Apparatuses, systems and methods for determining whether a vehicle system is distracting to a vehicle operator

• US 10,147,008 B1
• Filed: 01/13/2016
• Issued: 12/04/2018
• Est. Priority Date: 01/13/2015
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Chan, Aaron Scott, Sanchez, Kenneth Jason
• Primary Examiner(s): MOYER, ANDREW M
• Application Number:
  US14/994,440
• Time in Patent Office: 1,056 Days
• Field of Search: 382104, 382224
• CPC Class Codes: B60R 21/01542 detecting passenger motion
• CPC Class Codes: B60R 21/01552 detecting position of specific human body parts, e.g. face, eyes or hands
• CPC Class Codes: B60R 2300/30 characterised by the type of image processing
• CPC Class Codes: B60R 2300/8006 for monitoring and displaying scenes of vehicle interior, e.g. for monitoring passengers or cargo
• CPC Class Codes: B60W 2040/0872 Driver physiology
• CPC Class Codes: B60W 2050/0095 Automatic control mode change
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2420/54 Audio sensitive means, e.g. ultrasound
• CPC Class Codes: B60W 2540/22 Psychological state; Stress level or workload
• CPC Class Codes: B60W 2540/223 Posture, e.g. hand, foot, or seat position, turned or inclined
• CPC Class Codes: B60W 2540/225 Direction of gaze
• CPC Class Codes: B60W 2540/229 Attention level, e.g. attentive to driving, reading or sleeping
• CPC Class Codes: B60W 2540/26 Incapacity
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: B60W 50/08 Interaction between the driver and the control system
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: B60W 60/0053 from vehicle to occupant
• CPC Class Codes: B60W 60/0059 Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity
• CPC Class Codes: B60Y 2400/30 Sensors
• CPC Class Codes: B60Y 2400/3015 : Optical cameras
• CPC Class Codes: B60Y 2400/3017 : Radars
• CPC Class Codes: G01S 19/42 : Determining position
• CPC Class Codes: G05D 1/0061 : for transition from automatic pilot to manual pilot and vice versa
• CPC Class Codes: G06F 16/51 : Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 18/22 : Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 18/24 : Classification techniques
• CPC Class Codes: G06F 18/2413 : based on distances to training or reference patterns
• CPC Class Codes: G06T 15/005 : General purpose rendering architectures
• CPC Class Codes: G06T 2207/30196 : Human being; Person
• CPC Class Codes: G06T 2207/30268 : Vehicle interior
• CPC Class Codes: G06T 7/337 : involving reference images or patches
• CPC Class Codes: G06T 7/70 : Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06T 7/73 : using feature-based methods
• CPC Class Codes: G06V 20/59 : inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
• CPC Class Codes: G06V 20/593 : Recognising seat occupancy
• CPC Class Codes: G06V 20/597 : Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G06V 20/64 : Three-dimensional objects
• CPC Class Codes: G06V 40/10 : Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G06V 40/11 : Hand-related biometrics; Hand pose recognition
• CPC Class Codes: H04N 19/17 : the unit being an image region, e.g. an object
• CPC Class Codes: H04N 19/423 : characterised by memory arrangements H04N19/433 takes precedence
• CPC Class Codes: H04N 23/45 : for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images

Abstract

Apparatuses, systems and methods are provided for generating data representative of vehicle operator distractions. More particularly, apparatuses, systems and methods are provided for generating data representative of a vehicle operator distractions based on vehicle interior image data and vehicle system operation data. The vehicle interior data may be representative of a three-dimensional coordinate spatial location of at least one joint of a vehicle occupant. The three-dimensional coordinate spatial location of the at least one joint of the vehicle occupant may be tracked over time. The vehicle system operation data may be representative of whether a vehicle system causes a vehicle operator distraction.

