Collision detection system with a plausibiity module

• US 9,187,091 B2
• Filed: 08/29/2012
• Issued: 11/17/2015
• Est. Priority Date: 07/30/2012
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Mills, Aaron L.
• Primary Examiner(s): Mawari, Redhwan K
• Assistant Examiner(s): Torchinsky, Edward
• Application Number:
  US13/598,166
• Publication Number:
  US 20140032093A1
• Time in Patent Office: 1,175 Days
• US Class Current: 1/1
• CPC Class Codes: B60R 21/00 Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks safety belts or body harnesses in vehicles B60R22/00; devices, apparatus or methods for life-saving in general A62B; safety devices for propulsion unit control specially adapted for, or arranged in, vehicles B60K28/00; seats constructed to protect the occupant from the effect of abnormal g-forces, e.g. crash or safety seats, B60N2/42; energy-absorbing arrangements for hand wheels for steering vehicles B62D1/11; energy-absorbing arrangements for vehicle steering columns B62D1/19; harnessing in aircraft B64D25/00
• CPC Class Codes: B60W 10/18 including control of braking systems
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 2420/40 Photo, light or radio wave sensitive means, e.g. infrared sensors
• CPC Class Codes: B60W 2420/408 Radar; Laser, e.g. lidar
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2520/14 Yaw
• CPC Class Codes: B60W 2554/4041 Position
• CPC Class Codes: B60W 2554/801 Lateral distance
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• 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 30/095 Predicting travel path or likelihood of collision
• CPC Class Codes: B60W 40/10 related to vehicle motion
• CPC Class Codes: B60W 40/107 Longitudinal acceleration

Abstract

A collision detection system for a vehicle includes a sensor and a camera. The sensor measures a first data set of an object relative to the vehicle. The camera measures a second data set of the object relative to the vehicle and separately measures an image-based time-to-collision with the object based on scalable differences of captured images. A fusion module matches data from the sensor and the camera and estimates a collision threat based on the matched data. A plausibility module generates a signal if the measured image-based time-to-collision is less than a calculated steering-based time-to-collision and a braking-based time-to-collision with the object. A countermeasure module actuates a countermeasure device, such as an autonomous braking system, if the collision threat exceeds an actuation threshold and the signal from the plausibility module is received, thereby statistically reducing the rate of false actuations of the countermeasure device.

Claims

1. A collision detection system for a host vehicle, comprising:

a sensor for detecting an object in a field of view and measuring a first set of target data based on a position of the object relative to the host vehicle;

a camera for capturing a plurality of images from the field of view and processing the plurality of images to measure a second set of target data, including object classification and confidence values and an azimuth angle and angle rate of the object relative to the host vehicle, and to measure an image-based time-to-collision (TTC_IMAGE) of the host vehicle with the object based on scalable differences of the plurality of images;

a fusion module for determining a matched set of target data based on optimized values of the first and second sets of target data received from the sensor and the camera, wherein the fusion module estimates a threat of collision of the host vehicle with the object based on the matched set of target data;

a plausibility module for calculating a steering-based time-to-collision (TTC_STEERING) and a braking-based time-to-collision (TTC_BRAKING) of the host vehicle with the object based on the second set of target data received from the camera and an additional set of data received from a vehicle dynamics detector on the host vehicle, wherein the plausibility module generates an actuation signal if the TTC_IMAGE is less than the TTC_STEERING and the TTC_BRAKING; and

a countermeasure module for actuating a countermeasure device if the threat of collision received from the fusion module exceeds an actuation threshold and the actuation signal from the plausibility module is generated and received, thereby statistically increasing reliability of the collision detection system.

2. The collision detection system of claim 1, wherein the first set of target data measured by the sensor includes a first range and a first range rate of the object relative to the host vehicle, a first angle and a first angle rate of the object relative to the host vehicle, and a relative movement determination of the object, and wherein the sensor comprises a radar system.

3. The collision detection system of claim 1, wherein the camera includes an imager for capturing the plurality of images from the field of view based on light waves received from the field of view at known time intervals between times when images of the plurality of images are captured.

4. The collision detection system of claim 1, wherein the second set of target data measured by the camera includes a second range and second range rate of the object relative to the host vehicle, a second azimuth angle and second azimuth angle rate of the object relative to the host vehicle, a width measurement of the object, and an object classification of the object.

5. The collision detection system of claim 4, wherein the vehicle dynamics detector includes a yaw-rate sensor and a speed sensor on the host vehicle, and wherein the additional set of data received from the vehicle dynamics detector includes a yaw rate of the host vehicle measured by the yaw-rate sensor and a velocity of the host vehicle measured by the speed sensor.

6. The collision detection system of claim 5, wherein the TTC_STEERING is calculated as a function of the second range and the second range rate, the second azimuth angle and the second azimuth angle rate, the object classification, the yaw rate, and the velocity, and wherein the plausibility module estimates whether the object is in a path of travel of the host vehicle.

