Facilitating Vehicle Driving and Self-Driving

• US 20170277195A1
• Filed: 05/25/2017
• Published: 09/28/2017
• Est. Priority Date: 03/23/2016
• Status: Abandoned Application

• Current Assignee: Motional AD, LLC (Aptiv PLC)
• Original Assignee: nuTonomy, Inc. (Aptiv PLC)
• Inventors: Frazzoli, Emilio, Iagnemma, Karl
• Application Number:
  US15/605,388
• Publication Number:
  US 20170277195A1
• Time in Patent Office: Days
• CPC Class Codes: B60W 2050/0013 Optimal controllers
• CPC Class Codes: B60W 2050/146 Display means
• CPC Class Codes: B60W 2420/40 Photo, light or radio wave sensitive means, e.g. infrared sensors
• 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 2420/54 Audio sensitive means, e.g. ultrasound
• CPC Class Codes: B60W 2510/18 Braking system
• CPC Class Codes: B60W 2510/20 Steering systems
• CPC Class Codes: B60W 2540/18 Steering angle
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• CPC Class Codes: B60W 2552/50 Barriers
• CPC Class Codes: B60W 2552/53 Road markings, e.g. lane marker or crosswalk
• 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 2554/406 Traffic density
• CPC Class Codes: B60W 2554/60 Traversable objects, e.g. speed bumps or curbs
• CPC Class Codes: B60W 2554/802 Longitudinal distance
• CPC Class Codes: B60W 2554/804 : Relative longitudinal speed
• CPC Class Codes: B60W 2555/20 : Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2555/60 : Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2556/65 : Data transmitted between vehicles
• CPC Class Codes: B60W 2710/18 : Braking system
• CPC Class Codes: B60W 2710/20 : Steering systems
• CPC Class Codes: B60W 2756/10 : Involving external transmission of data to or from the vehicle
• CPC Class Codes: B60W 30/00 : Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
• 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 60/0011 : involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
• CPC Class Codes: B60W 60/0015 : specially adapted for safety
• CPC Class Codes: B60W 60/0016 : of the vehicle or its occupants
• CPC Class Codes: B60W 60/00276 : for two or more other traffic participants
• 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 1/0231 : using optical position detecting means position-fixing by using electromagnetic waves other than radio waves, e.g. optical position detecting means G01S5/16
• 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 1/0257 : 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 1/0268 : using internal positioning means
• CPC Class Codes: G05D 1/0278 : using satellite positioning signals, e.g. GPS
• CPC Class Codes: G05D 1/0285 : using signals transmitted via a public communication network, e.g. GSM network
• CPC Class Codes: G09B 19/167 : Control of land vehicles

Abstract

Among other things, an operation related to control of a vehicle is facilitated by actions that include the following. A finite set of candidate trajectories of the vehicle is generated that begin at a location of the vehicle as of a given time. The candidate trajectories are based on a state of the vehicle and on possible behaviors of the vehicle and of the environment as of the location of the vehicle and the given time. A putative optimal trajectory is selected from among the candidate trajectories based on costs associated with the candidate trajectories. The costs include costs associated with violations of rules of operation of the vehicle. The selected putative optimal trajectory is used to facilitate the operation related to control of the vehicle.

Claims

1. A method comprising

effecting an operation related to control of a vehicle by actions that include:

generating a finite set of candidate trajectories of the vehicle as of a given time, the generating of the finite set comprising applying a model that represents the vehicle'"'"'s expected responses to corresponding control policies for respective candidate trajectories as of the location of the vehicle and the given time,

selecting a putative optimal trajectory from among the candidate trajectories of the finite set based on the corresponding control policies and on costs associated with the candidate trajectories, and

effecting the operation related to control of the vehicle by applying a control policy associated with the selected putative optimal trajectory.

2. The method of claim 1 in which each of the control policies determines at least one of steering, braking, or throttling commands.

