Real-time vehicle accident prediction, warning, and prevention

1. A method for a first vehicle to detect a future vehicle accident, the method comprising:

accessing an accident profile of a second vehicle, wherein the accident profile contains data indicating vehicle operating parameters during a prior vehicle accident;

collecting current vehicle operating parameters from the first vehicle and the second vehicle, the current vehicle operating parameters being collected in real time;

based on a comparison between the current vehicle operating parameters and the accident profile of the second vehicle, determine a probability of the future vehicle accident; and

implementing preventive action responsive to the probability of the future vehicle accident exceeds a probability threshold;

wherein implementing preventive action responsive to the probability of the future vehicle accident exceeds the probability threshold comprises at least one of: generating an alert for occupants of the second vehicle; and controlling one or more operational systems of first vehicle to prevent the future vehicle accident.

2. The method of claim 1 , wherein controlling one or more of the operational systems of the first vehicle to prevent the future vehicle accident comprises at least one of: slowing the first vehicle; altering a path of the first vehicle; and stopping the first vehicle.

3. The method of claim 1 ,

wherein the current vehicle operating parameters are data collected in real time.

4. The method of claim 1 , further comprising:

identifying a driver of the second vehicle;

accessing a driver profile for the driver, wherein the driver profile represents a history of the driver; and

comparing the driver profile and data collected in real time to determine the probability of the future vehicle accident.

5. The method of claim 1 , further comprising:

collecting, in real time, from the second vehicle, data describing environment parameters of the second vehicle;

comparing data collected in real time with the data describing environment parameters of the second vehicle to determine the probability of the future vehicle accident.

6. The method of claim 1 , further comprising generating one or more accident profiles, the generating comprising:

for each of a plurality of accidents, receiving and storing sensor data from a plurality of vehicle sensors indicating values of vehicle operating parameters during each accident;

applying a machine learning algorithm to the data to identify the vehicle operating parameters and values that are indicative of the accident; and

generating a profile representing the identified vehicle operating parameters and values.

7. A first vehicle comprising: a processor; and a non-transitory machine-readable storage medium encoded with instructions executable by the processor, the machine-readable storage medium comprising instructions to cause the processor to perform a method comprising:

accessing an accident profile of a second vehicle, wherein the accident profile contains data indicating vehicle operating parameters during a prior vehicle accident;

collecting current vehicle operating parameter from the first vehicle and the second vehicle, the current vehicle operating parameters being collected in real time;

based on a comparison between the current vehicle operating parameters and the accident profile of the second vehicle, determine a probability of a future vehicle accident; and

implementing preventive action responsive to the probability of a future vehicle accident exceeds a probability threshold;

wherein implementing preventive action responsive to the probability of the future vehicle accident exceeds the probability threshold comprises at least one of: generating an alert for occupants of the second vehicle; and controlling one or more operational systems of the first vehicle to prevent the future vehicle accident.

8. The first vehicle of claim 7 , wherein controlling one or more of the operational systems of the first vehicle to prevent the future vehicle accident comprises at least one of: slowing the first vehicle; altering a path of the first vehicle; and stopping the first vehicle.

9. The first vehicle of claim 7 , wherein

the current vehicle operating parameters are data collected in real time.

10. The first vehicle of claim 7 , wherein the method further comprises:

identifying a driver of the second vehicle;

accessing a driver profile for the driver, wherein the driver profile represents a history of the driver; and

comparing the driver profile and data collected in real time to determine the probability of the future vehicle accident.

11. The first vehicle of claim 7 , wherein the method further comprises:

collecting, in real time, from the second vehicle, data describing environment parameters of the second vehicle; and

comparing data collected in real time with the data describing environment parameters of the second vehicle to determine the probability of the future vehicle accident.

12. A non-transitory machine-readable storage medium encoded with instructions executable by a hardware processor of a computing component of a first vehicle, the machine-readable storage medium comprising instructions to cause the hardware processor to perform a method comprising:

accessing an accident profile of a second vehicle, wherein the accident profile contains data indicating vehicle operating parameters during a prior vehicle accident;

collecting current vehicle operating parameter from the first vehicle and the second vehicle, the current vehicle operating parameters being collected in real time;

based on a comparison between the current vehicle operating parameters and the accident profile of the second vehicle, determine a probability of a future vehicle accident; and

implementing preventive action responsive to the probability of a future vehicle accident exceeds a probability threshold;

wherein implementing preventive action responsive to the probability of the future vehicle accident exceeds the probability threshold comprises at least one of: generating an alert for occupants of the second vehicle; and controlling one or more operational systems of the second vehicle to prevent the future vehicle accident.

13. The medium of claim 12 , wherein controlling one or more of the operational systems of the first vehicle to prevent the future vehicle accident comprises at least one of: slowing the first vehicle; altering a path of the first vehicle; and stopping the first vehicle.

14. The medium of claim 12 , wherein

the current vehicle operating parameters are data collected in real time.

15. The medium of claim 12 , wherein the method further comprises:

identifying a driver of the second vehicle;

accessing a driver profile for the driver, wherein the driver profile represents a history of the driver; and

comparing the driver profile and data collected in real time to determine the probability of the future vehicle accident.

16. The medium of claim 12 , wherein the method further comprises:

collecting, in real time, from the first vehicle, data describing environment parameters of the first vehicle;

comparing data collected in real time with the data describing environment parameters of the second vehicle to determine the probability of the future vehicle accident.

17. The medium of claim 12 , wherein the method further comprises generating one or more accident profiles, the generating comprising:

for each of a plurality of accidents, receiving and storing sensor data from a plurality of vehicle sensors indicating values of vehicle operating parameters during each accident;

applying a machine learning algorithm to the data to identify the vehicle operating parameters and values that are indicative of the accident; and

generating a profile representing the identified vehicle operating parameters and values.