Claims

1. A device for determining whether a vehicle system causes vehicle operator distractions by tracking vehicle occupant postures using image recognition, the device comprising:

at least one vehicle interior sensor for acquiring at least one image sequence of at least one vehicle occupant;

a memory for storing the vehicle interior data, vehicle occupant posture data relating to the vehicle interior data, a vehicle interior data receiving module, a three-dimensional coordinate spatial location extraction module, a vehicle system operation data receiving module, a skeletal pose data generation module, and a vehicle system distraction determination module; and

a processor that is configured to determine whether a vehicle system causes vehicle operator distractions by;

receiving vehicle interior data from the at least one vehicle interior sensor in response to the processor executing the vehicle interior data receiving module, wherein the vehicle interior data is representative of whether a vehicle system causes a vehicle operator distraction;

creating a vehicle occupant posture record for the at least one vehicle occupant comprising the vehicle interior data of the at least one vehicle occupant;

extracting three-dimensional coordinate spatial locations of at least one joint location of the at least one vehicle occupant from the vehicle interior data in response to the processor executing the three-dimensional coordinate spatial location extraction module, wherein the three-dimensional coordinate spatial locations of at least one joint location of the at least one vehicle occupant are stored in the vehicle occupant posture record as vehicle occupant posture data relating to the vehicle interior data;

receiving vehicle system operation data from a vehicle system in response to the processor executing the vehicle system operation data receiving module, wherein the vehicle system operation data is representative of whether a vehicle system causes a vehicle operator distraction;

determining whether a vehicle system causes a vehicle operator distraction based on the vehicle interior data and the vehicle system operation data in response to the processor executing the vehicle system distraction determination module; and

automatically updating the vehicle occupant posture record with the vehicle posture data, wherein the vehicle occupant posture record is representative of a first posture of the at least one vehicle occupant that corresponds to a range of movement of a posture that the at least one vehicle occupant was oriented for a longest period of total time over at least two occurrences within a predetermined period of time.

2. The device as in claim 1, wherein the at least one vehicle interior sensor is selected from:

at least one digital image sensor, at least one ultra-sonic sensor, at least one radar-sensor, at least one infrared light sensor, or at least one laser light sensor.

3. The device as in claim 1, further comprising:

a previously classified vehicle interior data receiving module stored on the memory that, when executed by the processor, causes the processor to receive previously classified vehicle interior data, wherein the previously classified vehicle interior data is representative of known vehicle operator distractions, wherein execution of the vehicle distraction determination module causes the processor to determine whether a vehicle system causes a vehicle operator distraction based on a comparison of the vehicle interior data with the previously classified vehicle interior data.

4. The device as in claim 1, wherein the vehicle system operation data is representative of operation of at least one of:

a vehicle heating, ventilating, and air condition system, a vehicle entertainment system, a vehicle radio, a vehicle navigation system, a vehicle cruise control system, a vehicle lighting system, a vehicle communication system, a vehicle seat control system, a vehicle windshield wiper system, a vehicle steering wheel adjustment system, a vehicle braking system, a vehicle warning system, a vehicle trip distance logging system, a vehicle fuel indicator, or a vehicle system maintenance indicator.

5. The device as in claim 3, further comprising:

an image feature extraction module stored on the memory that, when executed by the processor, causes the processor to extract image features from the previously classified vehicle interior data, wherein execution of the vehicle system distraction determination module causes the processor to determine whether a vehicle system causes a vehicle operator distraction based on a comparison of the vehicle interior data with the image features extracted from the previously classified vehicle interior data.

6. The device as in claim 1, further comprising:

a current image data receiving module stored on a memory that, when executed by a processor, causes the processor to receive current image data, wherein the current image data includes images and/or extracted image features that are representative of a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, or a vehicle occupant looking at themselves in a mirror, and wherein execution of the vehicle system distraction determination module further causes the processor to determine whether the vehicle system causes the vehicle operator distraction based on the current image data.

7. The device as in claim 3, further comprising:

a previously classified image data receiving module stored on the memory that, when executed by the processor, causes the processor to receive previously classified image data, wherein the previously classified image data includes images and/or extracted image features that have previously been classified as being representative of a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, or a vehicle occupant looking at themselves in a mirror, and wherein execution of the vehicle system distraction determination module further causes the processor to determine whether the vehicle system causes the vehicle operator distraction based on the previously classified image data.

