Object detection and classification for autonomous vehicles

• US 8,874,372 B1
• Filed: 04/05/2012
• Issued: 10/28/2014
• Est. Priority Date: 07/13/2011
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Zhu, Jiajun, Montemerlo, Michael Steven, Urmson, Christopher Paul, Chatham, Andrew
• Primary Examiner(s): Tran, Dalena
• Application Number:
  US13/440,555
• Time in Patent Office: 936 Days
• Field of Search: 701/514, 701/400, 701408-410, 701/422, 701428-430, 701/433, 701/437, 701/468, 701/444, 701/446, 701/458, 701/461, 701/469, 701/523, 340/435, 340/904, 340/988, 340/995.14, 34099517-99519, 340/995.22, 340/995.24, 340/995.25, 348/113, 348/116, 348/118, 348/119, 348/142, 348/135, 348/148, 348/149, 382/103, 382/104, 382/107
• US Class Current: 701/514
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G08G 1/09626 where the origin of the information is within the own vehicle, e.g. a local storage device, digital map
• CPC Class Codes: G08G 1/096725 where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station

Abstract

Aspects of the disclosure relate generally to safe and effective use of autonomous vehicles. More specifically, objects detected in a vehicle'"'"'s surroundings may be detected by the vehicle'"'"'s various sensors and identified based on their relative location in a roadgraph. The roadgraph may include a graph network of information such as roads, lanes, intersections, and the connections between these features. The roadgraph may also include the boundaries of areas, including for example, crosswalks or bicycle lanes. In one example, an object detected in a location corresponding to a crosswalk area of the roadgraph may be identified as a person. In another example, an object detected in a location corresponding to a bicycle area of the roadgraph and identified as a bicycle. By identifying the type of object in this way, an autonomous vehicle may be better prepared to react to or simply avoid the object.

Claims

1. A method comprising:

determining a current location of a vehicle;

accessing map data based on the current location of the vehicle, the map data including information about a roadway including a tagged area of the roadway, wherein the tagged area is associated with an object type;

receiving information about the vehicle'"'"'s surroundings generated by an object detection device;

detecting a moving object and a geographic location of the moving object based on the received information; and

when the geographic location of the moving object corresponds to the tagged area, identifying, by the processor, the moving object as a pedestrian.

2. The method of claim 1, wherein the object detection device includes a laser configured to collect range and intensity data, and the method further includes using the range and intensity data to detect the moving object and the location of the moving object.

3. The method of claim 1, wherein the map information includes a second tagged area of the roadway, wherein the second tagged area is associated with a second object type, the method further comprising:

detecting a second moving object and a second geographic location of the second moving object based on the received information; and

when the second geographic location of the second moving object corresponds to the second tagged area, identifying the second moving object based on the second object type associated with the second tagged area.

4. The method of claim 1, further comprising the processor causing the vehicle to maintain a minimum distance between the vehicle and the moving object.

5. The method of claim 1, wherein the vehicle is an autonomous vehicle and the method further comprises maneuvering the autonomous vehicle along the roadway by the processor based on the identification of the moving object.

6. The method of claim 1, further comprising, if the moving object is not within a corresponding tagged area of the roadway, using at least one image matching technique to identify the type of the moving object.

7. The method of claim 1, further comprising determining that the geographic location of the moving object corresponds to the tagged area when the geographic location is at least partially within the tagged area.

8. A device comprising:

memory storing map data including information about a roadway, the map data including a tagged area of the roadway, wherein the tagged area is associated with an object type;

a processor coupled to the memory, the processor being operable to;

determine current location of a vehicle;

receive information about the vehicle'"'"'s surroundings generated by an object detection device;

detect a moving object and a geographic location of the moving object based on the received information; and

when the geographic location of the moving object corresponds to the tagged area, identify the moving object as one of a pedestrian or a bicyclist based on the object type.

9. The device of claim 8, further comprising the object detection device.

10. The device of claim 8, wherein the object detection device includes a laser configured to collect range and intensity data, and processor is further configured to use the range and intensity data to detect the moving object and the location of the moving object.

11. The device of claim 8, wherein the map information includes a second tagged area of the roadway, wherein the second tagged area is associated with a second object type, the wherein the processor is further configured to:

detect a second moving object and a second geographic location of the second moving object based on the received information; and

when the second geographic location of the second moving object corresponds to the second tagged area, identify the second moving object based on the second object type.

12. The device of claim 8, wherein the processor is further configured to cause the vehicle to maintain a minimum distance between the vehicle and the moving object.

13. The device of claim 8, wherein the vehicle is an autonomous vehicle and the wherein the processor is further configured to maneuver the autonomous vehicle along the roadway based on the identification of the moving object.

14. The device of claim 8, wherein the processor is further configured to, if the moving object is not within a corresponding tagged area of the roadway, using at least one image matching technique to identify the type of the moving object.

15. The device of claim 8, wherein the processor is further configured to determine that the geographic location of the moving object corresponds to the tagged area when the geographic location is at least partially within the tagged area.

16. A non-transitory, tangible computer-readable storage medium on which computer readable instructions of a program are stored, the instructions, when executed by a processor, cause the processor to perform a method, the method comprising:

determining a current location of a vehicle;

accessing map data based on the current location of the vehicle, the map data including information about a roadway including a tagged area of the roadway, wherein the tagged area is associated with an object type;

receiving information about the vehicle'"'"'s surroundings from an object detection device;

detecting a moving object and a geographic location of the moving object based on the received information; and

when the geographic location of the moving object corresponds to the tagged area, identifying the moving object as one of a pedestrian or a bicyclist, based on the object type associated with the tagged area.

17. The medium of claim 16, wherein the object detection device includes a laser configured to collect range and intensity data and the method further includes using the range and intensity data to detect the moving object and the location of the moving object.

18. The medium of claim 16, wherein the map information includes a second tagged area of the roadway, a tag of the second tagged area of the roadway identifying a crosswalk wherein the tagged area is associated with an object type, the method further comprising:

detecting a second moving object and a second geographic location of the second moving object based on the received information; and

when the second geographic location of the second moving object corresponds to the second tagged area, identifying the second moving object based on the second object type.

19. The medium of claim 16, further comprising the processor causing the vehicle to maintain a minimum distance between the vehicle and the moving object.

20. The medium of claim 16, wherein the vehicle is an autonomous vehicle and the method further comprises maneuvering the autonomous vehicle along the roadway by the processor based on the identification of the moving object.

21. The medium of claim 16, wherein the method further comprises, if the moving object is not within a corresponding tagged area of the roadway, using at least one image matching technique to identify the type of the moving object.

22. The medium of claim 16, wherein the method further comprises determining that the geographic location of the moving object corresponds to the tagged area when the geographic location is at least partially within the tagged area.