Drowsy driver detection system

• US 8,957,779 B2
• Filed: 06/23/2010
• Issued: 02/17/2015
• Est. Priority Date: 06/23/2009
• Status: Expired due to Fees

• Current Assignee: L&P Property Management Company (Leggett & Platt Incorporated)
• Original Assignee: L&P Property Management Company (Leggett & Platt Incorporated)
• Inventors: Wu, Riheng, Turner, Jason, Browning, Caleb, Brummett, Travis
• Primary Examiner(s): Wu, Daniel
• Assistant Examiner(s): OTT, FREDERICK R
• Application Number:
  US13/379,763
• Publication Number:
  US 20120169503A1
• Time in Patent Office: 1,700 Days
• Field of Search: 340/575
• US Class Current: 340/575
• CPC Class Codes: G08B 21/06 indicating a condition of sleep, e.g. anti-dozing alarms
• CPC Class Codes: G08B 23/00 Alarms responsive to unspecified undesired or abnormal conditions

Abstract

A method of detecting impairment of a driver of a vehicle. The method includes sensing, using a sensor, a position of the driver'"'"'s head at a plurality of time points; determining, using a microprocessor, changes in the position of the driver'"'"'s head between the plurality of time points; evaluating, using a microprocessor, whether the changes in the position of the driver'"'"'s head between the plurality of time points exhibit at least one of a periodic and a quasi-periodic pattern; determining whether the driver is impaired based on the pattern of the changes in the position of the driver'"'"'s head; and if the driver is impaired, alerting the driver using an alarm.

Claims

1. A method of detecting impairment of a driver of a vehicle, comprising:

sensing, using a sensor, a position of the driver'"'"'s head at a plurality of time points;

determining, using a microprocessor, changes in the position of the driver'"'"'s head between the plurality of time points;

evaluating, using a microprocessor, whether the changes in the position of the driver'"'"'s head between the plurality of time points exhibit at least one of a periodic and a quasi-periodic pattern, wherein the step of evaluating comprises performing an autocorrelation function on the changes in the position of the driver'"'"'s head between the plurality of time points, normalizing the results of the autocorrelation function, and performing peak detection on the normalized results to identify a center peak having a center peak amplitude and at least one off-center peak having an off-center peak amplitude;

determining whether the driver is impaired when the at least one off-center peak amplitude is greater than a percentage of the center peak amplitude; and

if the driver is impaired, alerting the driver using an alarm.

2. The method of claim 1, wherein the sensing is performed with an ultrasonic sensor.

3. The method of claim 1, further comprising locating the sensor in a driver'"'"'s seat.

4. The method of claim 1, further comprising locating the sensor in a headrest of the driver'"'"'s seat.

5. The method of claim 1, wherein the plurality of time points comprises a first group of time points and a second group of time points, such that evaluating whether the changes in the position of the driver'"'"'s head between the plurality of time points exhibit at least one of a periodic and a quasi-periodic pattern comprises comparing the at least one of a periodic and a quasi-periodic pattern from the first group of time points with the at least one of a periodic and a quasi-periodic pattern from the second group of time points.

6. The method of claim 1, wherein alerting the driver includes using at least one of an audible alarm and a visual alarm.

7. The method of claim 1, wherein the step of normalizing the results of the autocorrelation function comprises

determining one or more local minima within the autocorrelation results,

fitting the minima to a polynomial function, and

subtracting the polynomial function from the autocorrelation results to obtain normalized results.

8. A system for detecting impairment of a driver of a vehicle, comprising:

a sensor for sensing a position of the driver'"'"'s head at a plurality of time points,

an alarm for alerting the driver; and

a microprocessor, wherein the microprocessor is configured to

determine changes in the position of the driver'"'"'s head between the plurality of time points;

evaluate whether the changes in the position of the driver'"'"'s head between the plurality of time points exhibit at least one of a periodic and a quasi-periodic pattern, wherein, in order to evaluate, the microprocessor is further configured to perform an autocorrelation function on the changes in the position of the driver'"'"'s head between the plurality of time points, normalize the results of the autocorrelation function, and perform peak detection on the normalized results to identify a center peak having a center peak amplitude and at least one off-center peak having an off-center peak amplitude;

determine whether the driver is impaired when the at least one off-center peak amplitude is greater than a percentage of the center peak amplitude; and

if the driver is impaired, alert the driver using the alarm.

9. The system of claim 8, wherein the sensor is an ultrasonic sensor.

10. The system of claim 8, wherein the sensor is located in a driver'"'"'s seat.

11. The system of claim 8, wherein the sensor is located in a headrest of the driver'"'"'s seat.

12. The system of claim 8, wherein the plurality of time points comprises a first group of time points and a second group of time points, wherein the microprocessor being configured to evaluate whether the changes in the position of the driver'"'"'s head between the plurality of time points exhibit at least one of a periodic and a quasi-periodic pattern comprises being configured to compare the at least one of a periodic and a quasi-periodic pattern from the first group of time points with the at least one of a periodic and a quasi-periodic pattern from the second group of time points.

13. The system of claim 8, wherein the alarm includes at least one of an audible alarm and a visual alarm.

14. The system of claim 8, wherein the microprocessor, in order to normalize the results of the autocorrelation function, is further configured to

determine one or more local minima within the autocorrelation results,

fit the minima to a polynomial function, and

subtract the polynomial function from the autocorrelation results to obtain normalized results.