System, apparatus and associated methodology for interactively monitoring and reducing driver drowsiness

• US 8,098,165 B2
• Filed: 02/27/2009
• Issued: 01/17/2012
• Est. Priority Date: 02/27/2009
• Status: Active Grant

• Current Assignee: Toyota Motor Corporation
• Original Assignee: Toyota Motor Engineering & Manufacturing North America Incorporated (Toyota Motor Corporation)
• Inventors: Demirdjian, David, Varri, Chenna K.
• Primary Examiner(s): Previl, Daniel
• Application Number:
  US12/394,125
• Publication Number:
  US 20100219955A1
• Time in Patent Office: 1,054 Days
• Field of Search: 340/575, 340/576, 340/439, 340/435, 340/438, 340/691.1, 340901-903, 340/309.16, 340/309.4, 340/545.4, 340/436, 340/425.5
• US Class Current: 340/575
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2562/0247 Pressure sensors
• CPC Class Codes: A61B 2562/043 in a linear array
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/18 for vehicle drivers or machine operators
• CPC Class Codes: A61B 5/6892 Mats
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: B60K 28/06 responsive to incapacity of driver
• CPC Class Codes: G08B 21/06 indicating a condition of sleep, e.g. anti-dozing alarms

Abstract

A system, apparatus and associated methodology for interactively monitoring and reducing driver drowsiness use a plurality of drowsiness detection exercises to precisely detect driver drowsiness levels, and a plurality of drowsiness reduction exercises to reduce the detected drowsiness level. A plurality of sensors detect driver motion and position in order to measure driver performance of the drowsiness detection exercises and/or the drowsiness reduction exercises. The driver performance is used to compute a drowsiness level, which is then compared to a threshold. The system provides the driver with drowsiness reduction exercises at predetermined intervals when the drowsiness level is above the threshold.

Claims

1. A system for monitoring and reducing driver drowsiness, comprising:

a plurality of sensors configured to sense driver position and motion;

an electronic storage unit configured to store an exercise database including a plurality of drowsiness detection exercises and a plurality of drowsiness reduction exercises;

an input/output interface configured to transmit information to a driver, and configured to receive information from the driver; and

a data processor configured to

select a drowsiness detection exercise from the exercise database,

instruct the drowsiness detection exercise to the driver via the input/output interface,

monitor driver performance of the instructed drowsiness detection exercise via the plurality of sensors,

generate a drowsiness level by comparing the driver performance of the instructed drowsiness detection exercise to a model performance of the instructed drowsiness detection exercise, and

compare the drowsiness level to a predetermined threshold,

wherein the data processor instructs a drowsiness reduction exercise to the driver at predetermined time intervals and monitors driver performance thereof, when the drowsiness level exceeds a predetermined threshold.

2. The system for monitoring and reducing driver drowsiness according to claim 1, wherein the data processor generates parameters including at least one of an exercise intensity, a limb velocity and a limb spatial position based on the driver performance, and generates the drowsiness level by comparing the generated parameters to parameters corresponding to the model performance.

3. The system for monitoring and reducing driver drowsiness according to claim 1, wherein the data processor stores a non-drowsy driver performance in an electronic memory, and adjusts the model performance based on the non-drowsy driver performance, the drowsiness level being generated based on the adjusted model performance.

4. The system for monitoring and reducing driver drowsiness according to claim 1, wherein the input/output interface receives an exercise category selection, and the data processor selects drowsiness detection exercises and drowsiness reduction exercises from the selected category.

5. The system for monitoring and reducing driver drowsiness according to claim 1, wherein the input/output interface receives an exercise category rejection, and the data processor selects drowsiness detection exercises and drowsiness reduction exercises from categories other than the rejected category.

6. The system for monitoring and reducing driver drowsiness according to claim 1, wherein the plurality of sensors include at least one of a plurality of pressure sensors arranged on a driver seat and a plurality of cameras facing the driver seat.

7. The system for monitoring and reducing driver drowsiness according to claim 6, wherein the plurality of sensors also includes an accelerometer arranged on a driver seatbelt.

8. The system for monitoring and reducing driver drowsiness according to claim 1, further comprising:

a display unit connected to the input/output interface and configured to provide a current drowsiness level to the driver.

9. A system for monitoring and reducing driver drowsiness, comprising:

a plurality of sensors configured to sense driver position and motion;

an electronic storage unit configured to store an exercise database including a plurality of drowsiness detection exercises and a plurality of drowsiness reduction exercises;

an input/output interface configured to transmit information to a driver, and configured to receive information from the driver; and

a data processor configured to select a drowsiness detection exercise from the exercise database, and configured to provide the drowsiness detection exercise to the driver via the input/output interface, the data processor monitoring driver performance of the drowsiness detection exercise via the plurality of sensors and generating a drowsiness level in accordance with the driver performance and a model performance of the drowsiness detection exercise,

wherein the data processor provides a drowsiness reduction exercise to the driver at predetermined time intervals and monitors driver performance thereof, when the drowsiness level exceeds a predetermined threshold, and

wherein the data processor compares a drowsiness level, corresponding to an exercise, to an effectiveness threshold, and deemphasizes a category corresponding to the exercise when the drowsiness level is below the effectiveness threshold, the data processor selecting a further exercise from a category other than the deemphasized category, the exercise and the further exercise being one of a drowsiness detection exercise and a drowsiness reduction exercise.

