SYSTEM AND METHOD FOR PREDICTING BEHAVIORS OF DETECTED OBJECTS

• US 20140136045A1
• Filed: 01/22/2014
• Published: 05/15/2014
• Est. Priority Date: 10/05/2010
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Zhu, Jiajun, Ferguson, David Ian Franklin, Dolgov, Dmitri A.
• Granted Patent: US 8,948,955 B2
• Time in Patent Office: Days
• US Class Current: 701/23
• CPC Class Codes: B60R 1/23 with a predetermined field of view
• CPC Class Codes: B60R 2300/30 characterised by the type of image processing
• CPC Class Codes: B60T 17/18 Safety devices; Monitoring
• CPC Class Codes: B60T 17/221 Procedure or apparatus for checking or keeping in a correct functioning condition of brake systems hydraulic pressure systems in general F15B19/00, F15B21/04; testing structures or apparatus G01M
• CPC Class Codes: B60T 2201/022 Collision avoidance systems
• CPC Class Codes: B60T 2210/32 Vehicle surroundings
• CPC Class Codes: B60T 2270/406 Test-mode; Self-diagnosis
• CPC Class Codes: B60T 7/22 initiated by contact of vehicle, e.g. bumper, with an external object, e.g. another vehicle , or by means of contactless obstacle detectors mounted on the vehicle
• CPC Class Codes: B60T 8/00 Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force by changing number of effective brake cylinders in power brake systems B60T17/10
• CPC Class Codes: B60T 8/17 Using electrical or electronic regulation means to control braking detecting or indicating faulty operation B60T8/885
• CPC Class Codes: B60T 8/885 using electrical circuitry
• CPC Class Codes: B60W 2050/0292 Fail-safe or redundant systems, e.g. limp-home or backup systems
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2420/408 Radar; Laser, e.g. lidar
• CPC Class Codes: B60W 2552/05 Type of road, e.g. motorways, local streets, paved or unpaved roads
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• 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 30/186 excessive wear or burn out of friction elements, e.g. clutches
• CPC Class Codes: B60W 40/06 : Road conditions
• CPC Class Codes: B60W 50/14 : Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: B62D 6/00 : Arrangements for automatically controlling steering depending on driving conditions sensed and responded to, e.g. control circuits means for initiating a change in direction B62D1/00; steering valves B62D5/06; combined with means for inclining the vehicle body or wheels on bends B62D9/00
• CPC Class Codes: G01C 21/3617 : using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement
• 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 17/931 : of land vehicles
• CPC Class Codes: G05B 2219/2637 : Vehicle, car, auto, wheelchair
• CPC Class Codes: G05D 1/0055 : with safety arrangements
• CPC Class Codes: G05D 1/0088 : characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/021 : specially adapted to land vehicles
• CPC Class Codes: G05D 1/0212 : with means for defining a desired trajectory involving a plurality of land vehicles G05D1/0287
• CPC Class Codes: G05D 1/0214 : in accordance with safety or protection criteria, e.g. avoiding hazardous areas monitoring the location of vehicles within a certain area, e.g. forbidden or allowed areas, in traffic control systems for road vehicles G08G1/13
• CPC Class Codes: G05D 1/024 : in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0246 : using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0257 : using a radar radar systems designed for anti-collision purposes between land vehicles or between land vehicle and fixed obstacles G01S13/931
• CPC Class Codes: G05D 1/0274 : using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G05D 1/0276 : using signals provided by a source external to the vehicle involving a plurality of vehicles G05D1/0287; automatically controlling vehicle speed responsive to externally generated signals B60K31/0058
• CPC Class Codes: G05D 1/0278 : using satellite positioning signals, e.g. GPS
• CPC Class Codes: G06Q 10/02 : Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 30/02 : Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0207 : Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 40/08 : Insurance
• CPC Class Codes: G06T 2207/10004 : Still image; Photographic image
• CPC Class Codes: G06T 2207/10028 : Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/30236 : Traffic on road, railway or crossing
• CPC Class Codes: G06T 2207/30252 : Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 2207/30261 : Obstacle
• CPC Class Codes: G06T 7/20 : Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/223 : using block-matching
• CPC Class Codes: G06T 7/231 : using full search
• CPC Class Codes: G06T 7/521 : from laser ranging, e.g. using interferometry; from the projection of structured light
• CPC Class Codes: G06T 7/74 : involving reference images or patches
• CPC Class Codes: G06V 10/255 : Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 20/56 : exterior to a vehicle by using sensors mounted on the vehicle
• 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 20/588 : Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G06V 20/64 : Three-dimensional objects
• CPC Class Codes: G07C 9/00563 : using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns

Abstract

Aspects of the invention relate generally to autonomous vehicles. Specifically, the features described may be used alone or in combination in order to improve the safety, use, driver experience, and performance of these vehicles.

