Vehicular collision avoidance system

• US 7,124,027 B1
• Filed: 07/11/2002
• Issued: 10/17/2006
• Est. Priority Date: 07/11/2002
• Status: Active Grant

• Current Assignee: Yazaki North America Incorporated (Yazaki Corporation)
• Original Assignee: Yazaki North America Incorporated (Yazaki Corporation)
• Inventors: Wilson, Terry B., Ernst, Jr., Raymond P.
• Primary Examiner(s): ARTHUR JEANGLAUDE, GERTRUDE
• Application Number:
  US10/193,512
• Time in Patent Office: 1,559 Days
• Field of Search: 701/1, 701/300, 701/301, 701/45, 701/96, 340/435, 340/436, 340/438, 342/29, 342/70, 342/72
• US Class Current: 701/301
• CPC Class Codes: B60W 30/08 Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 40/02 related to ambient conditions
• 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: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 2013/9316 combined with communication equipment with other vehicles or with base stations
• CPC Class Codes: G01S 2013/93185 Controlling the brakes
• CPC Class Codes: G01S 2013/932 using own vehicle data, e.g. ground speed, steering wheel direction
• CPC Class Codes: G01S 2013/9321 Velocity regulation, e.g. cruise control
• CPC Class Codes: G01S 2013/9322 using additional data, e.g. driver condition, road state or weather data
• CPC Class Codes: G01S 2013/93271 in the front of the vehicles

Abstract

A collision avoidance system for use in a vehicle. The system facilitates the avoidance of other vehicles and other potential hazards or obstacles. A sensor subsystem is used to capture sensor data relating to one or more areas outside the vehicle. Sensor data is sent from the sensor subsystem to a threat assessment subsystem for generating a threat assessment from the sensor data. The threat assessment is then sent to a feedback subsystem so that if appropriate, a response is generated by the system. The response can take the form of a visual, audio, and/or haptic warning. The response can also take the form of changes with respect to the vehicle itself, such as an automatic reduction in speed. The system can incorporate user-based attributes, vehicle-based attributes, and environment-based attributes in evaluating potential threats and contemplating system responses to those threats. A wide variety of different heuristics can be applied by the system. The system can be configured to minimize nuisance alarms and accommodate distinctions between users based on user preferences, user history, and other factors.

Claims

1. A collision avoidance system for a vehicle, comprising:

a sensor subsystem, wherein said sensor subsystem provides for the capture of sensor data from a radar measurement external to the vehicle;

an identification technology for storing internal attributes associated with a user of the vehicle;

a threat analysis subsystem, wherein said threat analysis subsystem provides for generating a threat assessment from said sensor data and a selected internal attribute from said identification technology; and

a feedback subsystem for processing said threat assessment and generating a feedback response from said threat assessment.

2. The system of claim 1, further comprising an accident information transmittal module, wherein said accident information transmittal module transmits an accident report after an accident.

3. The system of claim 1, further comprising an information sharing module and a target vehicle, wherein said information sharing module receives data from said target vehicle.

4. The system of claim 1, further comprising an information sharing module and a target vehicle, wherein said information sharing module transmits data to said target vehicle.

5. The system of claim 1, said threat assessment subsystem further including a plurality of modes, said plurality of modes comprising a headway maintenance mode and a speed maintenance mode.

6. The system of claim 5, further comprising an operator control mode.

7. The system of claim 1, wherein said threat assessment is a braking level and wherein said selected internal attribute is a predefined braking preference threshold, and wherein said feedback is determined by whether said braking level exceeds said predefined braking preference threshold.

8. The system of claim 1, further comprising a simulation component, wherein said selected internal attribute is set with said simulation component.

9. The system of claim 1, wherein said feedback subsystem provides for generating said feedback response from said selected internal attribute.

10. The system of claim 1, wherein said selected internal attribute is a user-specific attribute.

11. The system of claim 10, wherein said user-specific attribute is a selection-based attribute.

12. The system of claim 10, wherein said user-specific attribute is a history-based attribute.

13. The system of claim 10, wherein said user-specific attribute is a condition-based attribute.

14. The system of claim 1, wherein said identification technology comprises a smart card.

15. The system of claim 1, wherein said sensor data is a radar measurement from only one radar.

16. The system of claim 15, wherein said radar measurement is a forward looking radar measurement.

17. The system of claim 1, wherein said feedback response is a haptic warning.

18. The system of claim 1, wherein said feedback response is an automatic reduction in the speed of the vehicle.

19. The system of claim 1, wherein said feedback response is a virtual tow.

20. The system of claim 1, wherein said feedback response comprises an audio warning and a chance in speed.

21. The system of claim 20, wherein said feedback response further comprises a haptic warning.

22. The system of claim 1, wherein said feedback response comprises a plurality of warnings of varying severity.

23. The system of claim 1, wherein said feedback response is a following-too-close warning.

24. The system of claim 1, wherein said threat analysis subsystem includes a headway maintenance mode.

25. The system of claim 1, wherein said threat analysis subsystem includes a speed maintenance mode.

26. The system of claim 1, wherein said feedback subsystem is capable of being disabled by a driver interface in the vehicle.

