may be updated based on one or more conditions.
1 . A method comprising:
receiving an indication that an autonomous driving mode has been disengaged by a user;
determining when a cumulative number of user disengagements of the autonomous driving mode, including the indication that the autonomous driving mode has been disengaged by the user, exceeds a threshold;
requesting a portion of an autonomous vehicle model based on the cumulative number of user disengagements of the autonomous driving mode exceeding the threshold; and
receiving the requested portion of the autonomous vehicle model.
2 . The method of claim 1 , wherein a user disengagement of the autonomous driving mode includes implementing at least one course correction or correcting a course deviation.
3 . The method of claim 2 , wherein a course correction includes determining that an input associated with a manual override was received.
4 . The method of claim 3 , wherein the input associated with the manual override includes one of a manual velocity change or manual steering angle change.
5 . The method of claim 2 , wherein a course deviation includes determining that a path traveled by an autonomous vehicle is different from a projected path traveled by the autonomous vehicle.
6 . The method of claim 2 , wherein the threshold varies based on one or more of time, location, date, or weather condition.
7 . The method of claim 1 , generating a second autonomous vehicle model by applying the received requested portion of the autonomous vehicle model to an existing autonomous vehicle model.
8 . The method of claim 1 , further comprising:
storing a location associated with the indication that the autonomous driving mode has been disengaged by the user.
9 . The method of claim 8 , wherein the requested portion of the autonomous vehicle model is based on the stored location.
10 . The method of claim 1 , providing the requested portion of the autonomous vehicle model to an autonomous vehicle.
11 . A system comprising:
a memory;
a processor in communication with the memory, wherein the processor executes instructions stored in the memory, which cause the processor to execute a method, the method comprising:
receiving an indication that an autonomous driving mode has been disengaged by a user;
determining when a cumulative number of user disengagements of the autonomous driving mode, including the indication that the autonomous driving mode has been disengaged by the user, exceeds a threshold;
requesting a portion of an autonomous vehicle model based on the cumulative number of user disengagements of the autonomous driving mode exceeding the threshold; and
receiving the requested portion of the autonomous vehicle model.
12 . The system of claim 11 , wherein a user disengagement of the autonomous driving mode includes implementing at least one course correction or correcting a course deviation.
13 . The system of claim 12 , wherein a course correction includes determining that an input associated with a manual override was received.
14 . The system of claim 13 , wherein the input associated with the manual override includes one of a manual velocity change or manual steering angle change.
15 . The system of claim 12 , wherein a course deviation includes determining that a path traveled by an autonomous vehicle is different from a projected path traveled by the autonomous vehicle.
16 . A non-transitory computer readable medium having stored thereon instructions, which when executed by a processor cause the processor to execute a method, the method comprising:
receiving an indication that an autonomous driving mode has been disengaged by a user;
determining when a cumulative number of user disengagements of the autonomous driving mode, including the indication that the autonomous driving mode has been disengaged by the user, exceeds a threshold;
requesting a portion of an autonomous vehicle model based on the cumulative number of user disengagements of the autonomous driving mode exceeding the threshold; and
receiving the requested portion of the autonomous vehicle model.
17 . The non-transitory computer readable medium of claim 16 , wherein a user disengagement of the autonomous driving mode includes implementing at least one course correction or correcting a course deviation.
18 . The non-transitory computer readable medium of claim 17 , wherein a course correction includes determining that an input associated with a manual override was received.
19 . The non-transitory computer readable medium of claim 18 , wherein the input associated with the manual override includes one of a manual velocity change or manual steering angle change.
20 . The non-transitory computer readable medium of claim 17 , wherein a course deviation includes determining that a path traveled by an autonomous vehicle is different from a projected path traveled by the autonomous vehicle.