METHOD AND APPARATUS FOR GPS BASED SLOPE DETERMINATION, REAL-TIME VEHICLE MASS DETERMINATION, AND VEHICLE EFFICIENCY ANALYSIS

• US 20130164712A1
• Filed: 12/18/2012
• Published: 06/27/2013
• Est. Priority Date: 12/23/2011
• Status: Active Grant

• Current Assignee: Zonar Systems, Inc. (Continental AG)
• Original Assignee: Zonar Systems, Inc. (Continental AG)
• Inventors: HUNT, BRYAN, Mcquade, Charles Michael
• Granted Patent: US 9,384,111 B2
• Time in Patent Office: Days
• US Class Current: 434/65
• CPC Class Codes: B60W 2510/0638 Engine speed
• CPC Class Codes: B60W 2510/0657 Engine torque
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2552/15 Road slope, i.e. the inclination of a road segment in the longitudinal direction
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06F 11/3024 where the computing system component is a central processing unit [CPU]
• CPC Class Codes: G06F 11/3065 Monitoring arrangements determined by the means or processing involved in reporting the monitored data error or fault reporting or logging G06F11/0766
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06F 17/11 for solving equations , e.g. nonlinear equations, general mathematical optimization problems optimization specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G09B 19/167 Control of land vehicles

Abstract

Three dimensional GPS or vehicle position data is used to determine a slope the vehicle is traveling over at a specific point in time. The slope data can then be combined with other metrics to provide an accurate, slope corrected vehicle mass. The vehicle mass can then be used along with other vehicle data to determine an amount of work performed by a vehicle, enabling s detailed efficiency analysis of the vehicle to be performed. To calculate slope, horizontal ground speed (V_HGS) can be calculated using the Pythagorean Theorem. One can take the Z/Up magnitude and divide it by the horizontal ground speed. Replacing Z, x and y with directional vectors enables one to calculate slope. The slope data is then used to determine the mass of the vehicle at that time. Pervious techniques to calculate mass did not factor in slope, and thus are not accurate.

Claims

1. A method of evaluating driver performance using a road surface slope metric derived from data that includes vehicle position data, comprising the steps of:

(a) while the driver is operating the vehicle, automatically collecting vehicle data, the vehicle data including vehicle position data;

(b) using a first computing device to derive the road surface slope metric using vehicle position data; and

(c) using a second computing device to evaluate driver performance using a plurality of factors, at least one of which is derived from the road surface slope metric.

2. The method of claim 1, wherein the step of automatically collecting vehicle position data comprises the step of automatically collecting global position system (GPS) data.

3. The method of claim 1, wherein the step of using the first computing device to derive the road surface slope metric using vehicle position data comprises the steps of:

(a) using the vehicle position data to determine horizontal ground speed; and

(b) using the horizontal ground speed and an up directional vector from the vehicle position data to determine the road surface slope metric.

4. The method of claim 1, wherein the step of automatically collecting vehicle data further comprises the steps of automatically collecting the following types of data:

(a) vehicle speed data;

(b) torque data; and

(c) engine speed data.

5. The method of claim 4, further comprising the step of using a third computing device to determine a mass of the vehicle at a specific point in time, based on the road surface slope metric corresponding to that point in time.

6. The method of claim 5, wherein the step of using the third computing device to determine the mass of the vehicle comprises the steps of using vehicle speed data at that point in time, torque data at that point in time, and engine speed data at that point in time.

7. The method of claim 6, wherein the step of using the third computing device to determine the mass of the vehicle using vehicle speed data comprises the step of using vehicle speed data obtained from a vehicle speed sensor.

8. The method of claim 6, wherein the step of using the third computing device to determine the mass of the vehicle using vehicle speed data comprises the step of using vehicle speed data obtained from changes in the vehicle position data over time.

9. The method of claim 5, wherein the step of using the second computing device to evaluate driver performance comprises the step of using the vehicle mass derived from the road surface slope metric as one of the plurality of factors.

10. The method of claim 9, wherein the step of using the vehicle mass derived from the road surface slope metric as one of the plurality of factors comprises the step of producing a cost per loaded mile performance metric.

