System and method for lane boundary estimation and host vehicle position and orientation

• US 20140358321A1
• Filed: 06/01/2013
• Published: 12/04/2014
• Est. Priority Date: 06/01/2013
• Status: Active Grant

• Current Assignee: Harman International Industries Incorporated (Samsung Electronics Co. Ltd.)
• Original Assignee: Faroog Ibrahim
• Inventors: Ibrahim, Faroog
• Granted Patent: US 9,261,601 B2
• Time in Patent Office: Days
• US Class Current: 701/1
• CPC Class Codes: G01S 19/14 specially adapted for specific applications
• CPC Class Codes: G01S 19/39 the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO

Abstract

Lane Boundary Estimation and Host Vehicle Position and Orientation, within the host lane estimation, using V2V (vehicle to vehicle) system, are discussed here. Lane boundary detection and tracking is essential for many active safety/ADAS application. The lane boundary position enables the tracking of the host vehicle position and orientation inside the lane. It also enables classifying in-lane, adjacent lanes, and other lanes vehicles. These two functionalities (lane boundary estimation and vehicle lane classifications) enable active safety applications (such as LDW, FCW, ACC, or BSD). It also enables the lateral control of the vehicle for lane keeping assist system, or for full lateral control for automated vehicle (automated for one or multiple lane changes).

Claims

1. A method for lane boundary estimation and host vehicle position and orientation, said method comprising:

a global positioning system transmitting position of one or more vehicles to a path history module;

said path history module generating history of coordinates of said one or more vehicles;

a lane boundary estimation module generating statistical distribution curves representing said history of coordinates of said one or more vehicles in each of two coordinates in two-dimensional plane;

a clustering module generating clusters based on said statistical distribution curves representing said history of coordinates of said one or more vehicles;

a lane determination module setting width and position of each lane in highway based on said clusters; and

a processor combining results of said width and said position of each lane in said highway, to get an overall width and position of all lanes in said highway.

2. The method as recited in claim 1, said method comprising:

averaging results of said width of each lane in said highway.

3. The method as recited in claim 1, said method comprising:

averaging results of said position of each lane in said highway.

4. The method as recited in claim 1, said method comprising:

weighted-averaging results of said width of each lane in said highway.

5. The method as recited in claim 1, said method comprising:

weighted-averaging results of said position of each lane in said highway.

6. The method as recited in claim 1, said method comprising:

centering said clusters based on said statistical distribution curves.

7. The method as recited in claim 1, said method comprising:

determining virtual boundary line.

8. The method as recited in claim 1, said method comprising:

recording and storing said history of coordinates of said one or more vehicles.

9. The method as recited in claim 1, said method comprising:

generating said clusters based on a single vehicle.

10. The method as recited in claim 1, said method comprising:

generating said clusters based on multiple vehicles.

11. The method as recited in claim 1, said method comprising:

generating said clusters based on a single vehicle in a single lane.

12. The method as recited in claim 1, said method comprising:

generating said clusters based on multiple vehicles in a single lane.

13. The method as recited in claim 1, said method comprising:

generating said clusters based on a single vehicle in multiple lanes.

14. The method as recited in claim 1, said method comprising:

generating said clusters based on multiple vehicles in multiple lanes.

15. The method as recited in claim 1, said method comprising:

giving warning for lane change.

16. The method as recited in claim 1, said method comprising:

giving warning for lane change with sound.

17. The method as recited in claim 1, said method comprising:

giving warning for lane change with light.

18. The method as recited in claim 1, said method comprising:

using a road map.

19. The method as recited in claim 1, said method comprising:

measuring distance between said clusters.

20. The method as recited in claim 1, said method comprising:

measuring distance between centers of said clusters.

21. The method as recited in claim 1, said method comprising:

said lane determination module using map attributes.

22. The method as recited in claim 1, said method comprising:

said lane determination module using shape points.

23. The method as recited in claim 1, said method comprising:

said lane determination module using number of lanes.

24. The method as recited in claim 1, said method comprising:

said lane determination module using road structure.

25. The method as recited in claim 1, said method comprising:

said lane determination module using yaw rate.

26. The method as recited in claim 1, said method comprising:

said lane determination module using heading or direction.

27. The method as recited in claim 1, said method comprising:

matching vehicle position to longitudinal grid of road representation.

28. The method as recited in claim 1, said method comprising:

determining a host vehicle'"'"'s position and orientation within a host lane.

29. The method as recited in claim 1, said method comprising:

determining a curvature using Clothoid model.