Method for analyzing operation characteristics of a vehicle driver

• US 9,990,782 B2
• Filed: 11/09/2017
• Issued: 06/05/2018
• Est. Priority Date: 04/13/2012
• Status: Active Grant

• Current Assignee: Walter Steven Rosenbaum
• Original Assignee: Walter Steven Rosenbaum
• Inventors: Rosenbaum, Walter Steven
• Primary Examiner(s): Ingram, Thomas
• Application Number:
  US15/807,885
• Publication Number:
  US 20180082496A1
• Time in Patent Office: 208 Days
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• 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: G06Q 40/08 Insurance
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G07C 5/085 using electronic data carriers
• CPC Class Codes: G07C 5/0858 wherein the data carrier is removable

Abstract

A method analyzes characteristics of a vehicle driver, especially for insurance purposes. The method is performed by a cooperation of an analyzing vehicle system in a vehicle and a stationary processing unit remote from the vehicle. The analyzing vehicle system determines a driver operation characteristics parameter from the driving vehicle and sends the parameter to the stationary processing unit. The stationary processing unit derives a metric from that parameter as driver operation characteristics.

Claims

1. A method for analyzing a driving behavior of a vehicle driver, comprising:

during a movement of the vehicle, determining with an analyzing vehicle system in the vehicle a plurality of position coordinates of the vehicle and a speed of the vehicle as a driver operation parameter;

separating the speed data from the location data in different files containing either the location data or the respective speed data;

effecting a separation in the separating step in a way that a direct correlation between speed data and corresponding location data is destroyed due to the separation;

integrating a plurality of speed data to a speed average over a travel segment;

transmitting the driver operation parameter from the vehicle to a stationary processing unit;

at the stationary processing unit, processing the position coordinates via a data base that assigns a speed reference to each coordinate point on a road; and

comparing the determined average speed of the vehicle over a travel segment with the speed reference as a speed metric being the driving behavior within the stationary processing unit.

2. The method according to claim 1, wherein the speed reference is the average speed of a plurality of vehicles at that point during that time of the day.

3. The method according to claim 1, wherein the speed reference is lower at daytime than at night.

4. The method according to claim 1, wherein the speed reference is lower in rush hour than at other times of the day.

5. The method according to claim 1, wherein the speed reference is a statutory speed limit.

6. The method according to claim 1, wherein the average speed of the vehicle over a travel segment is compared with an average of a plurality of speed references as a speed metric within the stationary processing unit.

7. The method according to claim 1, wherein the stationary processing unit compares the average speed value to an average speed limit of more than one different speed limits over the travel segment.

8. The method according to claim 1, wherein the comparison by the stationary processing unit results in a speed difference from which the stationary processing unit derives a driving risk value from an actuarial parameter and feeds the speed difference and the driving risk value back to the driver.

9. The method according to claim 1, wherein the stationary processing unit compares the metric with metrics analogously derived for other drivers.

10. The method according to claim 1, wherein a rate of determining the speed, the average speed, and/or the speed metric is varied upon an input of a vehicle driver.

11. The method according to claim 1, wherein the analyzing vehicle system determines the plurality of position coordinates at random instants of time.

12. The method according to claim 1, wherein the analyzing vehicle system determines the speed of the vehicle at random instants of time.

13. The method according to claim 1, wherein the position coordinates of the vehicle are stored as entries in a file of the vehicle system and the sequence of entries of the file is randomized by the vehicle system.

14. The method according to claim 13, wherein the randomized data are free of indication of the temporal sequence of the entries.

15. The method according to claim 1, wherein the position coordinates are free of reference to the speed values themselves and of any timestamp from which an associated speed value may be determined.

16. The method according to claim 1, wherein the vehicle analyzing system erases the speed data from the file after integration of those speed data to the speed average.

17. The method according to claim 1, wherein the vehicle analyzing system stores the speed data as running speed average.

18. The method according to claim 1, wherein the route driven by the vehicle is tracked on one hand by travel segments from which the average speed over those travel segments is calculated, and on the other hand by exact location data which are sent to the stationary processing unit and from which the speed reference is calculated, wherein the location data are camouflaged by randomizing their sequence in the file and by separating them from time and speed data before sending them to the stationary processing unit.

19. The method according to claim 1, wherein the speed metric is calculated to a driving risk factor by using an area in which the vehicle was driven.

20. The method according to claim 19, wherein the area is classified containing the classes urban or rural.

21. The method according to claim 19, wherein the area is classified as type of road.

22. The method according to claim 21, wherein the type of road contains the classes city streets, urban roads and expressways.

23. The method according to claim 1, wherein during the movement of the vehicle the analyzing vehicle system camouflages the determined position coordinates by a position error.

24. The method according to claim 23, wherein the position error is a random position error.