Systems and methods for assessing equipment operator fatigue and using fatigue-risk-informed safety-performance-based systems and methods to replace or supplement prescriptive work-rest regulations

• US 20060200008A1
• Filed: 03/01/2006
• Published: 09/07/2006
• Est. Priority Date: 03/02/2005
• Status: Active Grant

• Current Assignee: Martin Moore-Ede
• Original Assignee: Martin Moore-Ede
• Inventors: Moore-Ede, Martin
• Granted Patent: US 8,075,484 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: B60K 28/06 responsive to incapacity of driver
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics

Abstract

In a system and method for assessing and modifying fatigue, an input device receives current work-rest pattern and/or sleep data from an individual. A data aggregation and processing platform combines the current work-rest pattern and/or sleep data with previous data related to the individual to generate a fatigue assessment result, a diagnostic assessment result, and a corrective intervention result. At least one output display outputs the fatigue assessment result, diagnostic assessment result and corrective intervention result in a user-readable format to a user. The user uses this information to revise the work-rest pattern to reduce or control future fatigue risk.

Claims

1. A fatigue risk assessment and modification system, comprising:

an input device that receives at least one of current work-rest pattern and sleep data from an individual;

a data aggregation and processing platform that combines the at least one of the current work-rest pattern and the sleep data with previous data related to the individual to generate at least one of a fatigue assessment result, a diagnostic assessment report that includes a causation of excessive fatigue risk, and a corrective intervention plan for reducing future fatigue risk; and

at least one output display that outputs the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan in a user-readable format to a user.

2. The system of claim 1, wherein the input device generates a current record from the at least one of the current work-rest pattern and the sleep data related to the individual, and wherein the data aggregation and processing platform stores the current record.

3. The system of claim 1 further comprising a plurality of input devices that receives at least one of current work-rest pattern and sleep data from a plurality of individuals, wherein the data aggregation and processing platform receives the at least one of the current work-rest pattern and the sleep data from each input device and generates at least one of a fatigue assessment result, a diagnostic assessment report that includes a causation of excessive fatigue risk, and a corrective intervention plan for reducing future fatigue risk for each individual.

4. The system of claim 1 further comprising a position verification device that verifies the at least one of the current work-rest pattern and the sleep data.

5. The system of claim 4, wherein the position verification device determines a first location of the individual at successive intervals of time and determines whether the individual has moved to a second location by comparing locations.

6. The system of claim 1 further comprising an engine control module that collects data on movements of a machine that is operated by the individual and verifies the at least one of the current work-rest pattern and the sleep data by determining whether the machine has moved.

7. The system of claim 1, wherein the at least one of the current work-rest pattern and the sleep data is collected from worker logs and manually entered into the input device.

8. The system of claim 1, wherein the at least one of the current work-rest pattern and the sleep data is collected from electronic logs and electronically entered into the input device.

9. The system of claim 1, wherein the at least one of the current work-rest pattern and the sleep data is transmitted from the input device to the data aggregation and processing platform through a communications network.

10. The system of claim 9, wherein the communications network is one of a satellite communications network, a wireless network, a telecommunications network, and a data communications network.

11. The system of claim 1, wherein the data aggregation and processing platform comprises a fatigue risk processor that computes the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan from the at least one of the current work-rest pattern and the sleep data.

12. The system of claim 11, wherein at least one predictive model is applied to the fatigue risk processor to compute the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan.

13. The system of claim 12, wherein the predictive model complies with a Fatigue-Risk-Informed Safety-Performance-Based (FRISPB) paradigm.

14. The system of claim 12, wherein the predictive model is at least one of a fatigue risk model and a driver profile model, the fatigue risk model for computing the fatigue assessment result as a fatigue risk score, the diagnostic assessment report, and the corrective intervention plan, and a driver profile model for computing a driver profile result that includes other non-fatigue causes of risk.

15. The system of claim 14, wherein the fatigue risk score and the driver profile result are combined to generate a driver risk assessment.

