MODEL-BASED STRUCTURED DATA FILTERING IN AN AUTONOMOUS VEHICLE
Model-based structured data filtering in an autonomous vehicle may include acquiring sensor data from a plurality of sensors of the autonomous vehicle; applying, based on one or more machine-learning models, one or more filtering operations to the sensor data; and transmitting the filtered sensor data to a server.
1 . A method for model-based structured data filtering in an autonomous vehicle, comprising:
acquiring sensor data from a plurality of sensors of the autonomous vehicle;
applying, based on one or more machine learning models, one or more filtering operations to the sensor data; and
transmitting the filtered sensor data to a server.
2 . The method of claim 1 , further comprising:
storing the acquired sensor data; and
wherein applying the one or more filtering operations to the sensor comprises applying the one or more filtering operations to the stored sensor data.
3 . The method of claim 2 , wherein applying the one or more filtering operations to the stored sensor data comprises applying, in response to an amount of used storage space meeting a threshold, the one or more filtering operations to the stored sensor data.
4 . The method of claim 2 , wherein applying the one or more filtering operations to the stored sensor data comprises applying, in response to the autonomous vehicle entering a stationary mode, the one or more filtering operations to the stored sensor data.
5 . The method of claim 1 , further comprising:
receiving an update to the one or more machine learning models;
acquiring additional sensor data;
applying the updated one or more machine learning models to the additional sensor data; and
transmitting the filtered additional sensor data to the server.
6 . The method of claim 1 , wherein applying the one or more filtering operations comprises modifying a fidelity of at least a portion of the sensor data.
7 . The method of claim 1 , wherein applying the one or more filtering operations comprises excluding, from the filtered sensor data, at least a portion of the sensor data.
8 . The method of claim 1 , further comprising determining, based on another one or more machine learning models, whether to repress storing at least a portion of the sensor data.
9 . An apparatus for model-based structured data filtering in an autonomous vehicle, the apparatus configured to perform steps comprising:
acquiring sensor data from a plurality of sensors of the autonomous vehicle;
applying, based on one or more machine learning models, one or more filtering operations to the sensor data; and
transmitting the filtered sensor data to a server.
10 . The apparatus of claim 9 , wherein the steps further comprise:
storing the acquired sensor data; and
wherein applying the one or more filtering operations to the sensor comprises applying the one or more filtering operations to the stored sensor data.
11 . The apparatus of claim 9 , wherein the steps further comprise:
receiving an update to the one or more machine learning models;
acquiring additional sensor data;
applying the updated one or more machine learning models to the additional sensor data; and
transmitting the filtered additional sensor data to the server.
12 . The apparatus of claim 9 , wherein applying the one or more filtering operations comprises modifying a fidelity of at least a portion of the sensor data.
13 . The apparatus of claim 9 , wherein applying the one or more filtering operations comprises excluding, from the filtered sensor data, at least a portion of the sensor data.
14 . The apparatus of claim 9 , wherein the steps further comprise determining, based on another one or more machine learning models, whether to repress storing at least a portion of the sensor data.
15 . An autonomous vehicle for model-based structured data filtering in an autonomous vehicle, the autonomous vehicle comprising apparatus configured to perform steps comprising:
acquiring sensor data from a plurality of sensors of the autonomous vehicle;
applying, based on one or more machine learning models, one or more filtering operations to the sensor data; and
transmitting the filtered sensor data to a server.
16 . The autonomous vehicle of claim 15 , wherein the steps further comprise:
storing the acquired sensor data; and
wherein applying the one or more filtering operations to the sensor comprises applying the one or more filtering operations to the stored sensor data.
17 . The autonomous vehicle of claim 16 , wherein applying the one or more filtering operations to the stored sensor data comprises applying, in response to the autonomous vehicle entering a stationary mode, the one or more filtering operations to the stored sensor data.
18 . The autonomous vehicle of claim 15 , wherein the steps further comprise:
receiving an update to the one or more machine learning models;
acquiring additional sensor data;
applying the updated one or more machine learning models to the additional sensor data; and
transmitting the filtered additional sensor data to the server.
19 . The autonomous vehicle of claim 15 , wherein the steps further comprise determining, based on another one or more machine learning models, whether to repress storing at least a portion of the sensor data.
20 . A computer program product disposed upon a non-transitory computer readable medium, the computer program product comprising computer program instructions for model-based structured data filtering in an autonomous vehicle that, when executed, cause a computer system to carry out the steps of:
acquiring sensor data from a plurality of sensors of the autonomous vehicle;
applying, based on one or more machine learning models, one or more filtering operations to the sensor data; and
transmitting the filtered sensor data to a server.