Marker aided autonomous vehicle localization

• US 9,541,409 B2
• Filed: 12/18/2014
• Issued: 01/10/2017
• Est. Priority Date: 12/18/2014
• Status: Active Grant

• Current Assignee: Nissan Motor Co., Ltd.
• Original Assignee: Nissan North America Incorporated (Nissan Motor Co., Ltd.)
• Inventors: Penna, Mauro Della, Kojo, Naoki
• Primary Examiner(s): Edwards, Jerrah
• Assistant Examiner(s): ALSOMIRI, MAJDI A
• Application Number:
  US14/575,008
• Publication Number:
  US 20160178382A1
• Time in Patent Office: 754 Days
• Field of Search: 701/25
• US Class Current: 1/1
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• CPC Class Codes: G01C 21/34 Route searching; Route guidance
• CPC Class Codes: G05D 1/0234 using optical markers or beacons optical beacons per se G01S1/70
• CPC Class Codes: G05D 1/0255 using acoustic signals, e.g. ultra-sonic singals sonar systems designed for anti-collision purposes G01S15/93
• CPC Class Codes: G05D 1/0272 comprising means for registering the travel distance, e.g. revolutions of wheels measuring distance traversed on the ground by vehicles, e.g. using odometers G01C22/00
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G05D 1/0278 using satellite positioning signals, e.g. GPS

Abstract

A method and apparatus for marker aided autonomous vehicle localization are disclosed. Marker aided autonomous vehicle localization may include an autonomous vehicle identifying transportation network information, identifying an origin, identifying a destination, generating a plurality of candidate routes from the origin to the destination based on the transportation network information, wherein each route from the plurality of routes indicates a distinct combination of road segments and lanes, generating an action cost probability distribution for each action in each candidate route, generating a route cost probability distribution based at least in part on the action cost probability distribution, identify an optimal route from the plurality of candidate routes based at least in part on the route cost probability distribution, and operate the autonomous vehicle to travel from the origin to the destination using the optimal route.

Claims

1. An autonomous vehicle comprising:

a processor configured to execute instructions stored on a non-transitory computer readable medium to;

identify transportation network information representing a vehicle transportation network,

identify a route from an origin to a destination in the vehicle transportation network using the transportation network information; and

a trajectory controller configured to operate the autonomous vehicle to travel from the origin to the destination using the route, wherein the processor is configured to;

detect an uncoded localization marker in the vehicle transportation network,

determine localization marker information indicating a location of the uncoded localization marker in the vehicle transportation network based on the transportation network information and an identified location of the autonomous vehicle in the vehicle transportation network,

generate first localization information indicating an orientation and a position of the autonomous vehicle relative to the uncoded localization marker in response to detecting the uncoded localization marker, and

generate second localization information indicating a current location of the autonomous vehicle in the vehicle transportation network based on the first localization information and the localization marker information, wherein the trajectory controller is configured to operate the autonomous vehicle to travel from the current location to the destination in response to generating the second localization information.

2. The autonomous vehicle of claim 1, wherein the transportation network information includes the localization marker information.

3. The autonomous vehicle of claim 1, wherein the uncoded localization marker is one of a plurality of sparsely located uncoded localization markers in a partially navigable portion of the vehicle transportation network, wherein each uncoded localization marker from the plurality of sparsely located uncoded localization markers is an instance of an invariant localization marker design.

4. The autonomous vehicle of claim 3, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

determine the identified location of the autonomous vehicle in the vehicle transportation network by generating third localization information indicating an estimated location of the autonomous vehicle within the partially navigable portion of the vehicle transportation network using odometry; and

determine the localization marker information by identifying the uncoded localization marker from the plurality of sparsely located uncoded localization markers based on the third localization information.

5. The autonomous vehicle of claim 1, further comprising:

a sensor configured to detect the uncoded localization marker on a condition that the uncoded localization marker is within an area proximate to the autonomous vehicle, and wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to detect the uncoded localization marker by;

controlling the sensor to monitor the area proximate to the autonomous vehicle in response to determining that the autonomous vehicle is proximal to a partially navigable portion of the vehicle transportation network, and

receiving information from the sensor indicating the detected uncoded localization marker.

6. The autonomous vehicle of claim 5, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

determine that the autonomous vehicle is proximal to the partially navigable portion of the vehicle transportation network on a condition that an accurate localization signal is unavailable, the transportation network information omits an accurate representation of a portion of the vehicle transportation network proximal to the autonomous vehicle, the transportation network information includes a partially navigable status indication for a portion of the vehicle transportation network proximal to the autonomous vehicle, or the transportation network information indicates that the uncoded localization marker is proximal to the autonomous vehicle.

7. The autonomous vehicle of claim 5, wherein the partially navigable portion of the vehicle transportation network is a parking area.

8. The autonomous vehicle of claim 5, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

detect the uncoded localization marker at an entrance to the partially navigable portion of the vehicle transportation network.

9. The autonomous vehicle of claim 5, wherein the partially navigable portion of the vehicle transportation network includes an entrance portion and an interior portion, and wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

detect the uncoded localization marker in the interior portion.

10. The autonomous vehicle of claim 1, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

detect the uncoded localization marker on a road surface.

11. The autonomous vehicle of claim 1, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

detect the uncoded localization marker by detecting a two dimensional symbol.

