Determining Travel Path Features Based on Retroreflectivity

• US 20140180590A1
• Filed: 02/27/2014
• Published: 06/26/2014
• Est. Priority Date: 02/20/2009
• Status: Active Grant

• Current Assignee: HERE Global B.V. (HERE Holding Corporation)
• Original Assignee: Navteq B.V. (HERE Holding Corporation)
• Inventors: Stroila, Matei Nicolai, Chen, Xin, Lu, Victor, Kohlmeyer, Bradley Dean, Moghaddam, Mahsa Kamali
• Granted Patent: US 9,476,705 B2
• Time in Patent Office: Days
• US Class Current: 702/5
• CPC Class Codes: G01C 3/06 Use of electric means to obtain final indication
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G09B 29/008 Touring maps or guides to public transport networks

Abstract

Systems, devices, features, and methods for determining geographic features corresponding to a travel path to develop a map database, such as a navigation database, are disclosed. For example, one method comprises emitting light from a light source, such as a LIDAR device, while on the travel path. Returning light is received based on the emitted light. The returning light is used to generate data points representing an area about the travel path. The data points are filtered as a function of a return intensity value to identify a feature associated with the travel path, in which the feature is treated with a retroreflective substance.

Claims

1. A method comprising:

receiving reflected light data points collected at a light collection device;

comparing, by a processor, the reflected light data points to at least one intensity threshold;

identifying a subset of the reflected light data points that exceed the at least one intensity threshold; and

identifying a predetermined shape data model that corresponds to the subset of the reflected light data points.

2. The method of claim 1, further comprising:

determining whether energy of the reflected lighted data points is substantially constant through a scan of the light collection device, wherein the subset of the reflected light data points are substantially constant and exceed the at least one intensity threshold.

3. The method of claim 1, wherein the predetermined shape model is selected from a group of lane markings including at least one of turn markings, side lane markings, restriction markings, or curb markings.

4. The method of claim 1, wherein the predetermined shape model includes a lane marking size.

5. The method of claim 1, wherein the predetermined shape model includes a lane marking color.

6. The method of claim 1, wherein the light collection device is a light detection and ranging device.

7. The method of claim 1, wherein the light collection device is a near infrared camera.

8. The method of claim 1, wherein the at least one intensity threshold comprises a global threshold and a local threshold.

9. The method of claim 1, further comprising:

applying a growing algorithm to the subset of the reflected light data points to eliminate gaps.

10. The method of claim 1, further comprising:

applying a grid of cells to the reflected light data points; and

determining a binary label for each of the cells of the grid.

11. The method of claim 1, further comprising:

scanning the light collection device in a first direction;

identifying an initial abrupt change in the reflected light data points in the first direction;

scanning the light collection device in a second direction;

identifying a second abrupt change in the reflected light data points in the second direction; and

discarding points before the initial abrupt change in the first direction and points before the second abrupt change in the second direction.

12. An apparatus comprising:

at least one processor; and

at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following;

compare reflected light data points to at least one intensity threshold;

identify a subset of the reflected light data points that exceed the at least one intensity threshold;

identify a predetermined shape data model that corresponds to the subset of the reflected light data points; and

store, in a map database, the predetermined shape data model that corresponds to the subset of the reflected light data points at a travel path associated with the reflected light data points.

13. The apparatus of claim 12, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

calculate an average ground elevation of the travel path; and

discard reflected light points more than a predetermined distance from the average ground elevation.

14. The apparatus of claim 13, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

identify borders of the travel path based on the average ground elevation.

15. The apparatus of claim 12, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

determine whether energy of the reflected lighted data points is substantially constant through a scan of the light collection device, wherein the subset of the reflected light data points are substantially constant and exceed the at least one intensity threshold.

16. The apparatus of claim 12, wherein the predetermined shape model is selected from a group of lane markings including turn markings, side lane markings, and restriction markings.

17. The apparatus of claim 12, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

scan the light collection device in a first direction;

identify an initial abrupt change in the reflected light data points in the first direction;

scan the light collection device in a second direction;

identify a second abrupt change in the reflected light data points in the second direction; and

discard points before the initial abrupt change in the first direction and points before the second abrupt change in the second direction.

18. The apparatus of claim 17, wherein the abrupt change deviates from an average value by a predetermined number of standard deviations.

19. A method comprising:

receiving position data for a device;

accessing a map database based on the position data; and

receiving a travel path image including a predetermined shape data model for a lane marking that corresponds to a subset of reflected data points identified from a comparison of an intensity threshold and reflected light data points collected by a light collection device.

20. The method of claim 19, wherein the predetermined shape model is selected from a group of lane markings including turn markings, side lane markings, and restriction markings.