3. The method of claim 1 in which the space of possible trajectories of the vehicle is sufficiently covered by the generated finite set of candidate trajectories so that the putative optimal strategy is arbitrarily close to the optimal strategy.

4. The method of claim 1 comprising applying one or more constraints to the finite set of candidate trajectories.

5. The method of claim 1 comprising representing the candidate trajectories as edges of a directed graph.

6. The method of claim 1 comprising monitoring an actual trajectory of the vehicle for a given time period.

7. The method of claim 6 comprising comparing, for the given time period, the actual trajectory of the vehicle with the putative optimal trajectory.

8. The method of claim 1 in which the effecting of an operation related to control of a vehicle comprises monitoring a driver'"'"'s performance.

9. The method of claim 8 comprising reporting a result of the monitoring of the driver'"'"'s performance.

10. The method of claim 8 comprising evaluating the driver'"'"'s performance based on one or more performance metrics.

11. The method of claim 8 comprising assessing the likelihood of an accident occurring.

12. The method of claim 1 in which effecting an operation related to control of a vehicle comprises autonomously driving the vehicle.

13. The method of claim 1 in which the costs associated with a given trajectory are based on costs associated with interactions between the states of the vehicle and states of the environment.

14. The method of claim 1 in which the selected putative optimal trajectory is associated with both speed and direction of the vehicle.

15. The method of claim 1 in which selecting the putative optimal trajectory comprises determining a minimum-cost path through a directed graph of which the candidate trajectories comprise edges.

16. An apparatus comprising

an autonomous vehicle comprising

controllable devices configured to cause the vehicle to traverse at least part of an optimal trajectory in a manner consistent with cost rules,

a controller to provide commands to the controllable devices in accordance with the optimal trajectory, and

a computational element configured to effect, through the controllable devices, an operation related to control of the vehicle, by actions that include:

generating a finite set of candidate trajectories of the vehicle as of a given time, the generating of the finite set comprising applying a model that represents the vehicle'"'"'s expected responses to corresponding control policies for respective candidate trajectories as of the location of the vehicle and the given time,

selecting a putative optimal trajectory from among the candidate trajectories of the finite set based on the corresponding control policies and on costs associated with the candidate trajectories, and

effecting the operation related to control of the vehicle by applying a control policy associated with the optimal trajectory.

17. The method of claim 16 in which each of the control policies determines at least one of steering, braking, or throttling commands.

18. The method of claim 16 in which the space of possible trajectories of the vehicle is sufficiently covered by the generated finite set of candidate trajectories so that the putative optimal strategy is arbitrarily close to the optimal strategy.

19. The method of claim 16 comprising applying one or more constraints to the finite set of candidate trajectories.

20. The method of claim 16 comprising representing the candidate trajectories as edges of a directed graph.

21. The method of claim 16 comprising monitoring an actual trajectory of the vehicle for a given time period.

22. The method of claim 21 comprising comparing, for the given time period, the actual trajectory of the vehicle with the putative optimal trajectory.

23. The method of claim 16 in which the effecting of an operation related to control of a vehicle comprises monitoring a driver'"'"'s performance.

24. The method of claim 23 comprising reporting a result of the monitoring of the driver'"'"'s performance.

25. The method of claim 23 comprising evaluating the driver'"'"'s performance based on one or more performance metrics.

26. The method of claim 23 comprising assessing the likelihood of an accident occurring.

27. The method of claim 16 in which effecting an operation related to control of a vehicle comprises autonomously driving the vehicle.

28. The method of claim 16 in which the costs associated with a given trajectory are based on costs associated with interactions between the states of the vehicle and states of the environment.

29. The method of claim 16 in which the selected putative optimal trajectory is associated with both speed and direction of the vehicle.

30. The method of claim 16 in which selecting the putative optimal trajectory comprises determining a minimum-cost path through a directed graph of which the candidate trajectories comprise edges.