12. An autonomous vehicle comprising:

a processor configured to execute instructions stored on a non-transitory computer readable medium to;

identify transportation network information representing a vehicle transportation network, the vehicle transportation network including a partially navigable portion, the partially navigable portion including a plurality of sparsely located uncoded localization markers, wherein each uncoded localization marker from the plurality of sparsely located uncoded localization markers is an instance of an invariant localization marker design, the transportation network information including localization marker information for each respective uncoded localization marker from the plurality of sparsely located uncoded localization markers, wherein the location information indicates a respective location of the respective uncoded localization marker in the vehicle transportation network,

identify a route from an origin to a destination in the vehicle transportation network using the transportation network information, wherein the route includes at least a part of the partially navigable portion of the vehicle transportation network; and

a trajectory controller configured to operate the autonomous vehicle to travel from the origin to the destination using the route, wherein the processor is configured to;

detect a first uncoded localization marker from the plurality of sparsely located uncoded localization markers in the vehicle transportation network,

generate first localization information indicating an orientation and a position of the autonomous vehicle relative to the first uncoded localization marker in response to detecting the first uncoded localization marker, and

generate second localization information indicating a current location of the autonomous vehicle in the vehicle transportation network based on the first localization information and localization marker information corresponding to the first uncoded localization marker, the localization marker information indicating a location of the uncoded localization marker in the vehicle transportation network, wherein the trajectory controller is configured to operate the autonomous vehicle to travel from the current location to the destination in response to generating the second localization information.

13. The autonomous vehicle of claim 12, further comprising:

a sensor configured to detect the first uncoded localization marker on a condition that the first uncoded localization marker is within an area proximate to the autonomous vehicle, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to detect the first uncoded localization marker by;

controlling the sensor to monitor the area proximate to the autonomous vehicle in response to determining that the autonomous vehicle is proximal to the partially navigable portion of the vehicle transportation network, and

receiving information from the sensor indicating the detected first uncoded localization marker.

14. The autonomous vehicle of claim 12, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

determine that the autonomous vehicle is proximal to the partially navigable portion of the vehicle transportation network on a condition that an accurate localization signal is unavailable, the transportation network information omits an accurate representation of a portion of the vehicle transportation network proximal to the autonomous vehicle, the transportation network information includes a partially navigable status indication for a portion of the vehicle transportation network proximal to the autonomous vehicle, or the transportation network information indicates that at least one of the plurality of sparsely located uncoded localization markers is proximal to the autonomous vehicle.

15. The autonomous vehicle of claim 12, wherein the partially navigable portion of the vehicle transportation network is a parking area.

16. The autonomous vehicle of claim 12, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

detect the first uncoded localization marker by detecting a two dimensional symbol on a road surface.

17. The autonomous vehicle of claim 12, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to:

determine the identified location of the autonomous vehicle in the vehicle transportation network by generating third localization information indicating an estimated location of the autonomous vehicle within the partially navigable portion of the vehicle transportation network using odometry; and

determine the localization marker information by identifying the uncoded localization marker from the plurality of sparsely located uncoded localization markers based on the third localization information.

18. An autonomous vehicle comprising:

a processor configured to execute instructions stored on a non-transitory computer readable medium to;

identify transportation network information representing a vehicle transportation network, the vehicle transportation network including a partially navigable portion, the partially navigable portion including a plurality of sparsely located uncoded localization markers, wherein each uncoded localization marker from the plurality of sparsely located uncoded localization markers is an instance of an invariant localization marker design, the transportation network information including localization marker information for each respective uncoded localization marker from the plurality of sparsely located uncoded localization markers, wherein the location information indicates a respective location of the respective uncoded localization marker in the vehicle transportation network,

identify a route from an origin to a destination in the vehicle transportation network using the transportation network information, wherein the route includes at least a part of the partially navigable portion of the vehicle transportation network; and

a trajectory controller configured to operate the autonomous vehicle to travel from the origin to the destination using the route, wherein the processor is configured to;

generate first localization information indicating an estimated location of the autonomous vehicle within the partially navigable portion of the vehicle transportation network using odometry,

detect a first uncoded localization marker from the plurality of sparsely located uncoded localization markers,

generate second localization information indicating an orientation and a position of the autonomous vehicle relative to the first uncoded localization marker in response to detecting the first uncoded localization marker,

determine localization marker information corresponding to the first uncoded localization marker, wherein determining the localization marker information includes identifying the first uncoded localization marker from the plurality of sparsely located uncoded localization markers based on the first localization information, and

generate third localization information identifying a current location of the autonomous vehicle in the vehicle transportation network based on the second localization information and the localization marker information, wherein the trajectory controller is configured to operate the autonomous vehicle to travel from the current location to the destination in response to generating the third localization information.

19. The autonomous vehicle of claim 18, further comprising:

a sensor configured to detect the first uncoded localization marker on a condition that the first uncoded localization marker is within an area proximate to the autonomous vehicle, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to;

determine that the autonomous vehicle is proximal to the partially navigable portion of the vehicle transportation network on a condition that an accurate localization signal is unavailable, the transportation network information omits an accurate representation of a portion of the vehicle transportation network proximal to the autonomous vehicle, the transportation network information includes a partially navigable status indication for a portion of the vehicle transportation network proximal to the autonomous vehicle, or the transportation network information indicates that the first uncoded localization marker is proximal to the autonomous vehicle; and

detect the first uncoded localization marker by;

controlling the sensor to monitor the area proximate to the autonomous vehicle in response to determining that the autonomous vehicle is proximal to the partially navigable portion of the vehicle transportation network, and

receiving information from the sensor indicating the detected first uncoded localization marker.