Robotic vehicle active safety systems and methods

• US 10,543,838 B2
• Filed: 03/28/2017
• Issued: 01/28/2020
• 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-Klay, Timothy David, Levinson, Jesse Sol, Lind, Amanda Blair
• Primary Examiner(s): Patton, Spencer D
• Application Number:
  US15/471,209
• Publication Number:
  US 20170297568A1
• Time in Patent Office: 1,036 Days
• 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 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/20 Static objects
• CPC Class Codes: B60W 2554/4026 Cycles
• CPC Class Codes: B60W 2554/4029 Pedestrians
• CPC Class Codes: B60W 2554/4041 Position
• CPC Class Codes: B60W 2554/80 Spatial relation or speed relative to objects
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2710/18 Braking system
• CPC Class Codes: B60W 2710/20 Steering systems
• CPC Class Codes: B60W 2710/30 Auxiliary equipments
• 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 60/0016 of the vehicle or its occupants
• CPC Class Codes: B60W 60/0027 using trajectory prediction for other traffic participants
• 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 13/87 Combinations of radar systems, e.g. primary radar and secondary radar
• CPC Class Codes: G01S 2013/9316 combined with communication equipment with other vehicles or with base stations
• CPC Class Codes: G01S 2013/9322 : using additional data, e.g. driver condition, road state or weather data
• CPC Class Codes: G01S 7/4808 : Evaluating distance, position or velocity data
• CPC Class Codes: G05D 1/0011 : associated with a remote control arrangement
• CPC Class Codes: G05D 1/0027 : involving a plurality of vehicles, e.g. fleet or convoy travelling fleet control of land vehicles from a control room G05D1/0297; traffic control systems for road vehicles G08G1/00; for marine craft G08G3/00; for aircraft G08G5/00
• CPC Class Codes: G05D 1/0044 : by providing the operator with a computer generated representation of the environment of the vehicle, e.g. virtual reality, maps maps used for automatic navigation G05D1/0274; flight directors G01C23/005
• 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 1/0291 : Fleet control monitoring fleets in traffic control systems for road vehicles G08G1/127, G08G1/127
• CPC Class Codes: G06F 3/04842 : Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04847 : Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06F 3/1454 : involving copying of the display data of a local workstation or window to a remote workstation or window so that an actual copy of the data is displayed simultaneously on two or more displays, e.g. teledisplay
• CPC Class Codes: G06F 3/147 : using display panels
• CPC Class Codes: G09G 2354/00 : Aspects of interface with display user
• CPC Class Codes: G09G 2360/08 : Power processing, i.e. workload management for processors involved in display operations, such as CPUs or GPUs
• CPC Class Codes: G09G 2370/16 : Use of wireless transmission of display information
• CPC Class Codes: G09G 2380/10 : Automotive applications
• CPC Class Codes: G09G 5/14 : Display of multiple viewports
• CPC Class Codes: G09G 5/363 : Graphics controllers
• CPC Class Codes: H04W 4/44 : for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]

Abstract

Systems 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, road debris, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may be configured to implement active safety measures to avoid the potential collision and/or mitigate the impact of an actual collision to passengers in the autonomous vehicle and/or to the autonomous vehicle itself. Interior safety systems, exterior safety systems, a drive system or some combination of those systems may be activated to implement active safety measures in the autonomous vehicle.

Claims

1. A method comprising:

receiving trajectory data representing a trajectory of an autonomous vehicle in an environment external to the autonomous vehicle;

determining object data comprising a position of an object in the environment, an object type of the object, and an object classification of the object;

determining a predicted location of the object in the environment based at least in part on the object data;

determining that the predicted location of the object coincides with the trajectory;

determining a first threshold location along the trajectory based at least in part on the predicted location of the object and the object data;

determining a second threshold location along the trajectory based at least in part on the predicted location of the object and the object data;

sensing an updated object position of the object in the environment;

implementing a safety action using a safety system based at least in part on the updated object position, the safety action associated with the first threshold location or the second threshold location.

2. The method of claim 1, further comprising:

determining a probability of impact of the object with the autonomous vehicle, wherein at least one of the first threshold location or the second threshold location is determined based at least in part on the probability of impact.

3. The method of claim 2, wherein the probability of impact is used to determine at least one of a first distance of the first threshold location from the autonomous vehicle or a second distance of the second threshold location from the autonomous vehicle.

4. The method of claim 1, wherein the safety system comprises an acoustic beam steering array, and

further wherein the safety action comprises a first safety action and a second safety action, the first safety action including emitting a first audio alert at a first angle relative to the trajectory and the second safety action comprises emitting a second audio alert at a second angle relative to the trajectory, the second audio alert differing from the first audio alert, the first safety action associated with the first threshold location, and the second safety action associated with the second threshold location.

