ACTIVE LIGHTING CONTROL FOR COMMUNICATING A STATE OF AN AUTONOMOUS VEHICLE TO ENTITIES IN A SURROUNDING ENVIRONMENT

• US 20170120804A1
• Filed: 11/04/2015
• Published: 05/04/2017
• Est. Priority Date: 11/04/2015
• Status: Active Grant

• Current Assignee: Zoox Inc. (Amazon.com, Inc.)
• Original Assignee: Zoox Inc. (Amazon.com, Inc.)
• Inventors: Kentley, Timothy David, Gamara, Rachad Youssef
• Granted Patent: US 9,804,599 B2
• Time in Patent Office: Days
• CPC Class Codes: B60N 2/42 the seat constructed to protect the occupant from the effect of abnormal g-forces, e.g. crash or safety seats for protecting children B60N2/26; arm-rests B60N2/75; head-rests B60N2/888
• CPC Class Codes: B60Q 1/0035 relative to the vehicle
• CPC Class Codes: B60Q 1/085 due to special conditions, e.g. adverse weather, type of road, badly illuminated road signs or potential dangers B60Q1/10, B60Q1/12, B60Q1/1423 take precedence
• CPC Class Codes: B60Q 1/26 the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic
• CPC Class Codes: B60Q 1/2611 Indicating devices mounted on the roof of the vehicle
• CPC Class Codes: B60Q 1/268 on windscreens or windows B60Q1/302 takes precedence; lighting devices for vehicle interior on or for windows B60Q3/208
• CPC Class Codes: B60Q 1/44 for indicating braking action or preparation for braking, e.g. by detection of the foot approaching the brake pedal
• CPC Class Codes: B60Q 1/442 visible on the front side of the vehicle, e.g. for pedestrians
• CPC Class Codes: B60Q 1/507 specific to autonomous vehicles
• CPC Class Codes: B60Q 1/525 automatically indicating risk of collision between vehicles in traffic or with pedestrians, e.g. after risk assessment using the vehicle sensor data
• CPC Class Codes: B60Q 2300/45 Special conditions, e.g. pedestrians, road signs or potential dangers
• CPC Class Codes: B60Q 2400/40 Welcome lights, i.e. specific or existing exterior lamps to assist leaving or approaching the vehicle
• CPC Class Codes: B60Q 2400/50 Projected symbol or information, e.g. onto the road or car body
• CPC Class Codes: B60Q 5/005 automatically actuated
• CPC Class Codes: B60Q 5/006 indicating risk of collision between vehicles or with pedestrians
• CPC Class Codes: B60R 21/01 Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents electrical circuits for transmission of signals between steering wheel and the vehicle itself B60R16/027; for electrically actuating belt retractor locking means B60R22/343
• CPC Class Codes: B60R 21/36 using airbags
• 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: 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 1/0212 with means for defining a desired trajectory involving a plurality of land vehicles G05D1/0287
• 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 1/005 : including pedestrian guidance indicator
• CPC Class Codes: G08G 1/056 : with provision for distinguishing direction of travel
• CPC Class Codes: G08G 1/09623 : Systems involving the acquisition of information from passive traffic signs by means mounted on the vehicle G08G1/0967 takes precedence
• 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 1/166 : 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: G08G 1/202 : Dispatching vehicles on the basis of a location, e.g. taxi dispatching
• CPC Class Codes: G10K 11/18 : Methods or devices for transmitting, conducting or directing sound G10K11/02, G10K11/36 take precedence
• CPC Class Codes: G10K 11/34 : using electrical steering of transducer arrays, e.g. beam steering constructional aspects B06B1/0607, B06B1/085

Abstract

Systems, apparatus and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input to determine whether an object external to an autonomous vehicle (e.g., another vehicle, a pedestrian, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may include a light emitter positioned external to a surface of the autonomous vehicle and being configured to implement a visual alert by emitting light from the light emitter. Data representing a light pattern may be received by the light emitter and the light emitted by the display may be indicative of the light pattern. The light pattern may be selected to gain the attention of the object (e.g., a pedestrian, a driver of a car, a bicyclists, etc.) in order to avoid the potential collision or to alert the object to the presence of the autonomous vehicle.

