Vehicle Exception Event Management Systems

• US 20150035665A1
• Filed: 10/17/2014
• Published: 02/05/2015
• Est. Priority Date: 11/09/2006
• Status: Active Grant

• Current Assignee: SmartDrive Systems, Inc. (Solera Holdings Incorporated)
• Original Assignee: SmartDrive Systems, Inc. (Solera Holdings Incorporated)
• Inventors: Plante, James, Kasavaraju, Ramesh, Nickerson, Andrew, Mauro, Gregory
• Granted Patent: US 9,738,156 B2
• Time in Patent Office: Days
• US Class Current: 340/438
• CPC Class Codes: B60K 35/00 Instruments specially adapted for vehicles; Arrangement of instruments in or on vehicles
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/085 using electronic data carriers

Abstract

Exception event recorders and analysis systems include: vehicle mounted sensors arranged as a vehicle event recorder to capture both discrete and non-discrete data; a discretization facility; a database; and an analysis server all coupled together as a computer network. Motor vehicles with video cameras and onboard diagnostic systems capture data when the vehicle is involved in a crash or other anomaly (an ‘event’). In station where interpretation of non-discrete data is rendered, i.e. a discretization facility, captured data is used as a basis for production of supplemental discrete data to further characterize the event. Such interpreted data is joined to captured data and inserted into a database in a structure which is searchable and which supports logical or mathematical analysis by automated machines. A coupled analysis server is arranged to test stored data for prescribed conditions and upon finding such, to initiate further actions appropriate for the detected condition.

Claims

1. A discretization system configured to receive vehicle event information that includes first non-discrete sensory data and first discrete quantitative data related to operation of a vehicle during a vehicle event, the discretization system comprising:

one or more physical computer processors configured to;

facilitate discretization of a portion of the first non-discrete sensory data;

determine second discrete quantitative data based on the discretization of the portion of the first non-discrete sensory data; and

determine third discrete quantitative data based on one or more of the first discrete quantitative data, the second discrete quantitative data, or the first non-discrete sensory data.

2. The system of claim 1, wherein the one or more physical computer processors are configured such that the first discrete quantitative data, the second discrete quantitative data, and/or the third discrete quantitative data include observations related to operator behavior, the observations related to operator behavior related to one or more of a collision, a near collision, a driving error, a distraction, a position of a head of an operator, an eye position of the operator, a hand position of the operator, talking by the operator, a lane departure, a lane position, a number of lanes in a direction of travel, a road type, a following distance, a number of visible vehicles, or a vehicle environment.

3. The system of claim 1, further comprising:

a user interface configured to facilitate manual discretization of the portion of the first non-discrete sensory data by a human interpreter, the user interface configured to receive one or more of entry or selection of manual interpretation information from the human interpreter;

wherein the one or more physical computer processors configured to determine the second discrete quantitative data based on the manual discretization by the human interpreter.

4. The system of claim 3, wherein the one or more physical computer processors are further configured to determine the third discrete quantitative data based on one or more of predetermined logic rules, or predetermined algorithms.

5. The system of claim 3, wherein the one or more physical computer processors are further configured to facilitate presentation of the third discrete quantitative data to a remotely located user.

6. The system of claim 3, further comprising a data store configured to electronically store the first discrete quantitative data, the first non-discrete sensory data, the second discrete quantitative data, and the third discrete quantitative data, the data store comprising one or more of a relational database, a NoSQL database, or a Hadoop data store.

7. The system of claim 6, wherein the data store is configured such that the first discrete quantitative data, the first non-discrete sensory data, the second discrete quantitative data, and the third discrete quantitative data are associated with the vehicle event and a vehicle event timeline in the data store.

8. The system of claim 3, wherein the user interface includes one or more of a keypad, a button, a switch, a keyboard, a knob, a lever, a display screen, a touch screen, a speaker, a microphone, an indicator light, an audible alarm, a printer, or a tactile feedback device.

9. The system of claim 3, wherein the one or more physical computer processors are further configured to automatically discretize a second portion of the first non-discrete sensory data via one or more of a neural network or logistic regression;

and

determine the third discrete quantitative data based on one or more of the first discrete quantitative data, the second discrete quantitative data, or the automatically discretized second portion of the first non-discrete sensory data.

10. The system of claim 3, wherein the one or more physical computer processors are further configured to automatically discretize a second portion of the first non-discrete sensory data via one or more of pattern recognition image processing techniques or pattern recognition audio signal processing techniques;

and

determine the third discrete quantitative data based on one or more of the first discrete quantitative data, the second discrete quantitative data, or the automatically discretized second portion of the first non-discrete sensory data.

11. The system of claim 3, wherein the first non-discrete sensory data received by the discretization system includes one or more of audio recording data or visual information representing a vehicle environment of the vehicle, the visual information acquired by one or more cameras, the vehicle environment including spaces in and around an interior and an exterior of the vehicle, the one or more cameras including one or more of a forward looking camera, a driver view camera, a passenger view camera, a rear vehicle view camera, or a side vehicle view camera.