5. The method of claim 1, wherein the safety action includes a first safety action that comprises emitting a first light pattern and a second safety action that comprises emitting a second light pattern, the first safety action associated with the first threshold location and the second safety action associated with the second threshold location.

6. The method of claim 1, further comprising repeatedly sensing an updated object position,

wherein the implementing the safety action comprises tensioning a seat belt.

7. The method of claim 1, further comprising determining a collision avoidance trajectory to maneuver the autonomous vehicle from the trajectory.

8. A system comprising:

an autonomous vehicle, the autonomous vehicle having a plurality of sensors for sensing an object in an environment surrounding the autonomous vehicle; and

a computing system communicatively coupled to the autonomous vehicle to receive data from the plurality of sensors and to transmit instructions to the autonomous vehicle, the computing system being programmed to;

determine object data comprising a position of the object, an object type of the object, and an object classification of the object;

determine a predicted location of the object in the environment based at least in part on the object data;

determine that the predicted location of the object coincides with a trajectory of the autonomous vehicle;

determine a first threshold location along the trajectory based at least in part on the predicted location of the object and the object data;

determine a second threshold location along the trajectory based at least in part on the predicted location of the object and the object data;

cause the autonomous vehicle to emit a first alert based at least in part on a determination that an updated location of the object coincides with the first threshold boundary; and

cause the autonomous vehicle to emit a second alert based at least in part on a determination that the updated location of the object coincides with the second threshold boundary.

9. The system of claim 8, wherein the computing system is further programmed to determine a probability of impact of the object with the autonomous vehicle, wherein at least one of the threshold location or the second threshold location is determined based at least in part on the probability of impact.

10. The method of claim 9, wherein the probability of impact is used to determine at least one of a first distance of the first threshold location from the autonomous vehicle or a second distance of the second threshold location from the autonomous vehicle.

11. The system of claim 8, wherein the autonomous vehicle is a bi-directional vehicle configured to drive forward in a first direction or drive forward in a substantially opposite second direction without turning around the autonomous vehicle, and the computing system is further programmed to generate instructions for the autonomous vehicle to change direction from driving forward in the first direction along the trajectory to driving forward in the second direction without turning around based on a determination that the updated location of the object coincides with the second threshold boundary.

12. The system of claim 8, wherein the safety system comprises an acoustic beam steering array, the first safety action comprises emitting a first audio alert at a first angle relative to the trajectory and the second safety action comprises emitting a second audio alert at a second angle relative to the trajectory, the second audio alert being different from the first audio alert.

13. The system of claim 8, wherein the safety system comprises a light emitter, the first safety action comprises emitting a first light pattern, and the second safety action comprises emitting a second light pattern, the second light pattern being different from the first light pattern.

14. A method comprising:

receiving trajectory data representing a trajectory of an autonomous vehicle in an environment external to the autonomous vehicle;

determining object data comprising a position of an object in the environment, an object type of the object, and an object classification of the object;

determining a probability of impact of the autonomous vehicle and the object based at least in part on the trajectory and the object data;

based at least in part on the probability of impact, determining a first threshold location along the trajectory and a second threshold location along the trajectory;

sensing an updated object position of the object in the environment;

determining an updated vehicle position along the trajectory; and

implementing a first safety action using a safety system in response to the updated object position and updated vehicle position corresponding to the first threshold location, or implementing a second safety action using the safety system in response to the updated vehicle position corresponding to the second threshold location.

15. The method of claim 14, further comprising determining a predicted next location of the object based at least in part on the object data, the predicted next location being further used to determine the probability of impact.

16. The method of claim 14, further comprising:

determining a predicted location of a collision between the object and the autonomous vehicle, the predicted location being used to determine the probability of impact.

17. The method of claim 14, wherein at least one of determining the first threshold location comprises determining a first distance from the autonomous vehicle or determining the second threshold location comprises determining a second distance from the autonomous vehicle.

18. The method of claim 14, wherein the safety system comprises an acoustic beam steering array, the first safety action comprises emitting a first audio alert at a first angle relative to the trajectory and the second safety action comprises emitting a second audio alert at a second angle relative to the trajectory.

19. The method of claim 14, wherein the safety system comprises a light emitter, the first safety action comprises emitting a first light pattern, and the second safety action comprises emitting a second light pattern.

20. The method of claim 14, wherein the object data further comprises an object behavior, the method further comprising:

determining an updated object behavior; and

de-escalating the second safety action, based at least in part on the updated object behavior.