Construction zone object detection using light detection and ranging

• US 9,199,641 B2
• Filed: 02/23/2015
• Issued: 12/01/2015
• Est. Priority Date: 09/05/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Ferguson, David Ian, Haehnel, Dirk, Mahon, Ian
• Primary Examiner(s): Shaawat, Mussa A
• Assistant Examiner(s): INGRAM, THOMAS P
• Application Number:
  US14/629,344
• Publication Number:
  US 20150266472A1
• Time in Patent Office: 281 Days
• US Class Current: 1/1
• CPC Class Codes: B25J 19/023 including video camera means
• CPC Class Codes: B25J 9/16 Programme controls programme controls in general G05B19/00, e.g. numerical pogramme controls G05B19/18; recording or playback systems G05B19/42
• CPC Class Codes: B25J 9/1697 Vision controlled systems
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2552/53 Road markings, e.g. lane marker or crosswalk
• CPC Class Codes: B60W 2554/20 Static objects
• 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 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/0956 the prediction being responsive to traffic or environmental parameters
• CPC Class Codes: B60W 30/18163 Lane change; Overtaking manoeuvres
• CPC Class Codes: B60W 40/06 Road conditions
• CPC Class Codes: B60W 60/00184 related to infrastructure
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G01C 21/3461 Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
• CPC Class Codes: G01S 13/86 Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
• CPC Class Codes: G01S 13/865 Combination of radar systems with lidar systems
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 17/86 Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G01S 2013/93185 : Controlling the brakes
• CPC Class Codes: G01S 2013/9319 : Controlling the accelerator
• CPC Class Codes: G01S 2013/9327 : Sensor installation details
• CPC Class Codes: G01S 2013/93271 : in the front of the vehicles
• CPC Class Codes: G01S 2013/93273 : on the top of the vehicles
• CPC Class Codes: G01S 2013/93275 : in the bumper area
• CPC Class Codes: G01S 2013/93277 : in the lights
• CPC Class Codes: G01S 7/4808 : Evaluating distance, position or velocity data
• CPC Class Codes: G05D 1/021 : specially adapted to land vehicles
• CPC Class Codes: G05D 1/0246 : using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0251 : extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision stereoscopic image analysis H04N13/00; depth recovery from images G06T7/593
• CPC Class Codes: G05D 1/027 : comprising intertial navigation means, e.g. azimuth detector inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165
• CPC Class Codes: G06V 20/10 : Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• 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: G06V 20/582 : of traffic signs
• CPC Class Codes: G06V 20/588 : Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G08G 1/16 : Anti-collision systems road vehicle drive control systems for predicting or avoiding probable or impending collision otherwise than by control of a particular sub-unit B60W30/08
• CPC Class Codes: G08G 1/165 : for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 : for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 : Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: Y10S 901/47 : Optical

Abstract

Methods and systems for construction zone object detection are described. A computing device may be configured to receive, from a LIDAR, a 3D point cloud of a road on which a vehicle is travelling. The 3D point cloud may comprise points corresponding to light reflected from objects on the road. Also, the computing device may be configured to determine sets of points in the 3D point cloud representing an area within a threshold distance from a surface of the road. Further, the computing device may be configured to identify construction zone objects in the sets of points. Further, the computing device may be configured to determine a likelihood of existence of a construction zone, based on the identification. Based on the likelihood, the computing device may be configured to modify a control strategy of the vehicle; and control the vehicle based on the modified control strategy.

Claims

1. A method, comprising:

selecting, by a computing device of a vehicle, a portion of a three-dimensional (3D) point cloud representing an area within a predetermined threshold distance from a surface of a road of travel of the vehicle;

identifying one or more construction zone objects in the selected portion;

determining, using the computing device, a likelihood of existence of a construction zone based on the identified one or more construction zone objects;

in response to the likelihood exceeding a threshold likelihood, determining a severity of road changes based on a number and locations of the one or more construction zone objects; and

controlling, using the computing device, the vehicle based on the likelihood of existence of the construction zone and the severity of road changes.