Claims

1. A method comprising:

accessing sensor data generated by a sensor system of an autonomous vehicle;

determining, based at least in part on the sensor data, a location of the autonomous vehicle within the environment, wherein the location of the autonomous vehicle identifies a position and orientation of the autonomous vehicle within the environment according to a global coordinate system;

calculating, based at least in part on the location of the autonomous vehicle and at least a portion of the sensor data, a trajectory of the autonomous vehicle, wherein the trajectory indicates a planned path associated with navigating the autonomous vehicle between at least a first location and a second location within the environment;

identifying, based at least in part on the sensor data, an object within the environment;

determining a location of the object in the environment, wherein the location of the object identifies a position and orientation of the object within the environment according to the global coordinate system;

determining, based at least in part on the location of the object and the location of the autonomous vehicle, to provide a visual alert;

selecting a light pattern from a plurality of light patterns, wherein a first one of light patterns is associated with a first level of urgency of the visual alert, and a second one of the light patterns is associated with a second level of urgency of the visual alert;

selecting, from a plurality of light emitters of the autonomous vehicle, a light emitter to provide the visual alert; and

causing the light emitter to provide the visual alert, the light emitter emitting light indicative of the light pattern into the environment.

2. The method of claim 1, further comprising:

calculating, based at least in part on the location of the object and the trajectory of the autonomous vehicle, an orientation of the autonomous vehicle relative to the location of the object; and

wherein selecting the light emitter is based at least in part on the orientation of the autonomous vehicle relative to the location of the object.

3. The method of claim 1, further comprising:

estimating, based at least in part on the location of the object and the location of the autonomous vehicle, a threshold event associated with causing the light emitter to provide the visual alert;

detecting an occurrence of the threshold event; and

wherein causing the light emitter of the autonomous vehicle to provide the visual alert is based at least in part on the occurrence of the threshold event.

4. The method of claim 1, further comprising:

calculating, based at least in part on the location of the object and the location of the autonomous vehicle, a distance between the autonomous vehicle and the object; and

wherein selecting the light pattern is based at least in part on the distance.

5. The method of claim 1, wherein selecting the light pattern is based at least in part on one or more of a first threshold distance or a threshold time, wherein the first threshold distance is associated with the light pattern and a second threshold distance is associated with a different light pattern, wherein the first threshold distance and the second threshold distance is less than a distance between the object and the autonomous vehicle, and wherein the threshold time is shorter in duration as compared to a time associated with the location of the autonomous vehicle and the location of the object being coincident with each other.

6. The method of claim 1, further comprising:

calculating, based at least in part on the location of the object and the trajectory of the autonomous vehicle, a time associated with the location of the autonomous vehicle and the location of the object being coincident with each other; and

wherein causing the light emitter of the autonomous vehicle to provide the visual alert is based at least in part on the time.

8. The method of claim 1, further comprising:

determining an object classification for the object, the object classification determined from a plurality of object classifications, wherein the object classifications include a static pedestrian object classification, a dynamic pedestrian object classification, a static car object classification, and a dynamic car object classification; and

wherein selecting the light pattern is based at least in part on the object classification.

9. The method of claim 1, further comprising:

accessing map data associated with the environment, the map data accessed from a data store of the autonomous vehicle;

determining position data and orientation data associated with the autonomous vehicle; and

wherein determining the location of the autonomous vehicle within the environment is based at least in part on the map data, the position data and the orientation data.

10. The method of claim 1, further comprising:

selecting a different light pattern from the plurality of light patterns based at least in part on a first location of the object before the visual alert is provided and a second location of the object after the visual alert is provided; and

causing the light emitter to provide a second visual alert, wherein the light emitter emits light indicative of the different light pattern into the environment.

