DRIVING EVENT CLASSIFICATION SYSTEM

• US 20140148972A1
• Filed: 10/16/2013
• Published: 05/29/2014
• Est. Priority Date: 10/16/2012
• Status: Active Grant

• Current Assignee: Appy Risk Technologies Limited (Trak Global Group Ltd.)
• Original Assignee: Intelligent Mechatronic Systems Inc. (Trak Global Group Ltd.)
• Inventors: Basir, Otman A., Miners, William Ben, Jamali, Seyed Hamidreza
• Granted Patent: US 10,417,838 B2
• Time in Patent Office: Days
• US Class Current: 701/1
• 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

This vehicle monitoring system provides a plurality of sensors in the vehicle recording performance of the vehicle. A processor (remote or on-board) receives data from the sensors. The processor classifies the data from the at least one sensor as an event in one of a plurality of classifications. The processor associates at least one parameter with the classification.

Claims

1. A vehicle monitoring system comprising:

at least one sensor in the vehicle, the at least one sensor recording performance of the vehicle; and

a processor receiving data from the at least one sensor, the processor classifying the data from the at least one sensor as an event in one of a plurality of classifications, the processor associating at least one parameter with the one of the plurality of classifications.

2. The vehicle monitoring system of claim 1 wherein the event is classified as a harsh braking event and wherein the parameter is a severity of the harsh braking event.

3. The vehicle monitoring system of claim 2 wherein the processor is programmed to evaluate a plurality of severities of a plurality of harsh braking events.

4. The vehicle monitoring system of claim 2 wherein the processor is programmed to assign a level of confidence to the classification based upon the data.

5. The vehicle monitoring system of claim 1 wherein the at least one sensor includes an accelerometer and a vehicle speed sensor.

6. The vehicle monitoring system of claim 5 wherein the processor is programmed to compare data from the accelerometer and the vehicle speed sensor to determine a type of road on which the vehicle is travelling.

7. The vehicle monitoring system of claim 5 wherein the processor is programmed to compare data from the accelerometer and the vehicle speed sensor to determine that the vehicle is travelling on an on-ramp or an off-ramp.

8. The vehicle monitoring system of claim 1 wherein the at least one sensor is a three-axis accelerometer and wherein the processor is programmed to evaluate the data from the three-axis accelerometer to determine unbalanced wheels of the vehicle.

9. The vehicle monitoring system of claim 1 wherein the processor is on-board the vehicle.

10. The vehicle monitoring system of claim 9 wherein the processor is programmed to optimize compression of the data based upon historical data and to transmit the compressed data to a remote server.

11. The vehicle monitoring system of claim 1 wherein the processor is located remotely from the vehicle.

12. The vehicle monitoring system of claim 1 wherein the processor is programmed to adapt the plurality of classifications based upon data from a plurality of vehicles including the vehicle.

13. A method for monitoring a vehicle including the steps of:

a) receiving data from a vehicle sensor;

b) classifying the data from the vehicle sensor as an event in one of a plurality of classifications; and

c) associating at least one parameter with the event.

14. The method of claim 13 wherein said step b) further includes the step of classifying the event as a harsh braking event and wherein said step c) further includes the step of associating a severity of the harsh braking event as the at least one parameter of the event.

15. The method of claim 14 further including the step of evaluating frequencies of a plurality of severities of a plurality of harsh braking events.

16. The method of claim 14 further including the step of assigning a level of confidence to the classification based upon the data.