Route planning for an autonomous vehicle

• US 10,126,136 B2
• Filed: 06/14/2016
• Issued: 11/13/2018
• Est. Priority Date: 06/14/2016
• Status: Active Grant

• Current Assignee: Motional AD, LLC (Aptiv PLC)
• Original Assignee: nuTonomy, Inc. (BorgWarner Incorporated)
• Inventors: Iagnemma, Karl
• Primary Examiner(s): Sweeney, Brian P
• Application Number:
  US15/182,360
• Publication Number:
  US 20170356747A1
• Time in Patent Office: 882 Days
• Field of Search: 701 25
• CPC Class Codes: G01C 21/34 Route searching; Route guidance
• CPC Class Codes: G01C 21/3461 Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
• 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: H05K 999/99 dummy group

Abstract

Among other things, a determination is made of an ability of an autonomous vehicle to safely or robustly travel a road feature or a road segment or a route that is being considered for the autonomous vehicle as of a time or range of times. Route root conforms to properties of stored road network information. The road feature or road segment or route is eliminated from consideration if the computer has determined that the road feature or road segment or route cannot be safely or robustly traveled by the autonomous vehicle. The determination by the computer is based on properties of the environment in which the autonomous vehicle travels.

Claims

1. A method for causing safe or robust travel of an autonomous vehicle, the method comprising

receiving signals from a sensor of the autonomous vehicle, the signals representing a sensed aspect of an environment in which the autonomous vehicle is to travel,

by computer determining an ability of the autonomous vehicle to safely or robustly travel a road feature or a road segment or a route that is being considered for the travel of the autonomous vehicle as of a time or range of times, the road feature or road segment or route conforming to properties of stored road network information

eliminating the road feature or road segment or route from consideration if the computer has determined that the road feature or road segment or route cannot be safely or robustly traveled by the autonomous vehicle,

the determining of the ability of the autonomous vehicle to safely or robustly travel the road feature or road segment or route being based on properties of the environment in which the autonomous vehicle travels,

the determining of the ability of the autonomous vehicle to safely or robustly travel the road feature or road segment or route based on an actual or estimated level of performance of the sensor with respect to the properties of the environment, and

sending signals to cause the autonomous vehicle to travel and to avoid the road feature or road segment or route while traveling.

2. The method of claim 1 in which the environment comprises road features.

3. The method of claim 1 in which the properties of the environment comprise navigability by the autonomous vehicle.

4. The method of claim 1 in which the properties of the environment comprise spatial characteristics of road features.

5. The method of claim 4 in which the spatial characteristics comprise aspects of intersections, roundabouts, or junctions.

6. The method of claim 1 in which the properties of the environment comprise connectivity characteristics of road features.

7. The method of claim 6 in which the connectivity characteristics comprise aspects of intersections, roundabouts, or junctions.

8. The method of claim 1 in which the properties of the environment comprise spatial orientations of road features.

9. The method of claim 1 in which the properties of the environment comprise locations of road work or traffic accidents.

10. The method of claim 1 in which the properties of the environment comprise the road surface roughness of road features.

11. The method of claim 1 in which the properties of the environment comprise curvature or slope that affect visibility.

12. The method of claim 1 in which the properties of the environment comprise characteristics of markings of road features.

13. The method of claim 1 in which the properties of the environment comprise physical navigation challenges of road features associated with inclement weather.

14. The method of claim 1 in which the computer determines an ability of the autonomous vehicle to safely or robustly travel each of a set of road features or road segments or routes.

15. The method of claim 1 in which the computer determines the ability of the autonomous vehicle as of a given time.

16. The method of claim 1 in which the route is one of two or more candidate routes determined by a route planning process.

17. The method of claim 1 in which the ability of the autonomous vehicle to safely or robustly travel a road feature or a road segment or a route depends on characteristics of software processes.

18. The method of claim 17 in which the software processes comprise processing of data from sensors on the vehicle.

19. The method of claim 17 in which the software processes comprise motion planning.

20. The method of claim 17 in which the software processes comprise decision-making.

21. The method of claim 17 in which the software processes comprise vehicle motion control.

22. The method of claim 17 in which the characteristics comprise an actual or estimated level of performance as a function of current or predicted future conditions.

23. The method of claim 1 in which the detection property of the sensor comprises the reaction time of the sensor to a change in the aspect of the environment.

24. The method of claim 23 in which the detection property of the sensor comprises the reaction time of the sensor relative to a characteristic of the travel of the autonomous vehicle.

25. The method of claim 24 in which the characteristic of the travel of the autonomous vehicle comprises a speed of the autonomous vehicle.

26. The method of claim 23 in which the change in the aspect of the environment comprises a motion of another vehicle or object.

27. The method of claim 1 in which the properties of the environment comprise road roughness.

28. The method of claim 1 in which the properties of the environment comprise aspects contributing to poor visibility.

29. The method of claim 1 in which the properties of the environment comprise flawed markings, signage, or signals.

30. A method for causing safe or robust travel of an autonomous vehicle, the method comprising

receiving a signal from a motion-planning, decision-making, or motion-control process representing a trajectory for travel of the autonomous vehicle, a decision about a short-term course of action for travel of the autonomous vehicle, or control inputs for driving functions of the autonomous vehicle,

by computer, determining an ability of the autonomous vehicle to safely or robustly travel a road feature or a road segment or a route that is being considered for the travel of the autonomous vehicle as of a time or range of times, the road feature or road segment or route conforming to properties of stored road network information,

eliminating the road feature or road segment or route from consideration if the computer has determined that the road feature or road segment or route cannot be safely or robustly traveled by the autonomous vehicle,

the determining of the ability of the autonomous vehicle to safely or robustly travel the road feature or road segment or route being based on a capability of the motion-planning, decision-making, or motion-control process with respect to the trajectory, decision, or control inputs, and

sending signals to cause the autonomous vehicle, based on the trajectory, decision, or control inputs, to travel and to avoid the road feature or road segment or route while traveling.

31. The method of claim 30 in which the capability of the motion-planning, decision-making, or motion-control process with respect to the trajectory, decision, or control inputs comprises a performance characteristic.

32. The method of claim 30 in which the capability comprises a limitation.

33. The method of claim 30 in which the capability is based on knowledge of the process design or observed performance and simulation or experimental testing of the process.

34. The method of claim 30 in which the road feature, road segment, or route comprises connectivity characteristics.

35. The method of claim 34 in which the connectivity characteristics comprise aspects of intersections, roundabouts, or junctions.