Method and System for Tuning the Effect of Vehicle Characteristics on Risk Prediction

• US 20100188201A1
• Filed: 01/26/2009
• Published: 07/29/2010
• Est. Priority Date: 01/26/2009
• Status: Active Grant

• Current Assignee: Lytx, Inc.
• Original Assignee: Lytx, Inc.
• Inventors: Cook, Bryan, Li, Hongying, Ellegaard, Peter
• Granted Patent: US 8,269,617 B2
• Time in Patent Office: Days
• US Class Current: 340/439
• CPC Class Codes: B60Q 1/00 Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor for lighting vehicle interior B60Q3/00
• 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

Abstract

A Method and System for Tuning the Effect of Vehicle Characteristics on Risk Prediction is disclosed. The system many incorporate many of those driver risk assessment system features previously disclosed by Assignee'"'"'s Prior Applications. The present system provides a major functional distinction from those prior systems by adding the feature of real-time tuning of the risk assessment/prediction/analysis system in response to ongoing changes in vehicle motion characteristics. Specifically, system monitors the vehicle center of gravity for changes on a real-time basis, and then adjusts the risk prediction/assessment/analysis system responsively. The system executes an initialization feature that implements an initial, or series of initial vehicular motion profiles at the commencement of either a driving trip of the system being powered up. A catalog or index of “standardized” motion profiles are accessible for initial comparison to actual vehicle motion characteristics in order to streamline the tuning of the driver risk analysis system. The system determines if and when an offset in Center of Gravity (i.e. from where initialized) has occurred, after which the system responsively tunes the driver risk assessment/prediction/analysis/reporting system.

Claims

1. A method for evaluating risk in driving, comprising:

initializing a spacial motion detecting event capture device associated with a vehicle, said initialization comprising tuning said device responsive to preset vehicle type/class data;

monitoring vehicle spacial motion with said spacial motion detecting event capture device;

capturing driving event data at one or more event capture devices coupled with said vehicle;

analyzing the driving event data with at least one event detector device to calculate a driving event score, said score responsive to said spacial motion monitoring; and

combining a plurality of driving event scores in a local data repository associated with said vehicle.

2. The method of claim 1, further comprising:

a vehicle class/type surveillance step comprising comparing data from said spacial motion detecting event capture device to preexisting vehicle type/class data stored in a data repository associated with said vehicle; and

first tuning said driving event data analyzing step responsive to said vehicle class/type surveillance step.

3. The method of claim 2, wherein said vehicle class/type surveillance step comprises comparing spacial motion data representative of a variety of distinct classes/types of vehicles stored in said data repository with said spacial motion detecting event capture device.

4. The method of claim 3, wherein said first tuning step comprises adjusting preset thresholds within said event detector devices, said thresholds responsible for identifying captured data as event data.

5. The method of claim 4, further comprising:

a vehicle historical motion surveillance steps comprising comparing data from said spacial motion detecting event capture device to historical data related to said vehicle stored in a data repository associated with said vehicle; and

generating an alert detectable to human senses responsive to said vehicle historical motion surveillance step.

6. The method of claim 1, further comprising a filtering step prior to said analyzing step, said filtering step comprising filtering said captured event data responsive to vehicle spacial motion data captured by said spacial motion detecting event capture device.

7. The method of claim 6, further comprising:

a vehicle class/type surveillance step comprising comparing data from said spacial motion detecting event capture device to preexisting vehicle type/class data stored in a data repository associated with said vehicle;

first tuning said driving event data analyzing step responsive to said vehicle class/type surveillance step; and

second tuning said filtering step responsive to said vehicle class/type surveillance step.

8. The method of claim 7, wherein said vehicle class/type surveillance step comprises comparing spacial motion data representative of a variety of distinct classes/types of vehicles stored in said data repository with said spacial motion detecting event capture device.

9. The method of claim 8, wherein said first tuning step comprises adjusting preset thresholds within said event detector devices, said thresholds responsible for identifying captured data as event data.

10. The method of claim 9, wherein said second tuning step comprises adjusting preset parameters controlling filtration of said captured event data by said event detector devices prior to said analyzing step.

11. The method of claim 10, further comprising:

a vehicle historical motion surveillance steps comprising comparing data from said spacial motion detecting event capture device to historical data related to said vehicle stored in a data repository associated with said vehicle; and

generating an alert detectable to human senses responsive to said vehicle historical motion surveillance step.

12. The method of claim 11, further comprising:

a vehicle historical motion surveillance steps comprising comparing data from said spacial motion detecting event capture device to historical data related to said vehicle stored in a data repository associated with said vehicle; and

generating an alert detectable to human senses responsive to said vehicle historical motion surveillance step.

13. A system for reducing risk in driving, comprising:

at least one event capture device associated with a vehicle, at least one of which event capture devices comprises sensitivity to spacial motion of said vehicle;

at least one event detector device coupled with the vehicle and configured to communicate with said event capture devices and to determine, responsive to event scoring criteria, whether or not data captured by said event capture devices represents a driving event; and

a trigger threshold tuner coupled with said event detector devices, said tuner acting to modify said event scoring criteria responsive to said detected spacial motion of said vehicle.

14. The system of claim 13, further comprising a raw data filter for filtering data captured by said event capture devices prior to said determination of whether or not said data represents a driving event, said raw data filter data filtration responsive to said detected spacial motion of said vehicle.

15. The system of claim 14, wherein said event capture device comprising sensitivity to spacial motion of said vehicle comprises the ability to detect offsets in vehicle center of gravity from prior vehicle center of gravity locations.

16. The system of claim 15, wherein said event detector comprises sensitivity to movement of said event capture device relative to said vehicle.

17. A method for reducing risk in driving, comprising:

initializing a spacial motion detecting event capture device associated with a vehicle, said initialization comprising tuning said device responsive to preset vehicle type/class data;

monitoring vehicle spacial motion with said spacial motion detecting event capture device;

identifying an individual driver;

identifying driving events responsive to said vehicle spacial motion, said identifying responsive to said tuning;

obtaining a plurality of driving event data for the individual driver, the driving event data obtained from a data storage area comprising a plurality of captured driving event data for a plurality of drivers;

analyzing the plurality of driving event data;

analyzing demographic data for the individual driver, said demographic data obtained from a data storage area comprising a plurality of driver records, said records comprising demographic data; and

scoring the individual driver based on the analysis of the plurality of driving event data and the analysis of the demographic data.