PROCESSING A REQUEST SIGNAL REGARDING OPERATION OF AN AUTONOMOUS VEHICLE

• US 20180281796A1
• Filed: 04/03/2017
• Published: 10/04/2018
• Est. Priority Date: 04/03/2017
• Status: Active Grant

• Current Assignee: Motional AD, LLC (Aptiv PLC)
• Original Assignee: nuTonomy, Inc. (Aptiv PLC)
• Inventors: Ravichandran, Harshavardhan, Iagnemma, Karl, Wolff, Eric
• Granted Patent: US 10,850,734 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2556/55 using telemetry
• CPC Class Codes: B60W 30/181 Preparing for stopping
• CPC Class Codes: B60W 40/04 Traffic conditions
• CPC Class Codes: B60W 50/0097 Predicting future conditions
• CPC Class Codes: B60W 50/0098 Details of control systems ensuring comfort, safety or stability not otherwise provided for
• CPC Class Codes: B60W 50/038 Limiting the input power, torque or speed
• CPC Class Codes: B60W 50/08 Interaction between the driver and the control system
• CPC Class Codes: B60W 50/10 Interpretation of driver requests or demands

Abstract

Among other things, a vehicle drives autonomously on a trajectory through a road network to a goal location based on an automatic process for planning the trajectory without human intervention; and an automatic process alters the planning of the trajectory to reach a target location based on a request received from an occupant of the vehicle to engage in a speed-reducing maneuver.

Claims

1. A method comprising

causing a vehicle to drive autonomously on a trajectory through a road network to a goal location based on an automatic process for planning the trajectory without human intervention, and

causing the automatic process to alter the planning of the trajectory to reach a target location based on a request received from an occupant of the vehicle to engage in a speed-reducing maneuver.

2. The method of claim 1, in which the target location comprises a target stopping place.

3. The method of claim 1, in which the speed-reducing maneuver comprises stopping the vehicle.

4. The method of claim 1, in which the request comprises data received from a user interface in the vehicle as a result of an interaction by the occupant, and the user interface comprises a button, a switch, a pull-cord, a pedal, a pad, a sensor, a whistle, a display, or a voice assistant, or a combination of two or more of them.

5. The method of claim 4, in which the data comprises a degree of urgency.

6. The method of claim 5, comprising inferring the degree of urgency by an algorithmic analysis of the request.

7. The method of claim 6, in which the algorithmic analysis comprises analysis of a frequency, a volume, a sound, a voice, or a type, or two or more of them, of an oral request.

8. The method of claim 4, in which the data comprises an expected stopping time interval.

9. The method of claim 8, in which the expected stopping time interval has been indicated by the occupant.

10. The method of claim 8, comprising inferring the expected stopping time interval by an algorithmic analysis on the request.

11. The method of claim 1, comprising analyzing additional data comprising traffic data, sensor data, or map data, or two or more of them.

12. The method of claim 11, in which analyzing the additional data comprises evaluating quality of one or more target locations.

13. The method of claim 12, in which the quality is evaluated offline relative to the vehicle.

14. The method of claim 12, in which the quality is evaluated online when the vehicle is driving.

15. The method of claim 12, in which evaluating the quality comprises computing a quality based on one or more of the following factors:

an emergency condition, a location of the vehicle on the road network, a traffic speed, a traffic volume, a traffic composition, a lane choice, a blockage degree, a sightline from another vehicle, a distance from an intersection, presence of a dedicated lane, terrain, and a road slope.

16. The method of claim 15, in which one or more of the factors are represented by numerical values.

17. The method of claim 16, in which each of the numerical values is mapped to a pre-defined range.

18. The method of claim 15, in which computing the quality comprises assigning weights to one or more of the factors.

19. The method of claim 18, in which the weights are based on one or more of the following:

features of the request, a type of the vehicle, a regulation, a degree of urgency, and an expected stopping time interval.

20. The method of claim 12, comprising ignoring a target location based on its quality or information specifying its exclusion.

21. The method of claim 12, comprising classifying target locations in quality categories.

22. The method of claim 12, in which analyzing the additional data comprises applying a minimum quality threshold to identify one or more acceptable target locations.

23. The method of claim 22, comprising computing the minimum quality threshold based on one or more of the following:

a degree of urgency, an expected stopping time interval, and a conflicting rule.

24. The method of claim 1, comprising identifying a region potentially comprising a target location.

25. The method of claim 24, in which the region comprises a drivable area or a non-drivable area or both.

26. The method of claim 24, in which the region comprises an area faced by a forward-facing side of the vehicle.

27. The method of claim 24, in which the region comprises a shape or a size or both.

28. The method of claim 27, comprising determining the shape or the size based on a traffic condition or on a degree of urgency or on both.

29. The method of claim 24, comprising determining the region based on qualities of one or more target locations.

30. The method of claim 24, comprising expanding the region when no target location is identified.

31. The method of claim 24, comprising updating the region based on a new location of the vehicle.

32. The method of claim 24, comprising choosing a target location in the region by discretizing the region into potential target places.

33. The method of claim 24, comprising choosing a target location by using availability data.

34. The method of claim 33, comprising acquiring the availability data from one or more of the following:

a crowd-sourced database, a sensor, a perception process, a historical database, a parking lot database, a parking space database, the vehicle, and another vehicle.