Method and Apparatus for GPS Based Z-Axis Difference Parameter Computation

• US 20160311441A1
• Filed: 07/01/2016
• Published: 10/27/2016
• 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 10,102,096 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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

Data is collected during the operation of a vehicle and used to produce a ranking of a driver'"'"'s efficiency performance, and that ranking is shared on a hosted website, such that the drivers can compare their performance metrics to their peers. Fleet operators can use these performance metrics as incentives, by linking driver pay with efficiency performance. Individual fleet operators can host their own website, where driver rankings in that fleet can be compared, or the website can be hosted by a third party, and multiple fleet operators participate. The third party can offset their costs for operating the website by charging participating fleet operators a fee, and/or by advertising revenue. In some embodiments, all driver efficiency performance data is displayed in an anonymous format, so that individual drivers cannot be identified unless the driver shares their user ID.

Claims

1. A method of using vehicle position data, comprising the step of:

(a) while the driver is operating the vehicle, automatically collecting vehicle data, the vehicle data including vehicle position data in the x, y and z axes;

(b) using a first computing device to iteratively evaluate a first parameter of interest from changes in the z axis data over time, thereby producing a first sequence of values.

2. The method of claim 1, wherein the first sequence of values is road surface slope.

3. The method of claim 1, further comprising using a second computing device to evaluate a second parameter of interest, based on the first sequence of values.

4. The method of claim 3, wherein the second parameter of interest is vehicle weight.

5. The method of claim 4, further comprising using a third computer device a metric of interest using the second parameter of interest.

6. The method of claim 5, wherein the metric of interest is a driver performance metric.

7. 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.

8. The method of claim 2, wherein the step of using the first computing device to derive a sequence of values of road surface slope 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.

9. The method of claim 1, wherein the step of using the first computing device to iteratively evaluate a first parameter of interest from changes in the z axis data over time comprises the step of using a computing device disposed at the vehicle.

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

11. The method of claim 10, wherein the first and third computing devices are the same computing device.

12. The method of claim 10, wherein the first, second, and third computing devices are the same computing device.

13. 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.

14. 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.

15. A non-transitory memory medium having machine instructions stored thereon for iteratively evaluating a first parameter of interest from changes in the z axis data over time, thereby producing a first sequence of values.

16. The non-transitory memory medium of claim 15, further having machine instructions stored thereon for evaluating a second parameter of interest based on the first sequence of values.

17. The non-transitory memory medium of claim 15, further having machine instructions stored thereon for computing a metric based on the second parameter of interest.