Systems and methods for delivering vehicle-specific educational content for a critical event

1. A method comprising:

receiving, by a first computing device having at least one processor and from a user device of a vehicle user via a wireless data connection, a notification identifying a vehicle of the vehicle user, a vehicle identification of the vehicle, and a critical event;

determining, by the first computing device and based on the received notification, a set of parameters associated with the vehicle user;

creating a feature-vector for the vehicle user based on the set of parameters;

selecting educational content for the new vehicle user from a list of educational content based on the created feature-vector, wherein the selected educational content is a subset of the list of educational content; and

recording the subset of the educational content selected for the vehicle user in a selection repository in memory.

2. The method of claim 1 , wherein selecting the educational content is based on inputting the created feature-vector into a trained machine learning algorithm.

3. The method of claim 2 , further comprising training the machine learning algorithm to predict educational content based on parameters regarding vehicles and critical events.

4. The method of claim 3 , wherein training the machine learning algorithm is based on one or more feature-vectors associated with one or more other vehicle users and educational content selected by the respective other vehicle user.

5. The method of claim 4 , further comprising storing in memory of the first computing device the one or more feature-vectors associated with the one or more other vehicle users.

6. The method of claim 1 , further comprising receiving vehicle information from a telematics system of the vehicle, wherein creating the feature-vector for the vehicle user is further based on the vehicle information received from the telematics system of the vehicle.

7. The method of claim 1 , wherein determining the set of parameters includes using the machine learning algorithm to predict the set of parameters.

8. The method of claim 1 , further comprising generating a display that includes a link to the educational content selected for the vehicle user.

9. A system comprising:

a communication interface that communicates via a wireless data connection to receive a notification identifying a vehicle of the vehicle user, a vehicle identification of the vehicle, and a critical event; and

a processor that executes instructions stored in memory, wherein the processor executes the instructions to:

determine, by the first computing device and based on the received notification, a set of parameters associated with the vehicle user;

create a feature-vector for the vehicle user based on the set of parameters;

select educational content for the new vehicle user from a list of educational content based on the created feature-vector, wherein the selected educational content is a subset of the list of educational content; and

recording the subset of the educational content selected for the vehicle user in a selection repository in memory.

10. The system of claim 9 , wherein the processor selects the educational content based on inputting the created feature-vector into a trained machine learning algorithm.

11. The system of claim 10 , wherein the processor executes further instructions to train the machine learning algorithm to predict educational content based on parameters regarding vehicles and critical events.

12. The system of claim 11 , wherein the processor trains the machine learning algorithm based on one or more feature-vectors associated with one or more other vehicle users and educational content selected by the respective other vehicle user.

13. The system of claim 12 , further comprising memory that stores the one or more feature-vectors associated with the one or more other vehicle users.

14. The system of claim 9 , wherein the communication interface further receives vehicle information from a telematics system of the vehicle, wherein the processor creates the feature-vector for the vehicle user further based on the vehicle information received from the telematics system of the vehicle.

15. The system of claim 9 , wherein the processor determines the set of parameters by using the machine learning algorithm to predict the set of parameters.

16. The system of claim 9 , wherein the processor generates a display that includes a link to the educational content selected for the vehicle user.

17. A non-transitory, computer-readable storage medium, having embodied thereon a program executable by a processor to perform a method comprising:

receiving, by a first computing device having at least one processor and from a user device of a vehicle user via a wireless data connection, a notification identifying a vehicle of the vehicle user, a vehicle identification of the vehicle, and a critical event;

determining, by the first computing device and based on the received notification, a set of parameters associated with the vehicle user;

creating a feature-vector for the vehicle user based on the set of parameters;

selecting educational content for the new vehicle user from a list of educational content based on the created feature-vector, wherein the selected educational content is a subset of the list of educational content; and

recording the subset of the educational content selected for the vehicle user in a selection repository in memory.