Vehicle exception event management systems

• US 9,738,156 B2
• Filed: 10/17/2014
• Issued: 08/22/2017
• 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, Mauro, Gregory, Nickerson, Andrew
• Primary Examiner(s): Khatib, Rami
• Application Number:
  US14/516,650
• Publication Number:
  US 20150035665A1
• Time in Patent Office: 1,040 Days
• Field of Search: None
• 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 and form vehicle event records related to vehicle events, the discretization system comprising:

one or more physical computer processors 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, wherein the first non-discrete sensory data includes information captured by a video camera having a field-of-view that includes an environment about the vehicle;

facilitate discretization of a portion of the first non-discrete sensory data, wherein the portion of the first non-discrete sensory data includes the information captured by the video camera;

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

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;

form a vehicle event record that includes the third discrete quantitative data; and

transfer the vehicle event record to a remote computing device that is external to the vehicle; and

a user interface, wherein the user interface receives one or more of entry and selection of manual interpretation information pertaining to the portion of the first non-discrete sensory data from a human interpreter, wherein the manual interpretation information includes discrete numeric values;

wherein the one or more physical computer processors is configured to determine the second discrete quantitative data based on the discrete numeric values included in the manual interpretation information.

2. The system of claim 1, wherein the one or more physical computer processors are configured such that one or more of the first discrete quantitative data, the second discrete quantitative data, and 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, 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.

4. The system of claim 1, 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.

5. The system of claim 1, 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.

6. The system of claim 5, 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.

7. The system of claim 1, 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.

8. The system of claim 1, 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.

9. The system of claim 1, 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.

10. The system of claim 1, 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.

11. The system of claim 1, 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.

12. The system of claim 1, wherein the one or more physical computer processors are further configured to generate and facilitate distribution of a report based on one or more of the first discrete quantitative data, the first non-discrete sensory data, the second discrete quantitative data, and the third discrete quantitative data.

13. The system of claim 12, wherein the one or more physical computer processors are configured such that the report includes coaching information.

14. The system of claim 12, 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.

15. The system of claim 12, 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.

16. A method for receiving vehicle event information and forming vehicle event records related to vehicle events, the method comprising:

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, wherein the first non-discrete sensory data includes information captured by a video camera having a field-of-view that includes an environment about the vehicle;

facilitating discretization of a portion of the first non-discrete sensory data, wherein the portion of the first non-discrete sensory data includes the information captured by the video camera;

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

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;

forming a vehicle event record that includes the third discrete quantitative data;

transferring the vehicle event record to a remote computing device that is external to the vehicle; and

receiving one or more of entry or selection of manual interpretation information pertaining to the portion of the first non-discrete sensory data from a human interpreter via a user interface, wherein the manual interpretation information includes discrete numeric values; and

wherein determining the second discrete quantitative data is based on the discrete numeric values included in the manual interpretation information.

17. The method of claim 16, wherein one or more of the first discrete quantitative data, the second discrete quantitative data, and 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.

18. The method of claim 16, further comprising determining the third discrete quantitative data based on one or more of predetermined logic rules, or predetermined algorithms.

19. The method of claim 16, further comprising facilitating presentation of the third discrete quantitative data to a remotely located user.

20. The method of claim 16, 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.

21. The method of claim 16, 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.

22. The method of claim 16, 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.

23. The method of claim 16, 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.

24. The method of claim 16, 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.

25. The method of claim 16, 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.

26. The method of claim 16, 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.

27. The method of claim 16, further comprising generating and facilitating distribution of a report based on one or more of the first discrete quantitative data, the first non-discrete sensory data, the second discrete quantitative data, and the third discrete quantitative data.

28. The method of claim 27, wherein the report includes coaching information.

29. The method of claim 27, wherein the report is distributed via one or more of an email, a text message, or a phone call.

30. The method of claim 16, further comprising generating and facilitating distribution of a report based on discrete quantitative data and non-discrete sensory data from multiple individual vehicle events.