2. The method of claim 1, wherein the vehicle is in an autonomous operation mode.

3. The method of claim 1, wherein determining the likelihood of existence of the construction zone comprises determining, based on the number and locations of the one or more construction zone objects, a given likelihood that the one or more construction zone objects define a lane boundary.

4. The method of claim 1, wherein the one or more construction zone objects are construction cones or construction barrels.

5. The method of claim 1, wherein determining the likelihood of the existence of the construction zone comprises determining that the one or more construction zone objects are within a predetermined distance of each other.

6. The method of claim 1, wherein identifying the one or more construction zone objects in the selected portion comprises determining, for each identified construction zone object, a respective likelihood of the identification.

7. The method of claim 6, wherein determining the respective likelihood of the identification comprises:

identifying a shape in the selected portion; and

matching the shape to one or more shapes of standard construction zone objects.

8. A non-transitory computer readable medium having stored thereon instructions that, when executed by a computing device of a vehicle, cause the computing device to perform functions comprising:

selecting a portion of a three-dimensional (3D) point cloud representing an area within a predetermined threshold distance from a surface of a road of travel of the vehicle;

identifying one or more construction zone objects in the selected portion;

determining a likelihood of existence of a construction zone based on the identified one or more construction zone objects;

in response to the likelihood exceeding a threshold likelihood, determining a severity of road changes based on a number and locations of the one or more construction zone objects; and

controlling the vehicle based on the likelihood of existence of the construction zone and the severity of road changes.

9. The non-transitory computer readable medium of claim 8, wherein the one or more construction zone objects are construction cones or construction barrels.

10. The non-transitory computer readable medium of claim 8, wherein the function of determining the likelihood of the existence of the construction zone comprises determining that the one or more construction zone objects are within a predetermined distance of each other.

11. The non-transitory computer readable medium of claim 8, wherein the function of determining the likelihood of the existence of the construction zone comprises determining, based on the number and locations of the one or more construction zone objects, a given likelihood that the one or more construction zone objects define a lane boundary.

12. The non-transitory computer readable medium of claim 8, wherein the function of identifying one or more construction zone objects in the selected portion comprises:

identifying a shape in the selected portion; and

matching the shape to one or more shapes of standard construction zone objects.

13. A control system for a vehicle, comprising:

a light detection and ranging (LIDAR) device configured to capture a three-dimensional (3D) point cloud representing an area within a predetermined threshold distance from a surface of a road of travel of the vehicle;

a computing device in communication with the LIDAR device; and

data storage comprising instructions that, when executed by the computing device, cause the control system to perform functions comprising;

selecting a portion of the three-dimensional (3D) point cloud;

identifying one or more construction zone objects in the selected portion;

determining a likelihood of existence of a construction zone based on the identified one or more construction zone objects;

in response to the likelihood exceeding a threshold likelihood, determining a severity of road changes based on a number and locations of the one or more construction zone objects; and

controlling the vehicle based on the likelihood of existence of the construction zone and the severity of road changes.

14. The control system of claim 13, wherein the one or more construction zone objects are construction cones or construction barrels.

15. The control system of claim 13, wherein the function of determining the likelihood of existence of the construction zone comprises determining, based on the number and locations of the one or more construction zone objects, a given likelihood that the one or more construction zone objects define a lane boundary.

16. The control system of claim 15, wherein computing device is configured to have access to map information indicative of location of lane boundaries on the road, wherein determining the severity of road changes is based on a difference between location of the lane boundary defined by the one or more construction zone objects and a given lane boundary indicated by the map information.

17. The control system of claim 13, wherein the function of identifying one or more construction zone objects in the selected portion comprises:

identifying a shape in the selected portion; and

matching the shape to one or more shapes of standard construction zone objects.