7. The collision detection system of claim 5, wherein the TTC_BRAKING is calculated as a function of the velocity measured by the speed sensor and a selected constant rate of deceleration of the host vehicle.

8. The collision detection system of claim 1, wherein the countermeasure device comprises an autonomous braking controller for activating a brake system of the host vehicle.

9. A collision detection system for a vehicle, comprising:

a sensor;

a camera;

a fusion module for determining a matched set of target data based on values of a first and second set of data received from the sensor and the camera, wherein the fusion module estimates a threat of collision of the vehicle with an object based on the matched set of target data;

a plausibility module generating a signal if a time-to-collision measured by the camera is less than a steering-based time-to-collision and a braking-based time-to-collision, wherein the steering-based time-to-collision is calculated as a function of a range of the object relative to the vehicle, an azimuth angle of the object relative to the vehicle, a velocity of the vehicle, a lateral acceleration of the vehicle, a yaw-rate of the vehicle, and a width measurement of the object and the vehicle; and

a countermeasure actuating with the signal present and the collision threat exceeding a threshold.

10. The collision detection system of claim 9, wherein the time-to-collision measured by the camera is based on scalable differences of images captured by the camera.

11. The collision detection system of claim 9, wherein the camera includes an imager for capturing a plurality of images from light waves received from a field of view at known time intervals between time when images of the plurality of images are captured, and wherein the camera includes an image processor for processing the plurality of images for measuring the data and the time-to-collision.

12. The collision detection system of claim 9, wherein the matched data used by the fusion module comprises:

a first data set measured by the sensor having a first range and a first range rate of the object relative to the vehicle, a first azimuth angle and a first azimuth angle rate of the object relative to the vehicle, and a relative movement determination of the object; and

a second data set measured by the camera having a second range and a second range rate of the object relative to the host vehicle, a second azimuth angle and a second azimuth angle rate of the object relative to the host vehicle, a width measurement of the object, a classification of the object, and a confidence value of the object, and wherein the fusion module determines the matched data based on optimized values with increased reliability from the first and second sets of target data received from the sensor and the camera.

13. The collision detection system of claim 12, wherein the braking-based time-to-collision is calculated as a function of a measured velocity of the vehicle and an estimated rate of deceleration of the vehicle.

14. The collision detection system of claim 12, wherein the plausibility module estimates whether the object is in a path of travel of the vehicle, and wherein the countermeasure actuates based additionally on whether the object is in the path of travel of the vehicle and whether the confidence value of the object exceeds a confidence threshold.

15. The collision detection system of claim 9, further comprising:

a vehicle dynamics detector having a yaw-rate sensor and a speed sensor, wherein an additional set of data measured by the vehicle dynamics detector includes a yaw rate from the yaw-rate sensor and a velocity of the vehicle from the speed sensor.

16. The collision detection system of claim 9, wherein the countermeasure comprises an autonomous braking controller for activating a brake system of the vehicle, and wherein the sensor comprises a radar system.

17. The collision detection system of claim 9, wherein the camera measures object classification and confidence values and an azimuth angle and angle rate for calculating the steering-based time-to-collision.

18. A method for actuating an autonomous braking controller for a brake system of a host vehicle, the method comprising the steps of:

sensing an object in a field of view by an object detection sensor on the host vehicle;

measuring a first data set of the object with the object detection sensor, including a first range and a first range rate of the object relative to the host vehicle, a first angle and a first angle rate of the object relative to the host vehicle, and a relative movement determination of the object;

capturing a plurality of images based on light waves from the field of view by a camera on the host vehicle at known time intervals between instances when the images of the plurality of images are captured;

processing the plurality of images to measure a second data set of the object, including a second range and a second range rate of the object relative to the host vehicle, a second azimuth angle and a second azimuth angle rate of the object relative to the host vehicle, a width of the object, and an image based time-to-collision (TTC_IMAGE) of the host vehicle with the object based on scalable differences of the object derived from the plurality of images;

measuring an additional data set with a vehicle dynamics detector, including a yaw-rate sensor for measuring a yaw rate of the host vehicle and a speed sensor for measuring a longitudinal velocity of the host vehicle;

processing the first and second data sets, the TTC_IMAGE, and the additional data set;

estimating a threat of collision of the host vehicle with the object based on a combination of the first and second data sets;

determining a steering-based time-to-collision (TTC_STEERING) of the host vehicle with the object as a function of the second data set, the longitudinal velocity of the host vehicle, and the yaw rate of the host vehicle;

determining a braking-based time-to-collision (TTC_BRAKING) of the host vehicle with the object as a function of the longitudinal velocity of the host vehicle and a selected constant rate of deceleration of the host vehicle;

generating an actuation signal if the TTC_IMAGE is less than the TTC_STEERING and the TTC_BRAKING; and

actuating the autonomous braking controller for the brake system of the host vehicle based on the threat of collision exceeding a threshold and the actuation signal being present.

19. The method for actuating an autonomous braking controller of claim 18, wherein the plurality of images are processed to measure object classification and confidence values for determining the threat of collision of the host vehicle with the object.