SYSTEMS AND METHODS FOR PROVIDING FEEDBACK TO IMPROVE FUEL CONSUMPTION EFFICIENCY

1 . A method for improving fuel consumption efficiency, the method comprising:

collecting, by a computing device, user driving data for one or more vehicle trips made by a user between a particular pair of origination and destination points, the user driving data including information related to a user driving behavior of the user for the particular pair of origination and destination points;

analyzing, by the computing device, the user driving data to determine one or more user driving features of the user driving behavior for the particular pair of origination and destination points, the one or more user driving features being related to a user fuel consumption efficiency of the user for the particular pair of origination and destination points;

comparing, by the computing device, the one or more user driving features with one or more desired driving features of a desired driving behavior for the particular pair of origination and destination points, the one or more desired driving features being related to a desired fuel consumption efficiency for the particular pair of origination and destination points;

determining, by the computing device, a performance feedback based at least in part on the comparison; and

providing, by the computing device, the performance feedback to the user to improve the user fuel consumption efficiency for the particular pair of origination and destination points.

2 . The method of claim 1 , further comprising:

determining, by the computing device, the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points.

3 . The method of claim 2 , wherein determining the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points includes:

collecting community driving data for one or more vehicle trips made by at least one or more other users between the particular pair of origination and destination points, the community driving data including information related to a community driving behavior of at least the one or more other users for the particular pair of origination and destination points; and

analyzing the community driving data to determine the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points.

4 . The method of claim 3 , wherein collecting the community driving data for the one or more vehicle trips made by at least the one or more other users between the particular pair of origination and destination points includes:

collecting the community driving data for the one or more vehicle trips made by at least the user and the one or more other users between the particular pair of origination and destination points.

5 . The method of claim 1 , wherein the one or more desired driving features of the desired driving behavior include:

one or more first driving features that increase the desired fuel consumption efficiency;

one or more second driving features that decrease the desired fuel consumption efficiency; and

wherein:

the one or more first driving features correspond to one or more first importance levels respectively for increasing the desired fuel consumption efficiency; and

the one or more second driving features correspond to one or more second importance levels respectively for decreasing the desired fuel consumption efficiency.

6 . The method of claim 1 , wherein providing the performance feedback to the user to improve the user fuel consumption efficiency for the particular pair of origination and destination points includes:

providing the user with at least one suggestion about which of the one or more user driving features that the user needs to improve in order to improve the user fuel consumption efficiency.

7 . The method of claim 1 , wherein analyzing the user driving data to determine the one or more user driving features of the user driving behavior for the particular pair of origination and destination points includes:

providing the user driving data to an artificial neural network to generate the one or more user driving features of the user driving behavior for the particular pair of origination and destination points.

8 . The method of claim 7 , further comprising:

collecting community driving data for one or more vehicle trips made by at least one or more users between the particular pair of origination and destination points, the community driving data including information related to a community driving behavior of at least the one or more users for the particular pair of origination and destination points; and

providing the community driving data to the artificial neural network to generate the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points.

9 . The method of claim 8 , further comprising training the artificial neural network.

10 . A computing device for improving fuel consumption efficiency, the computing device comprising:

one or more processors; and

a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to:

collect user driving data for one or more vehicle trips made by a user between a particular pair of origination and destination points, the user driving data including information related to a user driving behavior of the user for the particular pair of origination and destination points;

analyze the user driving data to determine one or more user driving features of the user driving behavior for the particular pair of origination and destination points, the one or more user driving features being related to a user fuel consumption efficiency of the user for the particular pair of origination and destination points;

compare the one or more user driving features with one or more desired driving features of a desired driving behavior for the particular pair of origination and destination points, the one or more desired driving features being related to a desired fuel consumption efficiency for the particular pair of origination and destination points;

determine a performance feedback based at least in part on the comparison; and

provide the performance feedback to the user to improve the user fuel consumption efficiency for the particular pair of origination and destination points.

