Method and system for retrieving vehicular parameters from a vehicle data bus

• US 9,767,624 B2
• Filed: 12/23/2013
• Issued: 09/19/2017
• Est. Priority Date: 12/23/2012
• Status: Active Grant

• Current Assignee: Orpak Systems Ltd. (Vontier Corp.)
• Original Assignee: Orpak Systems Ltd. (Vontier Corp.)
• Inventors: Neulander, Osnat, Bakfan, Shay, Manos, Hezi, Peri, Itay
• Primary Examiner(s): To, Tuan C.
• Application Number:
  US14/654,579
• Publication Number:
  US 20150371457A1
• Time in Patent Office: 1,366 Days
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0841 Registering performance data recording measured values G01D; information storage G11B

Abstract

The present invention relates to a device, system and a method for obtaining and monitoring vehicular parameters and in particular, to such a device, system and method in which vehicular parameters are sniffed and automatically ascertained from a vehicle controller data bus.

Claims

1. A method for identifying vehicular parameters of a vehicle by sniffing for data communicated over a vehicle data bus (52) characterized in that said vehicular parameters are identified without interrogating the vehicle'"'"'s central processor (54), the method comprising:

a. sniffing to the vehicle data bus and recording data communicated thereon;

b. parsing said recorded vehicle bus data to form a plurality of vehicular parameter candidates;

c. performing a plurality of statistical measurements for each of said candidates to define said candidates'"'"' statistical behavior;

d. filtering said candidates according to a data behavioral model with at least one data behavioral modeling filter, wherein said data behavioral model is modeled to reflect the statistical behavior of known vehicular parameters, so as to associate each of said candidates with a vehicular parameter;

e. grouping and sorting said candidates according to said data behavioral model therein matching said candidates into groups representative of said vehicular parameters;

f. removing any of said candidates that are not matched and/or grouped to a vehicular parameter representative group;

g. performing a correlation analysis between said candidates that are grouped into a single vehicular parameter representative group, so as to determine a correlation coefficient;

h. scoring and sorting said candidates according to said correlation analysis; and

i. selecting winning candidates according to said score to determine the vehicular parameter.

2. The method of claim 1 wherein said correlation analysis score is a function of the correlation coefficient.

3. The method of claim 2 wherein said winning candidate is selected based on a score wherein the threshold of the correlation coefficient has an absolute value of at least 0.75.

4. The method of claim 1 further comprising the step of determining the scale of said candidates based on available a-priori data of any vehicular parameter.

5. The method of claim 4 wherein said a-priori data is selected from the vehicular parameter representative group consisting of initial odometer reading.

6. The method of claim 1 wherein said statistical measurements are selected from the vehicular parameter representative group consisting of minimum, maximum, mean, median, average, standard deviation, variance, distribution analysis, Gaussian distribution, any combination thereof.

7. The method of claim 1 wherein parsing said recorded vehicle bus data comprises applying a data structure Filters provided to extract available data structure details selected from:

MSB position, LSB position, reading frames, BigEndian, LittleEndian, MiddleEndian, data prefixes, bit length, number of bytes, encryption codes, data sequence order, or any combination thereof.

8. The method of claim 1 wherein recorded vehicle bus data is provided in the form of a message (10) having a message header (12) and payload (14), and wherein said message header comprises unique identifier in the form of a message ID (MID).

9. The method of claim 8 wherein said method is performed on said payload.

10. The method of claim 8 wherein said candidates are associated with said unique identifier message ID.

11. The method of claim 1 further comprising a cross correlation between at least two or more candidates from different vehicular parameter groups wherein said vehicular parameter are correlated and having a known correlation function, the method comprising:

j. Forming a cross correlation data set including at least two or more candidates;

k. Performing a cross-correlation analysis between said at least two or more candidates;

l. Determining a scaling factor for said at least two or more candidates based on said cross-correlation analysis.

12. The method of claim 11 further comprising obtaining a-priori data of any vehicular parameter.

13. The method of claim 12 wherein said a-priori data is selected from the vehicular parameter representative group consisting of initial odometer reading.

14. The method of claim 1 wherein said winning candidate is utilized to determine a scale of a parameter by comparison to a-priori data.

15. The method of claim 1 wherein said parsing is performed on a payload portion of said recorded vehicle bus data.

16. The method of claim 1 wherein said candidates are formed from a payload portion of said recorded vehicle bus data.

17. The method of claim 1 wherein said method is performed substantially simultaneously as data is communicated over the vehicle data is made available.

18. The method of claim 1 wherein said method is performed substantially without recording intermediate data.

19. A device adapted to be associated directly and/or indirectly with the vehicle data bus provided to implement the processor mediated method of claim 1, the device comprising, a processor module, a communication module, data capture module, and a data modeling module, characterized in that said data modelling module provides for statistically modeling vehicular parameter candidates based on known vehicular data historical data.

20. The device of claim 19 wherein said data modeling module comprises a message modeling module provided for modeling the data structure of data sniffed from the vehicle data bus.

21. A system for determining and analyzing vehicular parameters from a vehicle data bus characterized in that the system does not interrogate the vehicle processing unit, the system comprising a data management system (80) in communication with a vehicle bus reading (VBR) device (60) installed in a vehicle (50) wherein said VBR (60) is associated with said vehicle about said vehicle data bus (52), and wherein said VBR (60) provides for seamlessly ascertaining vehicular parameters from data communicated over said vehicle data bus (52) without interrogating the vehicle processor (54) by implementing the processor mediated method of claim 1.

22. The system of claim 21 wherein said data management system is a fleet management system.

23. The system of claim 21 wherein said data management system (80) communicates with said VBR (60) to define vehicular parameters of interest.

24. The system of claim 21 wherein said data management system (80) provide a-priori data that models the behavior of said vehicular parameters.

25. The system of claim 21 wherein said VBR (60) communicates to said data management system (80) any vehicular data ascertained from said vehicle data bus (52).