10. A method for monitoring and reducing driver drowsiness, comprising:

selecting, from an exercise database stored in an electronic storage unit, a drowsiness detection exercise, the database including a plurality of drowsiness detection exercises and a plurality of drowsiness reduction exercises;

instructing, via an input/output interface, the drowsiness detection exercise to a driver;

monitoring, via a plurality of sensors, driver performance of the instructed drowsiness detection exercise;

determining, in a data processor, a drowsiness level based on a comparison of the driver performance of the instructed drowsiness detection exercise with a model performance of the drowsiness detection exercise; and

comparing the drowsiness level to a drowsiness threshold,

wherein a drowsiness reduction exercise is instructed to the driver at predetermined time intervals when the drowsiness level is above the drowsiness threshold.

11. The method of monitoring and reducing driver drowsiness according to claim 10, further comprising:

generating parameters including at least one of an exercise intensity, a limb velocity and a limb spatial location based on the driver performance;

comparing the generated parameters to a model set of parameters corresponding to the model performance; and

generating a drowsiness level based on the difference between the generated parameters and the model set of parameters.

12. The method of monitoring and reducing driver drowsiness according to claim 10, further comprising:

monitoring non-drowsy driver performance;

storing the non-drowsy driver performance in the electronic storage unit; and

adjusting the model performance based on the non-drowsy driver performance,

wherein the drowsiness level is computed based on the adjusted model performance.

13. The method of monitoring and reducing driver drowsiness according to claim 10, further comprising:

receiving a driver input via the input/output interface;

selecting at least one of a drowsiness detection exercise and a drowsiness reduction exercise from a selected category, when the driver input is a category selection; and

selecting at least one of a drowsiness detection exercise and a drowsiness reduction exercise from a category other than a rejected category, when the driver input is a category rejection.

14. The method for monitoring and reducing driver drowsiness according to claim 10, further comprising:

displaying, on a display unit, a current drowsiness level.

15. A method for monitoring and reducing driver drowsiness, comprising:

selecting, from an exercise database stored in an electronic storage unit, a drowsiness detection exercise, the database including a plurality of drowsiness detection exercises and a plurality of drowsiness reduction exercises;

providing, via an input/output interface, the drowsiness detection exercise to a driver;

monitoring, via a plurality of sensors, driver performance of the drowsiness detection exercise;

determining, in a data processor, a drowsiness level based on the driver performance and a model performance of the drowsiness detection exercise;

comparing the drowsiness level to a drowsiness threshold, a drowsiness reduction exercise being provided to the driver at predetermined time intervals when the drowsiness level is above the drowsiness threshold

determining an exercise effectiveness for an exercise based on a drowsiness level corresponding thereto; and

de-emphasizing an exercise category corresponding to the exercise when the exercise effectiveness is below a predetermined effectiveness threshold,

wherein a further exercise is selected from exercise categories other than the de-emphasized category, the exercise and the further exercise being one of a drowsiness detection exercise and a drowsiness reduction exercise.

16. An apparatus for monitoring and reducing driver drowsiness, comprising:

means for storing an exercise database including a plurality of drowsiness detection exercises and a plurality of drowsiness reduction exercises;

means for selecting a drowsiness detection exercise from the drowsiness detection exercise from the exercise database;

means for instructing the drowsiness detection exercise to a driver;

means for monitoring driver performance of the instructed drowsiness detection exercise;

means for generating a drowsiness level by comparing the driver performance of the instructed drowsiness detection exercise to a model performance of the drowsiness detection exercise;

means for comparing the drowsiness level to a predetermined threshold; and

means for instructing a drowsiness reduction exercise to the driver at predetermined time intervals when the drowsiness level exceeds a predetermined drowsiness threshold.

17. The apparatus for monitoring and reducing driver drowsiness according to claim 16, further comprising:

means for deriving parameters including at least one of an exercise intensity, a limb velocity and a limb spatial position from the driver performance;

means for generating the drowsiness level based on the derived parameters and a model set of parameters derived from the model performance.

18. The apparatus for monitoring and reducing driver drowsiness according to claim 16, further comprising:

means for storing a non-drowsy driver performance; and

means for adjusting the model performance based on the non-drowsy driver performance,

wherein the drowsiness level is generated based on the adjusted model performance.

19. The apparatus for monitoring and reducing driver drowsiness according to claim 16, further comprising:

means for receiving a driver input,

wherein at least one of a drowsiness detection exercise and a drowsiness reduction exercise is selected from a selected category, when the driver input indicates the selected category, and at least one of a drowsiness detection exercise and a drowsiness reduction exercise is selected from a category other than a rejected category, when the driver input indicates the rejected category.

20. An apparatus for monitoring and reducing driver drowsiness, comprising:

means for storing an exercise database including a plurality of drowsiness detection exercises and a plurality of drowsiness reduction exercises;

means for selecting a drowsiness detection exercise from the drowsiness detection exercise from the exercise database;

means for providing the drowsiness detection exercise to a driver;

means for monitoring driver performance of the drowsiness detection exercise;

means for generating a drowsiness level based on the driver performance and a model performance of the drowsiness detection exercise;

means for providing a drowsiness reduction exercise to the driver at predetermined time intervals when the drowsiness level exceeds a predetermined drowsiness threshold;

means for determining an exercise effectiveness corresponding to an exercise provided to the driver, the exercise effectiveness being determined in accordance with the drowsiness level; and

means for de-emphasizing an exercise category corresponding to the exercise when the exercise effectiveness is below a predetermined effectiveness threshold,

wherein a further exercise is selected from categories other than the de-emphasized category, the exercise and the further exercise being one of a drowsiness detection exercise and a drowsiness reduction exercise.