Lane Level Traffic

• US 20160004915A1
• Filed: 07/07/2014
• Published: 01/07/2016
• Est. Priority Date: 07/07/2014
• Status: Active Grant

• Current Assignee: HERE Global B.V. (Nokia Corporation)
• Original Assignee: HERE Global B.V. (Nokia Corporation)
• Inventors: Chen, Xin, Ma, Xiang, Ostrovskiy, Roman, Zhao, Terence
• Granted Patent: US 9,747,505 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 50/30 Transportation; Communications
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G06T 17/05 Geographic models
• CPC Class Codes: G06V 10/74 Image or video pattern matching; Proximity measures in feature spaces
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/647 by matching two-dimensional images to three-dimensional objects
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions

Abstract

Lane level traffic levels are determined based on traffic camera images. A controller aligns a three-dimensional map with a traffic camera view, and identifies multiple lanes in the traffic camera view based on lane delineations of the three-dimensional map. The controller calculates a traffic parameter based on the multiple lanes in image frames from the traffic camera view and provides a traffic graphic based on the traffic parameter.

Claims

1. A method comprising:

aligning a three-dimensional map with a traffic camera view;

identifying a plurality of lanes in the traffic camera view based on lane delineations of the three-dimensional map;

calculating a traffic parameter based on the plurality of lanes in image frames from the traffic camera view; and

providing a traffic graphic based on the traffic parameter.

2. The method of claim 1, further comprising:

adding the traffic parameter to the three-dimensional map.

3. The method of claim 1, wherein aligning the three-dimensional map with the traffic camera view comprises:

calculating a focal distance of a camera for the traffic camera view;

calculating a distance to the plurality of lanes from the three-dimensional map; and

determining a correlation between the focal distance and the distance to the plurality of lanes to align the three-dimensional map with the traffic camera view.

4. The method of claim 3, wherein the correlation is based on a predetermined dimension of an object in the traffic camera view.

5. The method of claim 4, wherein the predetermined dimension of the object is a length of a car or a width of a path.

6. The method of claim 1, further comprising:

tracking vehicles in plurality of lanes from a first video frame to a subsequent video frame, wherein the traffic parameter is based on a difference in the positions of the vehicles from the first video frame to the subsequent video frame.

7. The method of claim 1, wherein aligning the three-dimensional map with the traffic camera view comprises:

identifying a position of a camera for the traffic camera view;

identifying a viewable distance range of the camera;

calculating a first distance to a first lane of the plurality of lanes; and

determining a first image location in the traffic camera view for the first lane based on the first distance and the viewable distance range to the position of the camera.

8. The method of claim 7, further comprising:

calculating a second distance to a second lane of the plurality of lanes; and

determining a second image location in the traffic camera view for the second lane based on the second distance and the viewable distance range to the position of the camera.

9. The method of claim 1, wherein the traffic parameter is traffic speed, traffic flow, or traffic density.

10. The method of claim 1, wherein individual vehicles in the traffic camera view are counted on a lane-by-lane basis in the plurality of lanes.

11. The method of claim 1, wherein the plurality of lanes travel in a same direction and the traffic parameter includes data for each of the plurality of lanes in the same 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 at least perform;

align a traffic camera view with map data, wherein the map data includes locations of multiple lanes of a road;

identify multiple lanes in image frames of the traffic camera view based on the locations of multiple lanes in the map data;

track vehicles in the traffic camera view according to the multiple lanes in the image frames; and

calculate a traffic parameter based on vehicles in the image frames from the traffic camera view.

13. The apparatus of claim 12, wherein the traffic parameter is added to a user interface including the map data.

14. The apparatus of claim 12, wherein the traffic camera view is aligned with map data based on a focal distance of a camera and relative distances of the multiple lanes.

15. The apparatus of claim 12, 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:

modifying an illustration of the road based on the traffic parameter.

16. The apparatus of claim 12, wherein the traffic camera view is aligned with map data based on a predetermined dimension of an object in the traffic camera view.

17. The apparatus of claim 12, wherein the traffic parameter is traffic speed, traffic flow, or traffic density.

18. The apparatus of claim 12, wherein the vehicles are counted in the image frames using background subtraction.

19. A non-transitory computer readable medium including instructions that when executed on a computer are operable to:

determine location data indicative of a geographical location of a mobile device, wherein the geographic location corresponds to a lane of a multi-lane road;

send the location data to a traffic server;

receive a traffic parameter from the traffic server, wherein the traffic parameter is based on an analysis of image frames of a video stream including the multi-lane road; and

display the traffic parameter in association with the lane of the multi-lane road.

20. The non-transitory computer readable medium of claim 19, wherein the traffic parameter includes traffic conditions in a second lane of the multi-lane road.