Identifying a stopping place for an autonomous vehicle

• US 10,681,513 B2
• Filed: 10/20/2016
• Issued: 06/09/2020
• Est. Priority Date: 10/20/2016
• Status: Active Grant

• Current Assignee: Motional AD, LLC (Aptiv PLC)
• Original Assignee: nuTonomy, Inc. (Aptiv PLC)
• Inventors: Iagnemma, Karl, Ravichandran, Harshavardhan
• Primary Examiner(s): Anwari, Maceeh
• Application Number:
  US15/298,936
• Publication Number:
  US 20180113456A1
• Time in Patent Office: 1,328 Days
• Field of Search: 701 25
• CPC Class Codes: G06V 20/586 of parking space
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/096811 where the route is computed offboard
• CPC Class Codes: H04W 4/70 Services for machine-to-machine communication [M2M] or machine type communication [MTC]

Abstract

Among other things, stored data is maintained indicative of potential stopping places that are currently feasible stopping places for a vehicle within a region. The potential stopping places are identified as part of static map data for the region. Current signals are received from sensors or one or more other sources current signals representing perceptions of actual conditions at one or more of the potential stopping places. The stored data is updated based on changes in the perceptions of actual conditions. The updated stored data is exposed to a process that selects a stopping place for the vehicle from among the currently feasible stopping places.

Claims

1. A computer-implemented method comprising:

receiving, by one or more processors, static map data for a region, wherein the static map data identifies one or more potential stopping places for a vehicle within the region;

maintaining, by the one or more processors, stored data indicative of one or more currently feasible stopping places for the vehicle within the region, wherein the one or more currently feasible stopping places area subset of the one or more potential stopping places, and wherein at least one potential stopping place of the one or more potential stopping places is determined to be a currently feasible stopping place based on;

an amount of time elapsed since the potential stopping place was determined to be infeasible for parking stopping exceeding a first threshold value,

a reason for the determination that the potential stopping place is infeasible for stopping, and

at least one of a historical level of demand for parking in a vicinity of the potential stopping place being less than a second threshold value or traffic volume in the vicinity of the potential stopping place being less than a third threshold value;

receiving from one or more sensors or one or more other sources current signals representing perceptions of actual conditions at the one or more currently feasible stopping places;

updating, by the one or more processors, the stored data based on the perceptions of actual conditions to include one or more updated currently feasible stopping places; and

exposing, by the one or more processors, the updated stored data to a process that selects a stopping place for the vehicle from among the one or more updated currently feasible stopping places.

2. The method of claim 1 comprising:

discretizing, by the one or more processors, the one or more potential stopping places as a finite number of points within the region.

3. The method of claim 2 comprising:

defining, by the one or more processors, the potential stopping place as a shape containing at least one of the points, the potential stopping place configured to accommodate a footprint of the vehicle.

4. The method of claim 3 comprising:

attributing, by the one or more processors, an orientation to the shape, the orientation corresponding to a direction of traffic flow at the potential stopping place.

5. The method of claim 2 comprising:

initializing, by the one or more processors, the one or more potential stopping places as one or more stopping places expected to be feasible based on prior signals from the one or more sensors, the prior signals representing past perceptions of past actual conditions at some of the one or more potential stopping places.

6. The method of claim 1 in which the one or more sensors comprise at least one sensor that is physically located on the vehicle.

7. The method of claim 1 in which the one or more sensors comprise at least one sensor that is physically remote from the vehicle,

wherein the at least one sensor is located inside a parking garage.

8. The method of claim 1 in which the current signals received from the one or more sensors are received through vehicle-to-vehicle or vehicle-to-infrastructure communication.

9. The method of claim 1 in which the one or more other sources comprise crowd-sourced data sources.

10. The method of claim 1 in which the vehicle is part of a fleet of vehicles managed from a central server and the method comprises the server distributing information received from sensors at one of the vehicles to other vehicles of the fleet.

11. An autonomous vehicle, comprising:

one or more processors;

one or more sensors; and

one or more data storage devices including instructions that when executed by the one or more processors, cause the autonomous vehicle to perform functions comprising;

receiving static map data for a region, wherein the static map data identifies one or more potential stopping places for a vehicle within the region;

maintaining stored data indicative of one or more currently feasible stopping places for the vehicle within the region, wherein the one or more currently feasible stopping places are a subset of the one or more potential stopping places, and wherein a at least one potential stopping place of the one or more potential stopping places is determined to be a currently feasible stopping place based on;

an amount of time elapsed since the potential stopping place was determined to be infeasible for stopping exceeding a first threshold value,

a reason for the determination that the potential stopping place is infeasible for stopping, and

at least one of a historical level of demand for parking in a vicinity of the potential stopping place being less than a second threshold value or traffic volume in the vicinity of the potential stopping place being less than a third threshold value;

receiving from the one or more sensors or one or more other sources current signals representing perceptions of actual conditions at the one or more currently feasible stopping places;

updating the stored data based on the perceptions of actual conditions to include one or more updated currently feasible stopping places; and

exposing the updated stored data to a process that selects a stopping place for the vehicle from among the one or more updated currently feasible stopping places.

12. The autonomous vehicle of claim 11, wherein the functions comprise:

initializing the potential stopping places as all of the potential stopping places identified as part of the static map data for the region.

13. The autonomous vehicle of claim 11, wherein the functions comprise:

discretizing the potential stopping places as a finite number of points within the region corresponding to potential stopping places.

14. The autonomous vehicle of claim 13, wherein the functions comprise:

defining a potential stopping place as a shape containing one of the points, the shape corresponding to a footprint of the vehicle.

15. The autonomous vehicle of claim 14, wherein the functions comprise:

attributing an orientation to the shape, the orientation corresponding to a direction of traffic flow.

16. The autonomous vehicle of claim 13, wherein the functions comprise:

initializing the potential stopping places as potential stopping places expected to be feasible based on prior signals from the one or more sensors representing perceptions of actual conditions at one or more of the potential stopping places.

17. The autonomous vehicle of claim 11 in which the current signals received from the one or more sensors are received through vehicle-to-vehicle or vehicle-to-infrastructure communication.

18. A non-transitory computer readable medium storing instructions thereon that, when executed by one or more processors, cause the one or more processors to perform functions comprising:

receiving static map data for a region, wherein the static map data identifies one or more potential stopping places for a vehicle within the region;

maintaining stored data indicative of one or more currently feasible stopping places for the vehicle within the region, wherein the one or more currently feasible stopping places are a subset of the one or more potential stopping places, and wherein at least one potential stopping place of the one or more potential stopping places determined to be a currently feasible stopping place based on;

an amount of time elapsed since the potential stopping place was determined to be infeasible for stopping exceeding a first threshold value,

a reason for the determination that the potential stopping place is infeasible for stopping, and

at least one of a historical level of demand for parking in a vicinity of the potential stopping place being less than a second threshold value or traffic volume in the vicinity of the potential stopping place being less than a third threshold value;

receiving from one or more sensors or one or more other sources current signals representing perceptions of actual conditions at the one or more currently feasible stopping places;

updating the stored data based on the perceptions of actual conditions to include one or more updated currently feasible stopping places; and

exposing the updated stored data to a process that selects a stopping place for the vehicle from among the one or more updated currently feasible stopping places.