Claims

1-23. -23. (canceled)

24. A method comprising:

controlling, by one or more processors, a vehicle according to a first control strategy;

detecting, by the one or more processors, an object at a location external to the vehicle using one or more sensors;

predicting, by the one or more processors, a future behavior of the detected object based on the detected location of the object, a time when the object was detected, and behavior data that indicates how other objects have operated at the detected location at a similar time; and

modifying, by the one or more processors, the first control strategy to obtain a second control strategy for controlling the vehicle based on the predicted future behavior of the detected object.

25. The method of claim 24, further comprising:

using the detected location to determine a state of the object, and

wherein the determined state of the object is used to further predict the future behavior.

26. he method of claim 25, wherein the determined state relates to at least one of:

traffic lane in which the detected object is traveling, speed, acceleration, entry onto a road, exit off of a road, activation of headlights, activation of taillights, or activation of blinkers.

27. The method of claim 24, wherein the behavior data is based on movement data for a plurality of other objects at one or more locations that are contextually similar to the detected location.

28. The method of claim 24, wherein:

the second control strategy comprises providing a command to orient the vehicle in a position and velocity based at least in part on the likely behavior of the detected object; and

providing the command to orient the vehicle includes positioning the vehicle at a predetermined distance from the detected object, the predetermined distance being based, at least in part, on a classification of the detected object.

29. The method of claim 24, wherein the likely behavior of the detected object is provided as a probability of the detected object entering to one or more states.

30. The method of claim 24, further comprising:

receiving updated behavior data from a remote server computer, and

wherein predicting the future behavior of the detected object is based at least in part on the updated behavior data.

37. The method of claim 24, further comprising:

receiving updated behavior data from a remote server computer, and

wherein predicting the future behavior of the detected object is based at least in part on the updated behavior data.

31. A system comprising one or more processors configured to:

control a vehicle according to a first control strategy;

detect an object at a location external to the vehicle using one or more sensors;

predict a future behavior of the detected object based on the detected location of the object, a time when the object was detected, and behavior data that indicates how other objects have operated at the detected location at a similar time; and

modify the first control strategy to obtain a second control strategy for controlling the vehicle based on the predicted future behavior of the detected object.

32. The system of claim 31, wherein the one or more processors are further configured to:

use the detected location to determine a state of the object, and

wherein the determined state of the object is used to further predict the future behavior.

33. The system of claim 32, wherein the determined state relates to at least one of:

traffic lane in which the detected object is traveling, speed, acceleration, entry onto a road, exit off of a road, activation of headlights, activation of taillights, or activation of blinkers.

34. The system of claim 31, wherein the behavior data is based on movement data for a plurality of other objects at one or more locations that are contextually similar to the detected location.

35. The system of claim 31, wherein:

the second control strategy comprises providing a command to orient the vehicle in a position and velocity based at least in part on the likely behavior of the detected object; and

providing the command to orient the vehicle includes positioning the vehicle at a predetermined distance from the detected object, the predetermined distance being based, at least in part, on a classification of the detected object.

36. The system of claim 31, wherein the likely behavior of the detected object is provided as a probability of the detected object entering to one or more states.

38. 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:

controlling a vehicle according to a first control strategy;

detecting an object at a location external to the vehicle using one or more sensors;

predicting a future behavior of the detected object based on the detected location of the object, a time when the object was detected, and behavior data that indicates how other objects have operated at the detected location at a similar time; and

modifying the first control strategy to obtain a second control strategy for controlling the vehicle based on the predicted future behavior of the detected object.

39. The medium of claim 38, wherein the method further comprises:

using the detected location to determine a state of the object, and

wherein the determined state of the object is used to further predict the future behavior.

40. The medium of claim 39, wherein the determined state relates to at least one of:

traffic lane in which the detected object is traveling, speed, acceleration, entry onto a road, exit off of a road, activation of headlights, activation of taillights, or activation of blinkers.

41. The medium of claim 38, wherein the behavior data is based on movement data for a plurality of other objects at one or more locations that are contextually similar to the detected location.

42. The medium of claim 38, wherein the likely behavior of the detected object is provided as a probability of the detected object entering to one or more states.

43. The medium of claim 38, wherein the method further comprises:

receiving updated behavior data from a remote server computer, and

wherein predicting the future behavior of the detected object is based at least in part on the updated behavior data.