16. The system of claim 15, wherein the driver risk assessment is output to the output display.

17. The system of claim 1, wherein the user uses the fatigue assessment result to control fatigue risk in the individual using a diagnostic assessment report on the causation of excessive fatigue risk, and a corrective intervention plan to reduce future fatigue risk.

18. The system of claim 1, wherein the individual is a commercial motor vehicle driver.

19. The system of claim 18, wherein the fatigue risk assessment system is installed in a machine in a vehicle that is operated by the driver.

20. The system of claim 1, wherein the individual is a machine operator.

21. The system of claim 20, wherein the fatigue risk assessment system is installed in a machine that is operated by the machine operator.

22. The system of claim 1, wherein the input device and the output display are the same.

23. A method for assessing fatigue and distributing a fatigue assessment and modification result comprising:

receiving at least one of current work-rest pattern and sleep data from an individual;

combining the at least one of the current work-rest pattern and the sleep data with previous data related to the individual;

generating at least one of a fatigue assessment result from the combination of the current work-rest pattern and the sleep data and previous data related to the individual, a diagnostic assessment report on the causation of any excessive fatigue risk, and a corrective intervention plan for reducing fatigue risk; and

outputting the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan in a user-readable format to a user.

24. The method of claim 23 further comprising:

generating a current record from the at least one of the current work-rest pattern and the sleep data related to the individual; and

storing the current record.

25. The method of claim 23, wherein the at least one of the current work-rest pattern and the sleep data is received from a group of individuals, and wherein the fatigue assessment result is generated for each individual.

26. The method of claim 23 further comprising verifying the at least one of the current work-rest pattern and the sleep data.

27. The method of claim 23 further comprising transmitting the at least one of the current work-rest pattern and the sleep data through a communications network.

28. The method of claim 27, wherein the communications network is one of a satellite communications network, a wireless network, a telecommunications network, and a data communications network.

29. The method of claim 23 further comprising applying at least one predictive model to compute the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan.

30. The method of claim 29, wherein the predictive model complies with a Fatigue-Risk-Informed Safety-Performance-Based (FRISPB) paradigm.

31. The method of claim 29 further comprising at least one of computing the fatigue assessment result as a fatigue risk score and computing a non-fatigue factor assessment result as a driver profile result.

32. The method of claim 31 further comprising generating a driver risk assessment from a combination of the fatigue risk score and the driver profile result.

33. The method of claim 23 comprising using the fatigue assessment result to control fatigue risk in the individual.

34. The method of claim 23 comprising combining the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan to reduce future fatigue risk.

35. The method of claim 23, wherein the individual is at least one of a machine operator and a driver.

36. A method for assessing operator fatigue comprising:

collecting at least one of work-rest pattern and sleep status data from at least one operator;

validating the least one of the work-rest pattern and the sleep status data;

combining the validated at least one of the work-rest pattern and the sleep status data with at least one of previously collected work-rest pattern and sleep data in a data aggregation and processing platform;

generating at least one of a fatigue assessment result, a diagnostic assessment report, and a corrective intervention plan from the validated at least one of the work-rest pattern and the sleep status data and the at least one of the previously collected work-rest pattern and sleep data; and

displaying the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan in a user-readable format.

37. The method of claim 36, wherein the at least one of the work-rest pattern and the sleep status data is validated by locating a commercial vehicle that is operated by the operator.

38. The method of claim 36, wherein the at least one of the work-rest pattern and the sleep status data is validated by locating a machine that is operated by the operator at intervals of time to compare a first location and a second location of the machine to determine a movement of the machine.

39. The method of claim 36 further comprising applying at least one predictive model to compute the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan.

40. The method of claim 39, wherein the predictive model complies with a Fatigue-Risk-Informed Safety-Performance-Based (FRISPB) paradigm.

41. The method of claim 39 further comprising at least one of computing the fatigue assessment result as a fatigue risk score, and computing a non-fatigue factor assessment result as an operator profile result.

42. The method of claim 41 further comprising generating an operator risk assessment from a combination of the fatigue risk score and the operator profile result.

