Highly localized weather data recorded by vehicles in a fleet

1. A non-transitory computer readable medium comprising instructions, the instructions, when executed by a computing system, cause the computing system to:

receive a plurality of weather data samples from a plurality of vehicles in a fleet, the weather data samples taken from a plurality of locations within a geographic area with one or more sensors of the plurality of vehicles comprising at least one of a thermometer, a humidity sensor, an air quality sensor, an air pressure sensor, a windspeed sensor, and an altimeter sensor;

classify current weather conditions in each of the plurality of locations in the geographic area based on the weather data samples;

determine a confidence score of the classification of the current weather conditions based on at least one of input from a mobile device associated with a passenger of the plurality of vehicles in the fleet, operational data provided by the plurality of vehicles in the fleet, and input from a human operator associated with the plurality of vehicles in the fleet, wherein the confidence score of the classification determines an overall certainty in the classification of the current weather conditions; and

in response to a determination that the confidence score satisfies a reliability of the classification of the current weather conditions, adjust at least one driving parameter for at least one vehicle from among the plurality of vehicles in the fleet based on the classification of the weather conditions, wherein a planned route of the at least one vehicle from among the plurality of vehicles comprises at least one location of the plurality of locations within the geographic area and the at least one driving parameter controls a deceleration or a direction of movement of the at least one vehicle from among the plurality of vehicles.

2. The non-transitory computer readable medium of claim 1 , wherein the at least one driving parameter comprises a braking parameter, a driving parameter, or a combination thereof.

3. The non-transitory computer readable medium of claim 1 , wherein the instructions, when executed by a computing system, cause the computing system to:

calculate a route for the at least one vehicle based on the current weather conditions.

4. The non-transitory computer readable medium of claim 1 , wherein the instructions, when executed by a computing system, cause the computing system to:

predict weather conditions for one or more of the plurality of locations at a future time based on the current weather conditions.

5. The non-transitory computer readable medium of claim 1 , wherein the instructions, when executed by a computing system, cause the computing system to:

transmit the classification of current weather conditions to a mobile device associated with a passenger; and

receive a confirmation of the classification of current weather conditions from the mobile device associated with the passenger.

6. The non-transitory computer readable medium of claim 1 , wherein the plurality of weather data samples comprises one or more measurements taken using a thermometer, a humidity sensor, a rain sensor, or a combination thereof.

7. The non-transitory computer readable medium of claim 1 , wherein the fleet comprises one or more autonomous vehicle (AV).

8. A computer-implemented method for classifying weather conditions, the method comprising:

receiving a plurality of weather data samples from a plurality of vehicles in a fleet, the weather data samples taken from a plurality of locations within a geographic area with one or more sensors of the plurality of vehicles comprising at least one of a thermometer, a humidity sensor, an air quality sensor, an air pressure sensor, a windspeed sensor, and an altimeter sensor;

classifying current weather conditions in each of the plurality of locations in the geographic area based on the weather data samples;

determining a confidence score of the classification of the current weather conditions based on at least one of input from a mobile device associated with a passenger of the plurality of vehicles in the fleet, operational data provided by the plurality of vehicles in the fleet, and input from a human operator associated with the plurality of vehicles in the fleet, wherein the confidence score of the classification determines an overall certainty in the classification of the current weather conditions; and

in response to a determination that the confidence score satisfies a reliability of the classification of the current weather conditions, adjusting at least one driving parameter for at least one vehicle from among the plurality of vehicles in the fleet based on the classification of the weather conditions, wherein a planned route of the at least one vehicle from among the plurality of vehicles comprises at least one location of the plurality of locations within the geographic area and the at least one driving parameter controls a deceleration or a direction of movement of the at least one vehicle from among the plurality of vehicles.

9. The computer-implemented method of claim 8 , wherein the at least one driving parameter comprises a braking parameter, a driving parameter, or a combination thereof.

10. The computer-implemented method of claim 8 , further comprising:

calculating a route for the at least one vehicle based on the current weather conditions.

11. The computer-implemented method of claim 8 , further comprising:

predicting weather conditions for one or more of the plurality of locations at a future time based on the current weather conditions.

12. The computer-implemented method of claim 8 , further comprising:

transmitting the classification of current weather conditions to a mobile device associated with a passenger; and

receiving a confirmation of the classification of current weather conditions from the mobile device associated with the passenger.

13. The computer-implemented method of claim 8 , wherein the plurality of weather data samples comprises one or more measurements taken using a thermometer, a humidity sensor, a rain sensor, or a combination thereof.

14. The computer-implemented method of claim 8 , wherein the fleet comprises one or more autonomous vehicle (AV).

15. A system for classifying weather conditions, comprising:

at least one memory; and

at least one processor coupled to the at least one memory, the at least one processor configured to:

receive a plurality of weather data samples from a plurality of vehicles in a fleet, the weather data samples taken from a plurality of locations within a geographic area with one or more sensors of the plurality of vehicles comprising at least one of a thermometer, a humidity sensor, an air quality sensor, an air pressure sensor, a windspeed sensor, and an altimeter sensor;

classify current weather conditions in each of the plurality of locations in the geographic area based on the weather data samples;

determine a confidence score of the classification of the current weather conditions based on at least one of input from a mobile device associated with a passenger of the plurality of vehicles in the fleet, operational data provided by the plurality of vehicles in the fleet, and input from a human operator associated with the plurality of vehicles in the fleet, wherein the confidence score of the classification determines an overall certainty in the classification of the current weather conditions; and

in response to a determination that the confidence score satisfies a reliability of the classification of the current weather conditions, adjust at least one driving parameter for at least one vehicle from among the plurality of vehicles in the fleet based on the classification of the weather conditions, wherein a planned route of the at least one vehicle from among the plurality of vehicles comprises at least one location of the plurality of locations within the geographic area and the at least one driving parameter controls a deceleration or a direction of movement of the at least one vehicle from among the plurality of vehicles.

16. The system of claim 15 , wherein the at least one driving parameter comprises a braking parameter, a driving parameter, or a combination thereof.

17. The system of claim 15 , wherein the at least one processor is further configured to:

calculate a route for the at least one vehicle based on the current weather conditions.

18. The system of claim 15 , wherein the at least one processor is further configured to:

predict weather conditions for one or more of the plurality of locations at a future time based on the current weather conditions.

19. The system of claim 15 , wherein the at least one processor is further configured to:

transmit the classification of current weather conditions to a mobile device associated with a passenger; and

receive a confirmation of the classification of current weather conditions from the mobile device associated with the passenger.

20. The system of claim 15 , wherein the plurality of weather data samples comprises one or more measurements taken using a thermometer, a humidity sensor, a rain sensor, or a combination thereof.