11. The method of claim 1, wherein the step of using the first computing device to derive the road surface slope metric using vehicle position data comprises the step of using a computing device disposed at the vehicle.

12. The method of claim 5, wherein the step of using the third computing device to determine the mass of the vehicle comprises the step of using a computing device disposed at the vehicle.

13. The method of claim 12, wherein the first and third computing devices are the same computing device.

14. The method of claim 12, wherein the first, second, and third computing devices are the same computing device.

15. The method of claim 1, further comprising the step of wirelessly transmitting data from the vehicle to the first computing device, the first computing device being disposed remote from the vehicle.

16. The method of claim 1, further comprising the step of wirelessly transmitting data from the vehicle to the second computing device, the second computing device being disposed remote from the vehicle.

17. A non-transitory memory medium having machine instructions stored thereon for carrying out step (b) of claim 1.

18. The non-transitory memory medium of claim 17, further having machine instructions stored thereon for carrying out step (c) of claim 1.

19. The non-transitory memory medium of claim 17, further having machine instructions stored thereon for carrying out the step of claim 3.

20. The non-transitory memory medium of claim 17, further having machine instructions stored thereon for carrying out the step of claim 5.

21. The non-transitory memory medium of claim 20, further having machine instructions stored thereon for carrying out the step of claim 7.

22. The non-transitory memory medium of claim 20, further having machine instructions stored thereon for carrying out the step of claim 8.

23. A non-transitory memory medium having machine instructions stored thereon for carrying out step (c) of claim 1.

24. The non-transitory memory medium of claim 23, further having machine instructions stored thereon for carrying out the step of claim 5.

25. The non-transitory memory medium of claim 24, further having machine instructions stored thereon for carrying out the step of claim 9.

26. The non-transitory memory medium of claim 24, further having machine instructions stored thereon for carrying out the step of claim 10.

27. A method of producing a performance metric indicative of a performance of a driver using at least in part slope data derived from vehicle position data, the method comprising the steps of:

(a) while the driver is operating the vehicle, automatically collecting time indexed vehicle data, the vehicle data comprising;

(i) position data;

(ii) vehicle speed data;

(iii) torque data; and

(iv) engine speed data;

(b) using a computing device to determine a slope the vehicle is traveling over at a specific point in time using changes the position data;

(c) using a computing device to determine a mass of the vehicle at a specific point in time using the slope, vehicle speed data, torque data, and engine speed data for the specific point in time;

(d) using a computing device to produce the performance metric based at least in part on the mass of the vehicle, the mass having been determined using slope data derived from vehicle position data.

28. The method of claim 27, wherein the step of using the computing device to determine the slope the vehicle is traveling over at a specific point in time comprises the steps of:

(a) determining a horizontal ground speed of the vehicle at a specific point in time based on the vehicle position data; and

;

(b) determining the slope the vehicle is traveling over at that point in time, based on the horizontal ground speed and Z axis position data at that point in time.

29. The method of claim 27, wherein the step of using the computing device to produce the performance metric comprises the step of producing a cost per loaded mile performance metric.

30. The method of claim 27, wherein the computing device used to determine slope and mass is disposed at the vehicle.

31. The method of claim 30, wherein the computing device used to determine the performance metric is remote from the vehicle, and further comprising the step of conveying the vehicle data, the slope, and vehicle mass from the vehicle to the remote computing device before the step of using the computing device to produce the performance metric.

32. The method of claim 27, wherein the computing device used to determine the slope, the mass, and the performance metric is remote from the vehicle, and further comprising the step of conveying the vehicle data from the vehicle to the remote computing device before the steps of using the computing device to determine the slope, using the computing device to determine the mass, and using the computing device to produce the performance metric.

33. A non-transitory memory medium having machine instructions stored thereon for carrying out step (b) of claim 27.

34. The non-transitory memory medium of claim 33, further having machine instructions stored thereon for carrying out step (c) of claim 27.

35. The non-transitory memory medium of claim 34, further having machine instructions stored thereon for carrying out step (d) of claim 27.

36. The non-transitory memory medium of claim 33, further having machine instructions stored thereon for carrying out steps (a) and (b) of claim 28.

37. A non-transitory memory medium having machine instructions stored thereon for carrying out step (d) of claim 27.