43. The method of claim 36 further comprising using the fatigue assessment result to control fatigue risk in the operator.

44. The method of claim 36 further comprising using the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan to reduce fatigue risk in the operator.

45. A fatigue risk assessment system for assessing fatigue in a truck driver, comprising:

an input device that receives at least one of current work-rest pattern and sleep data from the truck driver;

a data aggregation and processing platform that combines the at least one of the current work-rest pattern and the sleep data with previous data related to the truck driver to generate at least one of a fatigue assessment result, a diagnostic assessment report, and a corrective intervention plan from the at least one of the current work-rest pattern and the sleep data; and

at least one output display that outputs at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan in a user-readable format to a user.

46. The system of claim 45 further comprising a plurality of input devices that receives at least one of current work-rest pattern and sleep data from group of truck drivers, wherein the data aggregation and processing platform receives the at least one of the current work-rest pattern and the sleep data from each input device and generates at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan for each truck driver.

47. The system of claim 45 further comprising a position verification device that verifies the at least one of the current work-rest pattern and the sleep data.

48. The system of claim 45, wherein the at least one of the current work-rest pattern and the sleep data is transmitted from the input device to the data aggregation and processing platform through a communications network.

49. The system of claim 45, wherein the data aggregation and processing platform comprises a fatigue risk processor that computes the at least one of the fatigue assessment result, the diagnostic assessment report, and the corrective intervention plan from the at least one of the current work-rest pattern and the sleep data.

50. The system of claim 49, wherein at least one predictive model is applied to the fatigue risk processor to compute the fatigue assessment result.

51. The system of claim 50, wherein the predictive model complies with a Fatigue-Risk-Informed Safety-Performance-Based (FRISPB) paradigm.

52. The system of claim 50, wherein the predictive model is at least one of a fatigue risk model and a driver profile model, the fatigue risk model for computing the fatigue assessment result as a fatigue risk score, the diagnostic assessment report, and the corrective intervention plan, and a driver profile model for computing a driver profile result that includes other non-fatigue causes of risk.

53. The system of claim 52, wherein the fatigue risk score and the driver profile result are combined to generate a driver risk assessment.

54. The system of claim 53, wherein the driver risk assessment is output to the output display.

55. The system of claim 53, wherein the at least one of the driver risk assessment, the diagnostic assessment result, and the corrective intervention result is output to the output display.

56. The system of claim 45, wherein the fatigue risk assessment system is installed in a commercial motor vehicle that is operated by the truck driver.

57. A method for assessing truck driver fatigue comprising:

collecting at least one of work-rest pattern and sleep status data from at least one truck driver;

locating a commercial motor vehicle operated by the truck driver;

relocating a location of the commercial motor vehicle after a time interval and determining if the vehicle has moved;

updating the at least one of the work-rest pattern and sleep data to include at least one of validated work-rest pattern and sleep data of the driver of the commercial motor vehicle;

combining the at least one of the validated work-rest pattern and the sleep data with previously collected data in a data aggregation and processing platform;

generating at least one of a fatigue assessment result, a diagnostic assessment result, and a corrective intervention result from the validated work-rest pattern and the sleep data and the previously collected data; and

displaying the fatigue assessment result, the diagnostic assessment result, and the corrective intervention result in a user-readable format.

58. The method of claim 57, wherein the predictive model complies with a Fatigue-Risk-Informed Safety-Performance-Based (FRISPB) paradigm.

59. The method of claim 57 further comprising applying at least one predictive model to compute the fatigue assessment result, the diagnostic assessment result, and the corrective intervention result.

60. The method of claim 59 further comprising at least one of computing the fatigue assessment result as a truck driver fatigue risk score, the diagnostic assessment result, and the corrective intervention result, and computing a truck driver profile result that includes other non-fatigue causes of risk.

61. The method of claim 60 further comprising generating a truck driver risk assessment from a combination of the truck driver fatigue risk score and the truck driver profile result.

62. The method of claim 60 further comprising using the truck driver profile assessment result, the diagnostic assessment result, and the corrective intervention result to control fatigue risk in the truck driver.