8. A computer-implemented method for determining whether a vehicle system causes vehicle operator distraction by tracking vehicle occupant postures using image recognition, the method comprising:

receiving, at a processor, vehicle interior data from at least one vehicle interior sensor, wherein the vehicle interior data is representative of a series of three-dimensional coordinate spatial locations of at least one joint location of a vehicle occupant;

creating a vehicle occupant posture record for the at least one vehicle occupant comprising the vehicle interior data of the at least one vehicle occupant;

extracting three-dimensional coordinate spatial locations of at least one joint location of the at least one vehicle occupant from the vehicle interior data in response to the processor executing a three-dimensional coordinate spatial location extraction module, wherein the three-dimensional coordinate spatial locations of at least one joint location of the at least one vehicle occupant are stored in the vehicle occupant posture record as vehicle occupant posture data relating to the vehicle interior data;

receiving, at the processor, vehicle system operation data from a vehicle system, wherein the vehicle system operation data is representative of whether a vehicle system causes a vehicle operator distraction;

recognizing and tracking, using a processor, postures of the at least one vehicle occupant in the image sequence as vehicle occupant posture data by processing the three-dimensional coordinate spatial locations of at least one joint location of the at least one vehicle occupant in response to the processor executing a skeletal pose data generation module and adding the vehicle occupant posture data to the vehicle occupant posture record;

determining, using the processor, whether the vehicle system causes a vehicle operator distraction based on the vehicle interior data and the vehicle system operation data in response to the processor executing the vehicle system distraction determination module; and

automatically updating the vehicle occupant posture record with the vehicle posture data, wherein the vehicle occupant posture record is representative of a first posture of the at least one vehicle occupant that corresponds to a range of movement of a posture that the at least one vehicle occupant was oriented for a longest period of total time over at least two occurrences within a predetermined period of time.

9. The method as in claim 8, wherein the at least one vehicle interior sensor is selected from:

at least one digital image sensor, at least one ultra-sonic sensor, at least one radar-sensor, at least one infrared light sensor, or at least one laser light sensor.

10. The method as in claim 8, further comprising:

receiving, at the processor, previously classified vehicle interior data, wherein the previously classified vehicle interior data is representative of known vehicle operator distractions, wherein execution of the vehicle distraction determination module causes the processor to determine whether a vehicle system causes a vehicle operator distraction based on a comparison of the vehicle interior data with the previously classified vehicle interior data.

11. The method as in claim 8, wherein the vehicle system operation data is representative of operation of at least one of:

a vehicle heating, ventilating, and air condition system, a vehicle entertainment system, a vehicle radio, a vehicle navigation system, a vehicle cruise control system, a vehicle lighting system, a vehicle communication system, a vehicle seat control system, a vehicle windshield wiper system, a vehicle steering wheel adjustment system, a vehicle braking system, a vehicle warning system, a vehicle trip distance logging system, a vehicle fuel indicator, or a vehicle system maintenance indicator.

12. The method as in claim 10, further comprising:

extracting, using the processor, image features from the previously classified vehicle interior data, wherein execution of the vehicle system operation distraction determination module causes the processor to determine whether the vehicle system causes vehicle operator distractions based on a comparison of the vehicle interior data with the image features extracted from the previously classified vehicle interior data.

13. The method as in claim 8, further comprising:

receiving current image data, wherein the current image data includes images and/or extracted image features that are representative of a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, or a vehicle occupant looking at themselves in a mirror, and wherein determining whether the vehicle system causes the vehicle operator distraction is further based on the current image data.

14. The method as in claim 10, further comprising:

receiving previously classified image data, wherein the previously classified image data includes images and/or extracted image features that have previously been classified as being representative of a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, or a vehicle occupant looking at themselves in a mirror, and wherein determining whether the vehicle system causes the vehicle operator distraction is further based on the previously classified image data.

