Learning lanes from radar sensors

• US 10,002,537 B2
• Filed: 06/21/2017
• Issued: 06/19/2018
• 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
• Primary Examiner(s): Oh, Harry Y
• Application Number:
  US15/628,985
• Publication Number:
  US 20170287337A1
• Time in Patent Office: 363 Days
• Field of Search: 701300
• 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 a plurality of vehicles at a road segment, the probe data comprising an identification of static objects in proximity to the respective vehicles at the road segment and geographic locations of the static objects;

determining, using a processor, a first road boundary and a second road boundary at the road segment from the identified static objects received from the plurality of vehicles, the second road boundary being an opposite road boundary from the first road boundary;

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

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, combining, for each vehicle of the plurality of vehicles, the first distance and second distance to provide a determined width for each respective vehicle; and

adding together the determined widths for each respective vehicle of the plurality of vehicles and dividing by a total number of vehicles;

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

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

2. The method of claim 1, wherein the first and second road boundaries are determined from pluralities of static objects grouped along opposite edges of the road segment.

3. The method of claim 2, wherein the static objects comprise one or more of road signs, road curbs, barriers, or guard rails.

4. The method of claim 1, wherein the predetermined average lane width is between 3 meters and 4 meters.

5. The method of claim 1, further comprising:

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

6. A method comprising:

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

determining, using a processor, a first road boundary and a second road boundary at the road segment from the identified static objects received from the plurality of vehicles, the second road boundary being an opposite road boundary from the first road boundary;

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

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, combining, for each vehicle of the plurality of vehicles, the first distance and second distance to provide a determined width for each respective vehicle; and

adding together the determined widths for each respective vehicle of the plurality of vehicles and dividing by a total number of vehicles;

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

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

7. The method of claim 6, wherein the first and second road boundaries are determined from pluralities of static objects grouped along opposite edges of the road segment.

8. The method of claim 7, wherein the static objects comprise one or more of road signs, road curbs, barriers, or guard rails.

9. The method of claim 6, wherein the predetermined average lane width is between 3 meters and 4 meters.

10. The method of claim 6, further comprising:

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

11. 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;

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

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

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

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, combining, for each vehicle of the plurality of vehicles, the first distance and second distance to provide a determined width for each respective vehicle; and

adding together the determined widths for each respective vehicle of the plurality of vehicles and dividing by a total number of vehicles;

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

update a map database with the estimated number of lanes at the road segment, or report the estimated number of lanes at the road segment to a vehicle navigation device over a connected network.

12. The apparatus of claim 11, wherein the predetermined average lane width is between 3 meters and 4 meters.

13. The apparatus of claim 11, wherein the first and second road boundaries are determined from pluralities of static objects grouped along opposite edges of the road segment.

14. The apparatus of claim 13, wherein the static objects comprise one or more of road signs, road curbs, barriers, or guard rails.

15. The apparatus of claim 11, wherein the at least one memory and the computer program code are configured to further cause the apparatus to

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