11 . The computing device of claim 10 , wherein the instructions further comprise instructions that, when executed by the one or more processors, cause the one or more processors to:

determine the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points.

12 . The computing device of claim 11 , wherein the instructions that cause the one or more processors to determine the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points further comprise instructions that cause the one or more processors to:

collect community driving data for one or more vehicle trips made by at least one or more other users between the particular pair of origination and destination points, the community driving data including information related to a community driving behavior of at least the one or more other users for the particular pair of origination and destination points; and

analyze the community driving data to determine the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points.

13 . The computing device of claim 12 , wherein the instructions that cause the one or more processors to collect the community driving data for the one or more vehicle trips made by at least the one or more other users between the particular pair of origination and destination points further comprise instructions that cause the one or more processors to:

collect the community driving data for the one or more vehicle trips made by at least the user and the one or more other users between the particular pair of origination and destination points.

14 . The computing device of claim 10 , wherein the one or more desired driving features of the desired driving behavior include:

one or more first driving features that increase the desired fuel consumption efficiency;

one or more second driving features that decrease the desired fuel consumption efficiency; and

wherein:

the one or more first driving features correspond to one or more first importance levels respectively for increasing the desired fuel consumption efficiency; and

the one or more second driving features correspond to one or more second importance levels respectively for decreasing the desired fuel consumption efficiency.

15 . The computing device of claim 10 , wherein the instructions that cause the one or more processors to provide the performance feedback to the user to improve the user fuel consumption efficiency for the particular pair of origination and destination points further comprise instructions that cause the one or more processors to:

provide the user with at least one suggestion about which of the one or more user driving features that the user needs to improve in order to improve the user fuel consumption efficiency.

16 . The computing device of claim 10 , wherein the instructions that cause the one or more processors to analyze the user driving data to determine the one or more user driving features of the user driving behavior for the particular pair of origination and destination points further comprise instructions that cause the one or more processors to:

provide the user driving data to an artificial neural network to generate the one or more user driving features of the user driving behavior for the particular pair of origination and destination points.

17 . The computing device of claim 16 , wherein the instructions further comprise instructions that, when executed by the one or more processors, cause the one or more processors to:

collect community driving data for one or more vehicle trips made by at least one or more users between the particular pair of origination and destination points, the community driving data including information related to a community driving behavior of at least the one or more users for the particular pair of origination and destination points; and

provide the community driving data to the artificial neural network to generate the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points.

18 . The computing device of claim 17 , wherein the instructions further comprise instructions that, when executed by the one or more processors, cause the one or more processors to train the artificial neural network.

19 . A non-transitory computer-readable medium storing instructions for improving fuel consumption efficiency, the instructions when executed by one or more processors of a computing device, cause the computing device to:

collect user driving data for one or more vehicle trips made by a user between a particular pair of origination and destination points, the user driving data including information related to a user driving behavior of the user for the particular pair of origination and destination points;

analyze the user driving data to determine one or more user driving features of the user driving behavior for the particular pair of origination and destination points, the one or more user driving features being related to a user fuel consumption efficiency of the user for the particular pair of origination and destination points;

compare the one or more user driving features with one or more desired driving features of a desired driving behavior for the particular pair of origination and destination points, the one or more desired driving features being related to a desired fuel consumption efficiency for the particular pair of origination and destination points;

determine a performance feedback based at least in part on the comparison; and

provide the performance feedback to the user to improve the user fuel consumption efficiency for the particular pair of origination and destination points.

20 . The non-transitory computer-readable medium of claim 19 , wherein the instructions, when executed by the one or more processors, further cause the computing device to:

collect community driving data for one or more vehicle trips made by at least one or more other users between the particular pair of origination and destination points, the community driving data including information related to a community driving behavior of at least the one or more other users for the particular pair of origination and destination points; and

analyze the community driving data to determine the one or more desired driving features of the desired driving behavior for the particular pair of origination and destination points.