System and method for monitoring and reducing vehicle operator impairment

• US 10,343,693 B1
• Filed: 01/24/2018
• Issued: 07/09/2019
• Est. Priority Date: 12/17/2012
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Plummer, Bryan Allen, Brown, Parker Andrew, He, Jibo, Fields, Brian M., Roberson, Steve, Cielocha, Steve, Peng, Jufeng
• Primary Examiner(s): Tun, Nay
• Application Number:
  US15/878,946
• Time in Patent Office: 531 Days
• CPC Class Codes: B60K 28/066 actuating a signalling device B60K28/063 takes precedence
• CPC Class Codes: B60Q 9/00 Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00 , e.g. haptic signalling
• CPC Class Codes: B60W 2040/0818 Inactivity or incapacity of driver
• CPC Class Codes: B60W 2040/0827 due to sleepiness
• CPC Class Codes: B60W 2040/0836 due to alcohol
• CPC Class Codes: B60W 2040/0845 due to drugs
• CPC Class Codes: B60W 2050/143 Alarm means
• CPC Class Codes: B60W 2050/146 Display means
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2540/221 Physiology, e.g. weight, heartbeat, health or special needs
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: B60W 50/16 Tactile feedback to the driver, e.g. vibration or force feedback to the driver on the steering wheel or the accelerator pedal
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06V 20/597 Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G08B 21/02 Alarms for ensuring the safety of persons

Abstract

In a computer-implemented method, data about potential vehicle operator impairment is retrieved. The data is generated by monitoring a vehicle operator, the environment ahead of the vehicle, and/or force in one or more directions. A number of impairment scores are generated by analyzing the data about potential vehicle operator impairment. A specific time period during which the vehicle operator tends to be most impaired is determined based on the impairment scores. Recommendations to reduce operator impairment of the vehicle operator are identified and communicated to the vehicle operator.

Claims

1. A computer-implemented method comprising:

retrieving data about potential vehicle operator impairment generated during a plurality of trips by monitoring, with a plurality of sensors, (i) a vehicle operator, (ii) an environment ahead of a vehicle of the vehicle operator, and (iii) force in one or more directions;

generating, by one or more processors, a number of impairment scores by analyzing the data about potential vehicle operator impairment;

determining, by the one or more processors and based on the impairment scores, a specific time period during which the vehicle operator tends to be most impaired;

identifying, by the one or more processors, one or more recommendations to reduce operator impairment of the vehicle operator, the one or more recommendations including a recommendation to avoid driving, or to remove distractions while driving, during at least the specific time period; and

electronically communicating the one or more recommendations to the vehicle operator.

2. The computer-implemented method of claim 1, wherein retrieving data about potential vehicle operator impairment includes retrieving data about potential vehicle operator impairment generated by:

monitoring the vehicle operator with a first sensor;

monitoring the environment ahead of the vehicle with a second sensor, and

monitoring force in one or more directions with a third sensor.

3. The computer-implemented method of claim 1, wherein retrieving data about potential vehicle operator impairment includes retrieving data about potential vehicle operator impairment generated by:

monitoring the vehicle operator with a first optical sensor;

monitoring the environment ahead of the vehicle with a second optical sensor; and

monitoring force in one or more directions with an accelerometer.

4. The computer-implemented method of claim 3, wherein retrieving data about potential vehicle operator impairment generated by monitoring the vehicle operator with the first optical sensor includes retrieving data about potential vehicle operator impairment generated by one or more of:

monitoring vehicle operator blinks, including monitoring one or more of number, frequency, and duration of blinks;

monitoring vehicle operator head nods;

monitoring vehicle operator scanning frequency;

or

monitoring vehicle operator gaze fixation.

5. The computer-implemented method of claim 3, wherein retrieving data about potential vehicle operator impairment generated by monitoring the vehicle operator with the first optical sensor includes retrieving data about potential vehicle operator impairment generated by:

monitoring vehicle operator mirror checking;

monitoring vehicle operator head rotations;

monitoring vehicle operator scanning frequency; and

monitoring vehicle operator gaze fixation.

6. The computer-implemented method of claim 3, wherein retrieving data about potential vehicle operator impairment generated by monitoring the environment ahead of the vehicle with the second optical sensor includes retrieving data about potential vehicle operator impairment generated by:

monitoring lane deviation;

monitoring lane centering; and

monitoring time to collision.

