Method and apparatus for driver-centric fuel efficiency determination and utilization

1. A system comprising:

a processor configured to:

receive a request from an identified user for predicted fuel efficiency to be achieved by the identified user using a vehicle of a type, based on a vehicle model, defined in the request;

receiving a user profile for the identified user, responsive to the request;

obtain efficiency-affecting data from the user profile indicating at least one of user driving-behavior predefined as affecting fuel efficiency or route-related data predefined as affecting fuel efficiency;

compare the efficiency-affecting data to corresponding data gathered from drivers of the vehicle model to determine a correlation between the user profile and other drivers of the vehicle model, the correlation identifying data from the other drivers pertinent to determining fuel efficiency for the user using the vehicle of the type, the correlation determined based on predefined parameters, corresponding to a given data type of the efficiency-affecting data, the parameters identifying what constitutes a correlation for the given data type;

select at least one of the other drivers as a basis for predicting fuel efficiency for the identified user, based on fuel efficiency experienced by the at least one driver using the vehicle model, the selecting based at least in part on more than a predefined threshold degree of correlation between the identified user and the at least one driver, derived from the comparing;

predict a value for fuel efficiency for the user using the vehicle model based fuel efficiency experienced by at least one driver of the other driver; and

report the predicted fuel efficiency responsive to the identified user.

2. The system of claim 1 , wherein the efficiency-affecting data includes user driving behavior and wherein the parameters for driving behavior comparison define a correlation to ones of the other drivers' driving behavior based on a classification of the user driving behavior compared to classifications of the ones of the other drivers' driving behavior.

3. The system of claim 1 , wherein the efficiency-affecting data includes user route data.

4. The system of claim 3 , wherein the route data includes historical route characteristics encountered by the user more than a predefined threshold amount of time and wherein the parameters for historical route characteristic comparison define a correlation to other drivers based on ones of the other drivers encountering the same route characteristics for more than the predefined threshold amount of time.

5. The system of claim 4 , wherein the route characteristics include traffic.

6. The system of claim 4 , wherein the route characteristics include one or more specific road speed limits.

7. The system of claim 3 , wherein the route data includes route data for an upcoming route along which the user is traveling.

8. The system of claim 3 , wherein the route data includes a geographic locality and wherein the parameters for geographic locality comparison define a correlation to other drivers based on ones of the other drivers traveling within a predefined geographic region with a predefined threshold frequency.

9. The system of claim 8 , wherein the predefined geographic region includes a predefined region around a reference point defined with respect to the identified user.

10. The system of claim 1 , wherein the other drivers include a model driver generated from accrued user behavior observed as being exhibited by at least the other drivers, the model driver generated to have model driving behavior characteristics corresponding to driving-behavior characteristics of the user, obtained from the user profile, and having defined efficiency determined based on effects on efficiency for a given characteristic and a value of the given characteristic, ascribed to the model driver, the effect the value of the given characteristic has being an expected effect for the value based on observation of the real effects on efficiency achieved by a plurality of varied values of the given characteristic pertaining to the other drivers.

11. A non-transitory storage medium storing instructions that, when executed, cause one or more processors of a vehicle to perform a method comprising:

receiving a request from an identified user for predicted fuel efficiency to be achieved by the identified user using a vehicle of a type, based on a vehicle model, defined in the request;

receiving a user profile for the identified user, responsive to the request;

obtaining efficiency-affecting data from the user profile indicating at least one of user driving-behavior predefined as affecting fuel efficiency or route-related data predefined as affecting fuel efficiency;

comparing the efficiency-affecting data to corresponding data gathered from drivers of the vehicle model to determine a correlation between the user profile and other drivers of the vehicle model, the correlation identifying data from the other drivers pertinent to determining fuel efficiency for the user using the vehicle of the type, the correlation determined based on predefined parameters, corresponding to a given data type of the efficiency-affecting data, the parameters identifying what constitutes a correlation for the given data type;

selecting at least one of the other drivers as a basis for predicting fuel efficiency for the identified user, based on fuel efficiency experienced by the at least one driver using the vehicle model, the selecting based at least in part on more than a predefined threshold degree of correlation between the identified user and the at least one driver, derived from the comparing;

predicting a value for fuel efficiency for the user using the vehicle model based on fuel efficiency experienced by at least one driver of the other drivers;

presenting the predicted fuel efficiency responsive to the identified user via a display of the vehicle.

12. The storage medium of claim 11 , wherein the efficiency-affecting data includes user driving behavior and wherein the parameters for driving behavior comparison define a correlation to ones of the other drivers' driving behavior based on a classification of the user driving behavior compared to classifications of the ones of the other drivers' driving behavior.

13. The storage medium of claim 11 , wherein the efficiency-affecting data includes user route data.

14. The storage medium of claim 13 , wherein the route data includes historical route characteristics encountered by the user more than a predefined threshold amount of time and wherein the parameters for historical route characteristic comparison define a correlation to other drivers based on ones of the other drivers encountering the same route characteristics for more than the predefined threshold amount of time.

15. The storage medium of claim 14 , wherein the route characteristics include traffic.

16. The storage medium of claim 14 , wherein the route characteristics include one or more specific road speed limits.

17. The storage medium of claim 13 , wherein the route data includes a geographic locality and wherein the parameters for geographic locality comparison define a correlation to other drivers based on ones of the other drivers traveling within a predefined geographic region with a predefined threshold frequency.

18. The storage medium of claim 17 , wherein the predefined geographic region includes a predefined region around a reference point defined with respect to the identified user.