Learning Lanes From Radar Data

• US 20160171893A1
• Filed: 12/16/2014
• Published: 06/16/2016
• Est. Priority Date: 12/16/2014
• Status: Active Grant

• Current Assignee: HERE Global B.V. (HERE Holding Corporation)
• Original Assignee: HERE Global B.V. (HERE Holding Corporation)
• Inventors: Chen, Xin, Ma, Di, Ma, Xiang, Ostrovskiy, Roman, Zhukov, Vladimir, Zou, Xiaotao
• Granted Patent: US 9,721,471 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 15/931 of land vehicles
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G01S 2013/932 using own vehicle data, e.g. ground speed, steering wheel direction
• CPC Class Codes: G01S 2013/9322 using additional data, e.g. driver condition, road state or weather data
• CPC Class Codes: G01S 2013/9323 Alternative operation using light waves
• CPC Class Codes: G01S 2013/9324 Alternative operation using ultrasonic waves
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

Systems, methods, and apparatuses are disclosed for determining lane information of a roadway segment from vehicle probe data. Probe data is received from radar sensors of vehicles at a road segment, where the probe data includes an identification of static objects and dynamic objects in proximity to the respective vehicles at the road segment, and geographic locations of the static objects and the dynamic objects. A reference point, such as a road boundary, at the road segment is determined from the identified static objects. Lateral distances between the identified dynamic objects and the reference point are calculated. A number of lanes at the road segment are ascertained from a distribution of the calculated distances of the identified dynamic objects from the reference point.

Claims

1. A method comprising:

receiving probe data from radar sensors of vehicles at a road segment, the probe data comprising (1) an identification of static objects and dynamic objects in proximity to the respective vehicles at the road segment and (2) geographic locations of the static objects and the dynamic objects;

determining, using a processor, a reference point at the road segment from the identified static objects;

calculating lateral distances between the identified dynamic objects and the reference point, the lateral distance measured along an axis perpendicular to lanes of the road segment; and

ascertaining a number of lanes at the road segment from a distribution of the calculated distances of the identified dynamic objects from the reference point.

2. The method of claim 1, wherein the distribution of the calculated distances of the identified dynamic objects is arranged in a histogram, and the number of lanes at the road segment are ascertained based on the number of peaks in the histogram.

3. The method of claim 2, further comprising:

defining each lane of the ascertained number of lanes at the road segment with a respective lane number; and

identifying the lane number of a vehicle based on a shortest lateral distance of the vehicle to a peak in the histogram.

4. The method of claim 1, further comprising:

verifying the number of lanes at the road segment using ground truth data.

5. The method of claim 1, further comprising:

updating a map database with the ascertained number of lanes at the road segment.

6. The method of claim 1, further comprising:

reporting the ascertained number of lanes at the road segment to a vehicle navigation device over a connected network.

7. The method of claim 1, wherein the reference point is a road boundary.

8. The method of claim 1, wherein the dynamic objects identified are traveling in a same direction as the respective vehicles.

9. A method comprising:

receiving probe data from radar sensors of a plurality of vehicles at a road segment, the probe data comprising (1) an identification of static objects in proximity to the respective vehicles at the road segment and (2) geographic locations of the static objects;

determining, using a processor, a first road boundary and a second, opposite road boundary at the road segment from the identified static objects;

computing a width of the road segment from the identified first and second road boundaries; and

estimating a number of lanes at the road segment by dividing the computed width of the road segment by a predetermined average lane width.

10. The method of claim 9, wherein the first and second road boundaries are determined from pluralities of static objects grouped along opposite edges of the road segment.

11. The method of claim 10, wherein the static objects comprise one or more of road signs, road curbs, barriers, or guard rails.

12. The method of claim 9, wherein the predetermined average lane width is between 3 meters and 4 meters.

13. The method of claim 9, wherein the width of the road segment is computed by (1) determining, for each vehicle of the plurality of vehicles, a first distance between the first road boundary and the respective vehicle and a second distance between the second road boundary and the respective vehicle, (2) combining, for each vehicle, the first distance and second distance, and (3) averaging the combined distances for the plurality of vehicles.

14. 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 at least perform;

receive probe data from radar sensors of vehicles at a road segment, the probe data comprising (1) an identification of static objects and dynamic objects in proximity to the respective vehicles at the road segment and (2) geographic locations of the static objects and the dynamic objects;

determine a reference point at the road segment from the static objects;

calculate lateral distances of the identified dynamic objects from the reference point, the lateral distance measured along an axis perpendicular to lanes of the road segment; and

ascertain a number of lanes at the road segment from a distribution of the calculated distances of the identified dynamic objects from the reference point.

15. The apparatus of claim 14, wherein the reference point is a road boundary.

16. The apparatus of claim 14, wherein the distribution of the calculated distances of the identified dynamic objects is arranged in a histogram, and the number of lanes at the road segment are ascertained based on the number of peaks in the histogram.

17. The apparatus of claim 14, wherein the at least one memory and the computer program code are configured to cause the apparatus to further perform:

define each lane of the ascertained number of lanes at the road segment with a respective lane number; and

identify the lane number of a vehicle based on a shortest distance of the vehicle to a peak in the histogram.

18. The apparatus of claim 14, wherein the at least one memory and the computer program code are configured to cause the apparatus to further perform:

update a map database with the ascertained number of lanes at the road segment.

19. The apparatus of claim 14, wherein the at least one memory and the computer program code are configured to cause the apparatus to further perform:

report the ascertained number of lanes at the road segment to a vehicle navigation device over a connected network.

20. 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 at least perform;

receive probe data from radar sensors of a plurality of vehicles at a road segment, the probe data comprising (1) an identification of static objects in proximity to the respective vehicles at the road segment and (2) geographic locations of the static objects;

determine a first road boundary and a second, opposite road boundary at the road segment from the identified static objects;

compute a width of the road segment from the identified first and second road boundaries; and

estimate a number of lanes at the road segment by dividing the computed width of the road segment by a predetermined average lane width.

21. The apparatus of claim 20, wherein the predetermined average lane width is between 3 meters and 4 meters.

22. The apparatus of claim 20, wherein the width of the road segment is computed by (1) determining, for each vehicle of the plurality of vehicles, a first distance between the first road boundary and the respective vehicle and a second distance between the second road boundary and the respective vehicle, (2) combining, for each vehicle, the first distance and second distance, and (3) averaging the combined distances for the plurality of vehicles.