27. The system of claim 1, wherein said sensor subsystem generates an attentiveness level and wherein said threat assessment subsystem generates said threat assessment with said attentiveness level.

28. The system of claim 1, wherein said sensor subsystem generates an impairment level and wherein said threat assessment subsystem generates said threat assessment with said impairment level.

29. The system of claim 1, wherein said sensor subsystem includes a path-prediction module and a scene detector module.

30. The system of claim 1, wherein said sensor subsystem includes a stationary-object processing module.

31. The system of claim 1, further comprising a nuisance rate and a predetermined nuisance rate goal, wherein said predetermined nuisance rate goal is greater than said nuisance rate.

32. The system of claim 1, wherein said selected internal attribute comprises a user-based reaction time.

33. The system of claim 1, wherein said threat analysis subsystem includes a roadway environment attribute, and wherein said threat analysis subsystem generates said threat assessment with said roadway environment attribute.

34. The system of claim 33, wherein said roadway environment attribute is a change in grade, and wherein said change in grade does not cause a false alarm.

35. The system of claim 33, wherein said roadway environment attribute is a road surface condition, and wherein said road surface condition does not cause a false alarm.

36. The system of claim 33, wherein said roadway environment attribute is a surface type, and wherein said surface type does not cause a false alarm.

57. The system of claim 1, wherein said internal attribute is not derived from said sensor data.

58. The system of claim 1, further comprising a plurality of internal attributes, wherein said plurality of internal attributes includes said at least one user-based attribute and at least one vehicle-based attribute.

59. The system of claim 1, wherein said threat assessment is a collision assessment.

37. A collision avoidance system for a vehicle, comprising:

a sensor module for capturing sensor data;

an object detection module for identifying an object with said sensor data;

an object tracker module for generating tracking information relating to said object;

means for storing at least one user-based attribute associated with a user of the vehicle; and

a threat detector module for generating a threat assessment from said tracking information and said at least one user-based attribute.

38. The system of claim 37, wherein said user-based internal attribute is a braking level preference threshold, and wherein said threat detector module compares said braking level preference threshold to a braking level required to avoid a collision, before generating said threat assessment.

39. The system of claim 38, wherein said breaking level preference threshold is a selection-based attribute.

40. The system of claim 38, wherein said breaking level preference threshold is a history-based attribute.

41. The system of claim 37, wherein said user-based attribute is a response time threshold, and wherein said threat detector module compares said response time threshold to a response time require to avoid a collision, before generating said threat assessment.

42. The system of claim 41, wherein said response time threshold is a history-based attribute.

43. The system of claim 37, further comprising a plurality of modes including a headway maintenance mode and a speed maintenance mode, wherein said threat assessment depends on a mode in said plurality of modes.

44. The system of claim 37, further comprising a heuristic for generating said threat assessment.

45. The system of claim 44, wherein said heuristic is an azimuth angle scene detection heuristic.

46. The system of claim 44, wherein said heuristic is a yaw rate scene detection heuristic.

47. The system of claim 44, wherein said heuristic is a radius of curvature scene detection heuristic.

48. A method of building automotive collision avoidance systems, comprising the steps of:

setting a user-specific brake level preference threshold for use with the automotive collision avoidance system; and

programming a computer for use in the automotive collision avoidance system to initiate feedback when avoidance of a collision would require a brake level greater than the user-specific brake preference threshold.

49. The method of claim 48, wherein setting the user-specific brake level preference threshold comprises applying a statistical analysis to normative data.

50. The method of claim 48, wherein the user-specific brake level preference is set with a user-based attribute.

51. The method of claim 48, wherein the user-specific brake level preference is determined by a selection-based attribute.

52. The method of claim 48, wherein the user-specific brake level preference is determined by a history-based attribute.

53. The method of claim 48, wherein initiating feedback includes generating a haptic warning.

54. The method of claim 48, wherein initiating feedback includes automatically reducing the speed of the vehicle.

56. The method of claim 48, wherein the user-specific response time threshold is a history-based attribute.

55. A method of building automotive collision avoidance systems, comprising the steps of:

setting a user-specific response time threshold for use with the automotive collision avoidance system; and

programming a computer in the automotive collision avoidance system to initiate feedback when avoidance of a collision would require a response time greater than the user-specific response time threshold.

60. A collision avoidance system for a vehicle, comprising:

a sensor subsystem, wherein said sensor subsystem provides for the capture of sensor data;

a threat analysis subsystem, wherein said threat analysis subsystem provides for generating a threat assessment from said sensor data and at least one internal attribute, said at least one internal attribute being history based; and

a feedback subsystem, wherein said feedback subsystem provides for generating a feedback response from said threat assessment.

61. The system of claim 60, wherein said history-based internal attribute comprises a braking level preference attribute determined from data representative of a braking history.

62. The system of claim 60, wherein said history-based internal attribute comprises a user-based reaction time determined from data representative of a reaction time history.

63. The system of claim 60, wherein said history-based internal attribute comprises a user condition determined from data representative of historical user driving actions.