Probabilistic target selection and threat assessment method and application to intersection collision alert system

Patent metadata

Field	Value
Publication number	US-9250324-B2
Application number	US-201313901123-A
Country	US
Kind code	B2
Filing date	May 23, 2013
Priority date	May 23, 2013
Publication date	Feb 2, 2016
Grant date	Feb 2, 2016

Abstract

A system and method for providing target selection and threat assessment for vehicle collision avoidance purposes that employ probability analysis of radar scan returns. The system determines a travel path of a host vehicle and provides a radar signal transmitted from a sensor on the host vehicle. The system receives multiple scan return points from detected objects, processes the scan return points to generate a distribution signal defining a contour of each detected object, and processes the scan return points to provide a position, a translation velocity and an angular velocity of each detected object. The system selects the objects that may enter the travel path of the host vehicle, and makes a threat assessment of those objects by comparing a number of scan return points that indicate that the object may enter the travel path to the number of the scan points that are received for that object.

First claim

What is claimed is:

1. A method for providing target threat assessment in a collision avoidance system on a host vehicle, said method comprising:
determining a travel path of the host vehicle using motion dynamics of the host vehicle;
transmitting a scan signal from at least one sensor on the host vehicle;
receiving multiple scan return points at the host vehicle from one or more detected objects that reflect the scan signal;
generating a distribution signal defining a contour of each detected object using the scan signal;
calculating a position, a translation velocity and an angular velocity of each detected object using the scan return points;
selecting the objects that may be in or enter the travel path of the host vehicle using the distribution signal, position, translation velocity and angular velocity of each object; and
determining a threat assessment of those objects that are in or may enter the travel path of the host vehicle by comparing a number of scan return points that indicate that the object is in or may enter the travel path to the number of scan points that are received for that object.

2. The method according to claim 1 wherein generating a distribution signal of each object includes updating the distribution signal at subsequent sample times using a Gaussian mixture model.

3. The method according to claim 1 wherein selecting the objects that may be in or enter the travel path of the host vehicle includes reducing the complexity of the distribution signal to a reduced number of scan points.

4. The method according to claim 3 wherein selecting the objects that may be in or enter the travel path of the host vehicle includes using a probabilistic technique.

5. The method according to claim 4 wherein the probabilistic technique includes representing each reduced number of points as a Gaussian distribution.

6. The method according to claim 4 wherein the probabilistic technique includes using a Monte Carlo technique that separates the distribution signal into a plurality of particles.

7. The method according to claim 1 further comprising performing sensor visibility analysis to determine if one or more of the sensors is being blocked in a particular direction, wherein determining a threat assessment includes determining a collision threat if one of the sensors is blocked.

8. The method according to claim 7 wherein performing sensor visibility analysis includes performing the sensor visibility analysis if it is determined that the host vehicle is at or approaching an intersection.

9. The method according to claim 8 wherein performing sensor visibility analysis includes determining a speed of the host vehicle.

10. The method according to claim 1 wherein determining a threat assessment includes determining a time to collision for one or more of the scan return points.

11. The method according to claim 10 wherein determining a threat assessment includes identifying the number of time to collision values are less than a predetermined threshold.

12. The method according to claim 1 wherein determining a threat assessment includes providing a warning of a potential collision and providing automatic braking for an imminent collision.

13. The method according to claim 1 wherein the at least one sensor is a radar sensor.

14. A method for providing target threat assessment in a collision avoidance system on a host vehicle, said method comprising:
determining a travel path of the host vehicle using motion dynamics of the host vehicle;
transmitting a radar signal from at least one radar sensor on the host vehicle;
receiving multiple scan return points at the host vehicle from one or more detected objects that reflect the radar signal;
generating a distribution signal defining a contour of each detected object using the radar signal, wherein generating a distribution signal of each object includes updating the distribution signal at subsequent sample times using a Gaussian mixture model;
calculating a position, a translation velocity and an angular velocity of each detected object using the scan return points;
selecting the objects that may be in or enter the travel path of the host vehicle using the distribution signal, position, translation velocity and angular velocity of each object, wherein selecting the objects that may be in or enter the travel path of the host vehicle includes using a probabilistic technique; and
determining a threat assessment of those objects that are in or may enter the travel path of the host vehicle by comparing a number of scan return points that indicate that the object is in or may enter the travel path to the number of scan points that are received for that object, wherein determining a threat assessment includes determining a time to collision for one or more of the scan return points.

15. The method according to claim 14 wherein selecting the objects that may be in or enter the travel path of the host vehicle includes reducing the complexity of the distribution signal to a reduced number of scan points.

16. The method according to claim 15 wherein the probabilistic technique includes representing each reduced number of points as a Gaussian distribution.

17. The method according to claim 14 wherein the probabilistic technique includes using a Monte Carlo technique that separates the distribution signal into a plurality of particles.

18. The method according to claim 14 further comprising performing sensor visibility analysis to determine if one or more of the sensors is being blocked in a particular direction, wherein determining a threat assessment includes determining a collision threat if one of the sensors is blocked.

19. The method according to claim 18 wherein performing sensor visibility analysis includes performing the sensor visibility analysis if it is determined that the host vehicle is at or approaching an intersection.

20. The method according to claim 19 wherein performing sensor visibility analysis includes determining a speed of the host vehicle.

Assignees

• Gm Global Tech Operations Inc

Inventors

• Zeng Shuqing
• Zhang Wende
• Shields Mark E

Classifications

• G01S13/87 Primary

  Combinations of radar systems, e.g. primary radar and secondary radar · CPC title

• G01S7/40

  Means for monitoring or calibrating · CPC title

• G01S7/41

  using analysis of echo signal for target characterisation; Target signature; Target cross-section · CPC title

• G01S13/931 Primary

  of land vehicles · CPC title

• G01S2013/93271

  in the front of the vehicles · CPC title