11. The method of claim 1, wherein the light emitter includes a sub-section and the light pattern includes a sub-pattern associated with the sub-section, the sub-section being configured to emit light indicative of the sub-pattern, wherein at least one of the sub-patterns is indicative of one or more of a signaling function of the autonomous vehicle or a braking function of the autonomous vehicle and wherein at least one other sub-pattern is indicative of the visual alert.

15. The method of claim 1 further comprising:

receiving data representing a sensor signal indicative of a rate of rotation of a wheel of the autonomous vehicle; and

modulating the light pattern based at least in part on the rate of rotation.

21. The method of claim 1, wherein selecting, from the plurality of light emitters of the autonomous vehicle, the light emitter to provide the visual alert is based at least in part on one or more of an orientation of the autonomous vehicle, the location of the autonomous vehicle, the location of the object, or the trajectory of the object.

7. (canceled)

12-14. -14. (canceled)

16-20. -20. (canceled)

22. A system, comprising:

sensors operative to generate sensor data for an autonomous vehicle located within an environment, wherein the sensors include LIDAR sensors;

light emitters operative to emit light into the environment from the autonomous vehicle; and

one or more processors configured to perform actions, including;

determining, based at least in part on a portion of the sensor data, a location of the autonomous vehicle within the environment, wherein the location of the autonomous vehicle identifies a position and orientation of the autonomous vehicle within the environment;

calculating, based at least in part on the location of the autonomous vehicle and at least a portion of the sensor data, a trajectory of the autonomous vehicle, wherein the trajectory indicates a planned path associated with navigating the autonomous vehicle between at least a first location and a second location within the environment;

identifying, based at least in part on a portion of the sensor data, an object within the environment;

determining a location of the object, wherein the location of the object identifies a position and orientation of the object within the environment;

selecting, from a plurality of light patterns, a light pattern based at least in part on at least a portion of the sensor data;

selecting, from the light emitters, a light emitter to provide a visual alert; and

causing the light emitter to provide the visual alert by emitting light indicative of the light pattern into the environment.

23. The system of claim 22, wherein a first one of the light emitters is located on a first portion of the autonomous vehicle, and a second one of the light emitters is located on a second portion of the autonomous vehicle;

and wherein selecting the light emitter to provide the visual alert comprises

calculating, based at least in part on the location of the object and the trajectory of the autonomous vehicle, an orientation of the autonomous vehicle relative to the location of the object, and

selecting the first one of the light emitters based at least in part on the orientation of the autonomous vehicle relative to the location of the object.

24. The system of claim 22, wherein causing the light emitter to provide the visual alert comprises causing the light emitter to emit light indicative of the light pattern into the environment light during a first period of time and wherein the actions further comprise causing the light emitter to emit light indicative of a signaling function into the environment during a second period of time.

25. The system of claim 22, wherein the light emitters include a first light emitter located on a first end of the autonomous vehicle, a second light emitter located on a second end of the autonomous vehicle, a third light emitter located on a first side of the autonomous vehicle, and a fourth light emitter located on a second side of the autonomous vehicle.

26. The system of claim 22, wherein a first light emitter of the light emitters includes a first sub-section, and a second sub-section, wherein the first sub-section is operative to emit the light indicative of the light pattern into the environment, and wherein the second sub-section is operative to emit second light indicative of a signaling function.

27. The system of claim 22, further comprising a driver coupled to the light emitter, the driver configured to adjust the light emitted by the light emitter based at least on a speed of the autonomous vehicle, wherein the speed is determined, at least in part, on the sensor data.

28. The system of claim 22, wherein the acts further comprise selecting an intensity of the light emitted by the light emitter based at least in part on the location of the object and the location of the autonomous vehicle.

29. The system of claim 22, further comprising:

calculating, based at least in part on the location of the object and the trajectory of the autonomous vehicle, a time associated with the location of the autonomous vehicle and the location of the object being coincident with each other; and

causing the light emitter of the autonomous vehicle to provide the visual alert based at least in part on the time.