15. A non-transitory computer-readable medium storing computer-readable instructions that, when executed by a processor, cause the processor to determine whether a vehicle system causes vehicle operator distractions by tracking vehicle occupant postures using image recognition, the non-transitory computer-readable medium comprising:

vehicle interior data, vehicle occupant posture data relating to the vehicle interior data, a vehicle interior data receiving module, a vehicle system operation data receiving module, a skeletal pose data generation module, and a vehicle system distraction determination module; and

a processor that is configured to determine whether a vehicle system causes vehicle operator distractions by;

receiving vehicle interior data from at least one vehicle interior sensor in response to the processor executing the vehicle interior data receiving module, wherein the vehicle interior data is representative of whether a vehicle system causes a vehicle operator distraction;

creating a vehicle occupant posture record for the at least one vehicle occupant comprising the vehicle interior data of the at least one vehicle occupant;

extracting three-dimensional coordinate spatial locations of at least one joint location of the at least one vehicle occupant from the vehicle interior data in response to the processor executing a three-dimensional coordinate spatial location extraction module, wherein the three-dimensional coordinate spatial locations of at least one joint location of the at least one vehicle occupant are stored in the vehicle occupant posture record as vehicle occupant posture data relating to the vehicle interior data;

receiving vehicle system operation data from a vehicle system in response to the processor executing the vehicle system operation data receiving module, wherein the vehicle system operation data is representative of whether a vehicle system causes a vehicle operator distraction;

determining whether a vehicle system causes a vehicle operator distraction based on the vehicle interior data and the vehicle system operation data in response to the processor executing the vehicle system distraction determination module; and

automatically updating the vehicle occupant posture record with the vehicle posture data, wherein the vehicle occupant posture record is representative of a first posture of the at least one vehicle occupant that corresponds to a range of movement of a posture that the at least one vehicle occupant was oriented for a longest period of total time over at least two occurrences within a predetermined period of time.

16. The non-transitory computer-readable medium as in claim 15, further comprising:

a previously classified vehicle interior data receiving module that, when executed by the processor, causes the processor to receive previously classified vehicle interior data, wherein the previously classified vehicle interior data is representative of known vehicle operator distractions, wherein execution of the vehicle distraction determination module causes the processor to determine whether a vehicle system causes a vehicle operator distraction based on a comparison of the vehicle interior data with the previously classified vehicle interior data.

17. The non-transitory computer-readable medium as in claim 16, further comprising:

an image feature extraction module that, when executed by the processor, causes the processor to extract image features from the previously classified vehicle interior data, wherein execution of the vehicle system distraction determination module causes the processor to determine whether a vehicle system causes a vehicle operator distraction based on a comparison of the vehicle interior data with the image features extracted from the previously classified vehicle interior data.

18. The non-transitory computer-readable medium as in claim 15, further comprising:

a current image data receiving module that, when executed by a processor, causes the processor to receive current image data, wherein the current image data includes images and/or extracted image features that are representative of a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, or a vehicle occupant looking at themselves in a mirror, and wherein execution of the vehicle system distraction determination module further causes the processor to determine whether the vehicle system causes the vehicle operator distraction based on the current image data.

19. The non-transitory computer-readable medium as in claim 16, further comprising:

a previously classified image data receiving module that, when executed by the processor, causes the processor to receive previously classified image data, wherein the previously classified image data includes images and/or extracted image features that have previously been classified as being representative of a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, or a vehicle occupant looking at themselves in a mirror, and wherein execution of the vehicle system distraction determination module further causes the processor to determine whether the vehicle system causes the vehicle operator distraction based on the previously classified image data.

20. The non-transitory computer-readable medium as in claim 15, wherein the vehicle system operation data is representative of operation of at least one of:

a vehicle heating, ventilating, and air condition system, a vehicle entertainment system, a vehicle radio, a vehicle navigation system, a vehicle cruise control system, a vehicle lighting system, a vehicle communication system, a vehicle seat control system, a vehicle windshield wiper system, a vehicle steering wheel adjustment system, a vehicle braking system, a vehicle warning system, a vehicle trip distance logging system, a vehicle fuel indicator, or a vehicle system maintenance indicator.