7. The computer-implemented method of claim 3, wherein retrieving data about potential vehicle operator impairment generated by monitoring force in one or more directions with the accelerometer includes retrieving data about potential vehicle operator impairment generated by one or more of:

monitoring fore-aft force to detect hard braking;

monitoring fore-aft force change in speed;

or

monitoring lateral force.

8. The computer-implemented method of claim 1, wherein the recommendations to reduce operator impairment further include recommendations to one or both of:

reduce mobile device use; and

reduce use of vehicle features.

9. The computer-implemented method of claim 1, further comprising communicating an analysis of data about potential vehicle operator impairment as one or more of a graph, chart, table, or log of data entries.

10. A computer system comprising:

one or more processors;

a program memory storing executable instructions that when executed by the one or more processors cause the computer system to;

retrieve data about potential vehicle operator impairment generated during a plurality of trips by monitoring, with a plurality of sensors, (i) a vehicle operator, (ii) an environment ahead of a vehicle of the vehicle operator, and (iii) force in one or more directions,

generate a number of impairment scores by analyzing the data about potential vehicle operator impairment,

determine, based on the impairment scores, a specific time period during which the vehicle operator tends to be most impaired,

identify one or more recommendations to reduce operator impairment of the vehicle operator, the one or more recommendations including a recommendation to avoid driving, or to remove distractions while driving, during at least the specific time period, and

electronically communicate the one or more recommendations to the vehicle operator.

11. The computer system of claim 10, wherein the data about potential vehicle operator impairment is generated by:

monitoring the vehicle operator with a first sensor;

monitoring the environment ahead of the vehicle with a second sensor; and

monitoring force in one or more directions with a third sensor.

12. The computer system of claim 11, wherein the first sensor is an optical sensor, and wherein the data about potential vehicle operator impairment is generated by monitoring one or more of:

vehicle operator blinks, including one or more of a number, a frequency, or a duration of the vehicle operator blinks;

vehicle operator head nods;

vehicle operator scanning frequency;

or

vehicle operator gaze fixation.

13. The computer system of claim 11, wherein the second sensor is an optical sensor, and wherein the data about potential vehicle operator impairment is generated by monitoring one or more of:

lane deviation;

lane centering; and

time to collision.

14. The computer system of claim 11, wherein the third sensor is an accelerometer, and wherein the data about potential vehicle operator impairment is generated by monitoring one or more of:

fore-aft force to detect hard braking;

fore-aft force change in speed;

or

lateral force.

15. The computer system of claim 11, wherein the first sensor is a first optical sensor, the second sensor is a second optical sensor, and the third sensor is an accelerometer.

16. A non-transitory, computer-readable medium storing instructions that, when executed by one or more processors of a computer system, cause the computer system to:

retrieve data about potential vehicle operator impairment generated during a plurality of trips by monitoring, with a plurality of sensors, (i) a vehicle operator, (ii) an environment ahead of a vehicle of the vehicle operator, and (iii) force in one or more directions;

generate a number of impairment scores by analyzing the data about potential vehicle operator impairment;

determine, based on the impairment scores, a specific time period during which the vehicle operator tends to be most impaired;

identify one or more recommendations to reduce operator impairment of the vehicle operator, the one or more recommendations including a recommendation to avoid driving, or to remove distractions while driving, during at least the specific time period; and

electronically communicate the one or more recommendations to the vehicle operator.

17. The non-transitory, computer-readable medium of claim 16, wherein a first sensor of the plurality of sensors is an optical sensor, and wherein the data about potential vehicle operator impairment is generated by monitoring one or more of:

vehicle operator blinks, including one or more of a number, a frequency, or a duration of the vehicle operator blinks;

vehicle operator head nods;

vehicle operator scanning frequency;

or

vehicle operator gaze fixation.

18. The non-transitory, computer-readable medium of claim 17, wherein a second sensor of the plurality of sensors is an optical sensor, and wherein the data about potential vehicle operator impairment is generated by monitoring one or more of:

lane deviation;

lane centering; and

time to collision.

19. The non-transitory, computer-readable medium of claim 18, wherein a third sensor of the plurality of sensors is an accelerometer, and wherein the data about potential vehicle operator impairment is generated by monitoring one or more of:

fore-aft force to detect hard braking;

fore-aft force change in speed;

or

lateral force.

20. The non-transitory, computer-readable medium of claim 16, wherein a first sensor of the plurality of sensors is a first optical sensor, a second sensor of the plurality of sensors is a second optical sensor, and a third sensor of the plurality of sensors is an accelerometer.