Method and apparatus for estimating driving information

1. A method of estimating driving information, the method comprising:

receiving a driving route of a vehicle;

generating speed deviations corresponding to points on the driving route; and

generating a speed profile comprising a sequence of predicted speeds corresponding to the points based on the speed deviations and average speeds corresponding to the points,

wherein the average speeds corresponding to the points comprises any one or any combination of the a statistical average speed of vehicles travelling at each of the points and an average speed of vehicles based on a current traffic flow at the each of the points.

2. The method of claim 1 , wherein the generating of the speed deviations comprises:

acquiring a driving characteristic of the driving route; and

generating the speed deviations based on the driving characteristic and relative locations of the points using an adaptive neuro-fuzzy inference system (ANFIS).

3. The method of claim 2 , wherein the ANFIS comprises a membership function of the driving characteristic, and

the driving characteristic comprises any one or any combination of a driver type, a traffic flow, a weather condition, a road type, and a road curvature.

4. The method of claim 3 , wherein the ANFIS comprises ANFISs corresponding to membership functions of the driver type, and

the generating of the speed deviations comprises:

generating sub-road-types corresponding to the road type of the relative locations;

selecting an ANFIS corresponding to a membership function among the membership functions of the driver type based on a sub-road-type corresponding to a relative location among the relative locations; and

generating a speed deviation corresponding to the relative location based on the sub-road-type and the relative location using the selected ANFIS.

5. The method of claim 3 , wherein the driver type is defined based on a speed deviation corresponding to the road type.

6. The method of claim 3 , wherein a membership function of the driver type comprises at least one of a membership function corresponding to a conservative type, a membership function corresponding to a normal type, or a membership function corresponding to an aggressive type,

a membership function of the traffic flow comprises at least one of a membership function corresponding to a light flow, a membership function corresponding to a medium flow, or a membership function corresponding to a heavy flow,

a membership function of the weather condition comprises at least one of a membership function corresponding to a clear weather condition or a membership function corresponding to a wet weather condition,

a membership function of the road type comprises at least one of a membership function corresponding to a local road, a membership function corresponding to a local highway, or a membership function corresponding to a highway, and

a membership function of the road curvature comprises at least one of a membership function corresponding to a small curvature, a membership function corresponding to a medium curvature, or a membership function corresponding to a large curvature.

7. The method of claim 1 , wherein the generating of the speed deviations comprises:

acquiring a driving characteristic of the driving route;

generating sub-driving-characteristics corresponding to each of the points based on the driving characteristic and a location of the each of the points; and

generating a speed deviation corresponding to a relative location among the relative locations based on the relative location and a sub-driving-characteristic corresponding to the relative location.

8. The method of claim 1 , wherein the generating of the speed deviations comprises:

acquiring a driving characteristic of the driving route;

generating sub-driving-characteristics corresponding to each of the points based on the driving characteristic and a location of the each of the points; and

generating an output vector representing the speed deviations based on a first input vector representing the relative locations and a second input vector representing the sub-driving-characteristics.

9. The method of claim 1 , wherein the generating of the speed deviations comprises:

determining a number of the points by comparing a length of the driving route to a threshold length; and

setting the points on the driving route based on the determined number of the points.

10. The method of claim 1 , wherein the generating of the speed deviations comprises:

dividing the driving routes into sub-driving-routes by comparing a length of the driving route to a threshold length; and

generating speed deviations corresponding to points on a sub-driving-route among the sub-driving-routes.

11. The method of claim 1 , further comprising:

predicting an amount of power to be used by the vehicle based on the speed profile.

12. A method of estimating driving information, the method comprising:

receiving a driving route of a vehicle;

generating speed deviations corresponding to points on the driving route;

generating a speed profile comprising a sequence of predicted speeds corresponding to the points based on the speed deviations and average speeds corresponding to the points;

predicting an amount of power to be transferred to a powertrain of the vehicle based on the speed profile; and

predicting an amount of power to be used by an air conditioning system of the vehicle based on any one or any combination of solar radiation information and ambient temperature information.

13. The method of claim 1 , further comprising:

determining a driving range of the vehicle based on a predicted value of an amount of power to be used by the vehicle and at least one of a current amount of fuel of the vehicle or current state information of a battery unit of the vehicle.

14. The method of claim 13 , wherein the determining of the driving range of the vehicle comprises:

predicting at least one of an amount of fuel or state information of the battery unit at a destination based on the predicted value; and

determining whether the vehicle is able to reach the destination based on at least one of the predicted amount of fuel or the predicted state information.

15. The method of claim 1 , further comprising:

generating guide information to drive the vehicle based on the speed profile; and

outputting the guide information visually.

16. The method of claim 15 , wherein the generating of the guide information comprises:

comparing a predicted speed obtained based on the speed profile and a target speed obtained based on driving history information of the vehicle; and

generating the guide information based on the comparison.

17. The method of claim 15 , wherein the generating of the guide information comprises:

identifying a speed interval satisfying a criterion from the speed profile; and

generating guide information used for driving on a route corresponding to the identified speed interval.

18. A non-transitory computer-readable medium storing instructions, that when executed by a processor, cause the processor to perform the method of claim 1 .

19. An apparatus for estimating driving information, the apparatus comprising:

a processor configured to receive a driving route of a vehicle, to generate speed deviations corresponding to points on the driving route, and to generate a speed profile comprising a sequence of predicted speeds corresponding to the points based on the speed deviations and average speeds corresponding to the points,

wherein the average speeds corresponding to the points comprises any one or any combination of the a statistical average speed of vehicles travelling at each of the points and an average speed of vehicles based on a current traffic flow at the each of the points.

20. The apparatus of claim 19 , wherein the processor is further configured to acquire a driving characteristic of the driving route and to generate the speed deviations based on the driving characteristic and relative locations of the points using an adaptive neuro-fuzzy inference system (ANFIS),

the ANFIS comprises a membership function of the driving characteristic, and

the driving characteristic comprises any one or any combination of a driver type, a traffic flow, a road type, and a road curvature.