12. The system of claim 3, wherein the user interface is configured to facilitate manual discretization of a portion of the first non-discrete sensory data by a human interpreter via a graphical representation of the first discrete quantitative data, the graphical representation of the first discrete quantitative data including a graphical representation of one or more of vehicle acceleration, vehicle speed, engine speed, vehicle gear, vehicle brake position, vehicle steering wheel position, throttle position, engine load, vehicle angular velocity, gear ratio, lane departure, following distance, a collision warning, rollover protection system activation, fishtailing protection system activation, a speedometer, an engine RPM gage, or a force gauge.

13. The system of claim 3, wherein the one or more physical computer processors are further configured to generate and facilitate distribution of a report based on the first discrete quantitative data, the first non-discrete sensory data, the second discrete quantitative data, and/or the third discrete quantitative data.

14. The system of claim 13, wherein the one or more physical computer processors are configured such that the report includes coaching information.

15. The system of claim 13, wherein the one or more physical computer processors are configured such that the report is distributed via one or more of an email, a text message, or a phone call.

16. The system of claim 13, wherein the one or more physical computer processors are further configured to generate and facilitate distribution of a report based on discrete quantitative data and non-discrete sensory data from multiple individual vehicle events.

17. A method for receiving vehicle event information that includes first non-discrete sensory data and first discrete quantitative data related to operation of a vehicle during a vehicle event, the method comprising:

facilitating discretization of a portion of the first non-discrete sensory data;

determining second discrete quantitative data based on the discretization of the portion of the first non-discrete sensory data; and

determining third discrete quantitative data based on one or more of the first discrete quantitative data, the second discrete quantitative data, or the first non-discrete sensory data.

18. The method of claim 17, wherein the first discrete quantitative data, the second discrete quantitative data, and/or the third discrete quantitative data include observations related to operator behavior, the observations related to operator behavior related to one or more of a collision, a near collision, a driving error, a distraction, a position of a head of an operator, an eye position of the operator, a hand position of the operator, talking by the operator, a lane departure, a lane position, a number of lanes in a direction of travel, a road type, a following distance, a number of visible vehicles, or a vehicle environment.

19. The method of claim 17, wherein:

facilitating discretization of the portion of the first non-discrete sensory data includes facilitating manual discretization by a human interpreter by receiving one or more of entry or selection of manual interpretation information from the human interpreter via a user interface; and

the second discrete quantitative data is determined based on the manual discretization by the human interpreter.

20. The method of claim 19, further comprising determining the third discrete quantitative data based on one or more of predetermined logic rules, or predetermined algorithms.

21. The method of claim 19, further comprising facilitating presentation of the third discrete quantitative data to a remotely located user.

22. The method of claim 19, further comprising electronically storing the first discrete quantitative data, the first non-discrete sensory data, the second discrete quantitative data, and the third discrete quantitative data in a data store, the data store comprising one or more of a relational database, a NoSQL database, or a Hadoop data store.

23. The method of claim 19, wherein the data store is configured such that the first discrete quantitative data, the first non-discrete sensory data, the second discrete quantitative data, and the third discrete quantitative data are associated with the vehicle event and a vehicle event timeline in the data store.

24. The method of claim 19, wherein the user interface includes one or more of a keypad, a button, a switch, a keyboard, a knob, a lever, a display screen, a touch screen, a speaker, a microphone, an indicator light, an audible alarm, a printer, or a tactile feedback device.

25. The method of claim 19, further comprising automatically discretizing a second portion of the first non-discrete sensory data via one or more of a neural network or logistic regression;

and

determining the third discrete quantitative data based on one or more of the first discrete quantitative data, the second discrete quantitative data, or the automatically discretized second portion of the first non-discrete sensory data.

26. The method of claim 19, further comprising automatically discretizing a second portion of the first non-discrete sensory data via one or more of pattern recognition image processing techniques or pattern recognition audio signal processing techniques;

and

determining the third discrete quantitative data based on one or more of the first discrete quantitative data, the second discrete quantitative data, or the automatically discretized second portion of the first non-discrete sensory data.

27. The method of claim 19, wherein the first non-discrete sensory data includes one or more of audio recording data or visual information representing a vehicle environment of the vehicle, the visual information acquired by one or more cameras, the vehicle environment including spaces in and around an interior and an exterior of the vehicle, the one or more cameras including one or more of a forward looking camera, a driver view camera, a passenger view camera, a rear vehicle view camera, or a side vehicle view camera.

28. The method of claim 19, further comprising facilitating manual discretization of a portion of the first non-discrete sensory data by a human interpreter via a graphical representation of the first discrete quantitative data, the graphical representation of the first discrete quantitative data including a graphical representation of one or more of vehicle acceleration, vehicle speed, engine speed, vehicle gear, vehicle brake position, vehicle steering wheel position, throttle position, engine load, vehicle angular velocity, gear ratio, lane departure, following distance, a collision warning, rollover protection system activation, fishtailing protection system activation, a speedometer, an engine RPM gage, or a force gauge.

29. The method of claim 19, further comprising generating and facilitating distribution of a report based on the first discrete quantitative data, the first non-discrete sensory data, the second discrete quantitative data, and/or the third discrete quantitative data.

30. The method of claim 29, wherein the report includes coaching information.

31. The method of claim 29, wherein the report is distributed via one or more of an email, a text message, or a phone call.

32. The method of claim 19, further comprising generating and facilitating distribution of a report based on discrete quantitative data and non-discrete sensory data from multiple individual vehicle events.