| CPC G05D 1/0231 (2013.01) [B60R 11/04 (2013.01); G05D 1/027 (2013.01); G05D 1/0276 (2013.01); G05D 1/0278 (2013.01); G05D 1/245 (2024.01); G05D 1/247 (2024.01); G05D 1/248 (2024.01); G05D 1/249 (2024.01); G06F 13/4282 (2013.01); B60R 2011/004 (2013.01); B60R 2011/0068 (2013.01); B60R 2011/007 (2013.01); G06F 2213/0002 (2013.01)] | 18 Claims |

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1. A method of collecting diverse driving data, the method comprising:
for each of a plurality of removable pods each respectively attached to a unique vehicle in an environment:
collecting respective environmental data of the environment using one or more sensors of a respective removable pod,
recording the respective environmental data collected using the respective removable pod and corresponding vehicle data that corresponds to the respective environmental data,
determining time stamps for each instance of the respective environmental data and time stamps for each instance of the corresponding vehicle data using a respective computing device connected to the respective removable pod,
generating a respective aggregation of the time stamped instances of the respective environmental data and the time stamped instances of the corresponding vehicle data using the respective computing device, and
transmitting, to a remote server, the respective aggregation of the time stamped instances of the respective environmental data and the time stamped instances of the corresponding vehicle data;
aggregating, at the remote server, the time stamped instances of vehicle data and environmental data from the plurality of removable pods,
wherein each of the unique vehicles is attached to at least one removable pod;
generating training data for a machine learning model based on the time stamped instances of vehicle data and environmental data from the plurality of removable pods; and
training, based on the training data, the machine learning model, to generate control signals for an autonomous vehicle.
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