Obstacle evaluation technique

• US 9,495,875 B2
• Filed: 06/05/2014
• Issued: 11/15/2016
• Est. Priority Date: 06/06/2012
• Status: Active Grant

• Current Assignee: Waymo LLC (Alphabet Inc.)
• Original Assignee: X Development LLC (Alphabet Inc.)
• Inventors: Dowdall, Jonathan Baldwin, Zhu, Jiajun
• Primary Examiner(s): Nguyen, Nga X
• Application Number:
  US14/296,670
• Publication Number:
  US 20140288817A1
• Time in Patent Office: 894 Days
• Field of Search: 701300-301, 340/436
• US Class Current: 1/1
• CPC Class Codes: B60R 21/00 Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks safety belts or body harnesses in vehicles B60R22/00; devices, apparatus or methods for life-saving in general A62B; safety devices for propulsion unit control specially adapted for, or arranged in, vehicles B60K28/00; seats constructed to protect the occupant from the effect of abnormal g-forces, e.g. crash or safety seats, B60N2/42; energy-absorbing arrangements for hand wheels for steering vehicles B62D1/11; energy-absorbing arrangements for vehicle steering columns B62D1/19; harnessing in aircraft B64D25/00
• CPC Class Codes: B60R 21/013 including means for detecting collisions, impending collisions or roll-over
• CPC Class Codes: B60W 30/08 Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: B60W 30/095 Predicting travel path or likelihood of collision
• 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 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes

Abstract

A vehicle configured to operate in an autonomous mode may engage in an obstacle evaluation technique that includes employing a sensor system to collect data relating to a plurality of obstacles, identifying from the plurality of obstacles an obstacle pair including a first obstacle and a second obstacle, engaging in an evaluation process by comparing the data collected for the first obstacle to the data collected for the second obstacle, and in response to engaging in the evaluation process, making a determination of whether the first obstacle and the second obstacle are two separate obstacles.

Claims

1. A vehicle comprising:

at least one sensor;

at least one processor; and

data storage comprising instructions executable by the at least one processor to;

receive from the at least one sensor data relating to a plurality of potential obstacles,

conduct a first evaluation on at least a subset of the plurality of potential obstacles, the first evaluation including a first threshold comparison of the received data,

classify the at least a subset of potential non-stationary obstacles as a single non-stationary obstacle when the first evaluation indicates that the first threshold comparison of the received data is not met,

classify the at least a subset of potential obstacles as two separate non-stationary obstacles when the first evaluation indicates that at least one first threshold comparison of the received data is met;

determine that one or more environmental conditions have changed and responsively changing the first threshold to a second threshold;

conduct a second evaluation on at least a subset of the plurality of potential obstacles, the second evaluation including a second threshold comparison of the received data,

classify the at least a subset of potential non-stationary obstacles as a single nonstationary obstacle when the second evaluation indicates that the second threshold comparison of the received data is not met,

classify the at least a subset of potential obstacles as two separate non-stationary obstacles when the second evaluation indicates that at least one second threshold comparison of the received data is met.

2. The vehicle of claim 1, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them a change in distance that exceeds a distance threshold.

3. The vehicle of claim 1, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them a change in change in speed differential that exceeds a speed threshold.

4. The vehicle of claim 1, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them an orientation differential that exceeds an orientation threshold.

5. The vehicle of claim 1, wherein classifying the at least a subset of potential non-stationary obstacles as a single non-stationary obstacle comprises merging the received data that relates to the at least a subset of potential non-stationary obstacles.

6. The vehicle of claim 1, wherein at least one of the first and second evaluation comprises a respective evaluation of every at least a subset of potential non-stationary obstacles in the plurality of potential obstacles.

7. A method comprising:

collecting data relating to a plurality of potential obstacles;

conducting a first evaluation on the at least a subset of the plurality of potential obstacles, the at least one first evaluation including a first threshold comparison of the received data,

classifying the at least a subset of potential non-stationary obstacles as a single non-stationary obstacle when the first evaluation indicates that the first threshold comparison of the received data is not met,

classifying the at least a subset of potential obstacles as two separate non-stationary obstacles when the first evaluation indicates that at least one first threshold comparison of the received data is met;

determining that one or more environmental conditions have changed and responsively changing the first threshold to a second threshold;

conducting a second evaluation on at least a subset of the plurality of potential obstacles, the second evaluation including a second threshold comparison of the received data,

classifying the at least a subset of potential non-stationary obstacles as a single nonstationary obstacle when the second evaluation indicates that the second threshold comparison of the received data is not met,

classifying the at least a subset of potential obstacles as two separate non-stationary obstacles when the second evaluation indicates that at least one second threshold comparison of the received data is met.

8. The method of claim 7, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them a change in distance that exceeds a distance threshold.

9. The method of claim 7, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them a change in change in speed differential that exceeds a speed threshold.

10. The method of claim 7, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them an orientation differential that exceeds an orientation threshold.

11. The method of claim 7, wherein classifying the at least a subset of potential non-stationary obstacles as a single non-stationary obstacle comprises merging the received data that relates to the at least a subset of potential non-stationary obstacles.

12. The method of claim 7, wherein at least one of the first and second evaluation comprises a respective evaluation of every at least a subset of potential non-stationary obstacles in the plurality of potential obstacles.

13. A non-transitory computer readable medium (CRM) having stored thereon instructions executable by a computing device to cause the computing device to perform functions, the functions comprising:

collecting data relating to a plurality of potential obstacles;

conducting a first evaluation on the at least a subset of the plurality of potential obstacles, the at least one first evaluation including a first threshold comparison of the received data,

classifying the at least a subset of potential non-stationary obstacles as a single non-stationary obstacle when the first evaluation indicates that the first threshold comparison of the received data is not met,

classifying the at least a subset of potential obstacles as two separate non-stationary obstacles when the first evaluation indicates that at least one first threshold comparison of the received data is met;

determining that one or more environmental conditions have changed and responsively changing the first threshold to a second threshold;

conducting a second evaluation on at least a subset of the plurality of potential obstacles, the second evaluation including a second threshold comparison of the received data,

classifying the at least a subset of potential non-stationary obstacles as a single nonstationary obstacle when the second evaluation indicates that the second threshold comparison of the received data is not met,

classifying the at least a subset of potential obstacles as two separate non-stationary obstacles when the second evaluation indicates that at least one second threshold comparison of the received data is met.

14. The CRM of claim 13, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them a change in distance that exceeds a distance threshold.

15. The CRM of claim 13, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them a change in change in speed differential that exceeds a speed threshold.

16. The CRM of claim 13, wherein at least one of the first and second evaluation comprises a determination of whether the at least a subset of potential non-stationary obstacles has had between them an orientation differential that exceeds an orientation threshold.

17. The CRM of claim 13, wherein classifying the at least a subset of potential non-stationary obstacles as a single non-stationary obstacle comprises merging the received data that relates to the at least a subset of potential non-stationary obstacles.

18. The CRM of claim 13, wherein at least one of the first and second evaluation comprises a respective evaluation of every at least a subset of potential non-stationary obstacles in the plurality of potential obstacles.