AUTONOMOUS VEHICLE LANE ROUTING AND NAVIGATION

• US 20150345966A1
• Filed: 05/30/2014
• Published: 12/03/2015
• Est. Priority Date: 05/30/2014
• Status: Active Grant

• Current Assignee: Nissan Motor Co., Ltd.
• Original Assignee: Nissan North America Incorporated (Nissan Motor Co., Ltd.)
• Inventors: Meuleau, Nicolas
• Granted Patent: US 9,404,761 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/3453 Special cost functions, i.e. other than distance or default speed limit of road segments
• CPC Class Codes: G01C 21/3469 Fuel consumption; Energy use; Emission aspects
• CPC Class Codes: G01C 21/3658 Lane guidance
• 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: G05D 1/0217 in accordance with energy consumption, time reduction or distance reduction criteria

Abstract

A method and apparatus for autonomous vehicle lane routing and navigation are provided. Autonomous vehicle lane routing and navigation may include identifying vehicle transportation network information including road segment information and lane information, wherein the road segment information for at least one road segment from the plurality of road segments includes lane information representing at least two adjacent lanes, identifying an origin, identifying a destination, generating a plurality of candidate routes from the origin to the destination, wherein each route from the plurality of routes indicates a distinct combination of road segments and lanes, and wherein at least one candidate route from the plurality of candidate routes includes at least one of the adjacent lanes, identifying an optimal route from the plurality of candidate routes, the optimal route having a minimal route cost, and operating 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 vehicle transportation network information, the vehicle transportation network information including road segment information representing a plurality of road segments, the road segment information including lane information representing at least one lane for each respective road segment, wherein the road segment information for at least one road segment from the plurality of road segments includes lane information representing at least two adjacent lanes,

identify an origin,

identify a destination,

generate 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, and wherein at least one candidate route from the plurality of candidate routes includes at least one of the adjacent lanes, and

identify an optimal route from the plurality of candidate routes, the optimal route having a minimal route cost; and

a trajectory controller configured to operate the autonomous vehicle to travel from the origin to the destination using the optimal route.

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

identify the optimal route using a Markov decision process.

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

identify the optimal route using a discrete time stochastic control process.

4. The autonomous vehicle of claim 1, wherein the lane information includes waypoint information representing at least one waypoint for each respective lane, and wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to identify the optimal route by:

identifying a first routing state, the first routing state including an indication of a first road segment, an indication of a first lane associated with the first road segment, and an indication of a first waypoint associated with the first lane;

identifying a second routing state, the second routing state including an indication of a second road segment, an indication of a second lane associated with the second road segment, and an indication of a second waypoint associated with the second lane such that the second waypoint is immediately adjacent to the first waypoint; and

estimating an action cost representing a cost to transition from the first routing state to the second routing state.

5. The autonomous vehicle of claim 4, wherein estimating the action cost includes evaluating at least one of a plurality of cost metrics.

6. The autonomous vehicle of claim 5, wherein the plurality of cost metrics includes at least one of a distance cost metric, a duration cost metric, a fuel cost metric, or an acceptability cost metric.

7. The autonomous vehicle of claim 6, wherein estimating the action cost includes calculating a cost function that is minimizing with respect to the distance cost metric, minimizing with respect to the duration cost metric, minimizing with respect to the fuel cost metric, and maximizing with respect to the acceptability cost metric.

8. The autonomous vehicle of claim 5, wherein estimating the action cost includes identifying a weighting factor associated with each respective cost metric from the plurality of cost metrics.

9. The autonomous vehicle of claim 5, wherein estimating the action cost includes generating a plurality of weighted cost metrics such that each weighted cost metric from the plurality of weighted cost metrics is based on a product of a respective cost metric from the plurality of cost metrics and a weighting factor associated with the respective cost metric.

10. The autonomous vehicle of claim 9, wherein estimating the action cost includes calculating a sum of the plurality of cost weighted metrics.

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

identifying a third routing state, the third routing state including an indication of a third road segment, an indication of a third lane associated with the third road segment, and an indication of a third waypoint associated with the third lane such that the third waypoint is immediately adjacent to the first waypoint; and

estimating an action cost representing a cost to transition from the first routing state to the third routing state.

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

selecting the minimal action cost from among the action cost representing the cost to transition from the first routing state to the second routing state and the action cost representing the cost to transition from the first routing state to the third routing state.

13. The autonomous vehicle of claim 11, wherein the second road segment is the third road segment and the second lane differs from the third lane.

14. The autonomous vehicle of claim 4, further comprising:

a geographic location unit, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to identify the origin by;

controlling the geographic location unit identify a current geographic location of the autonomous vehicle; and

identifying a waypoint from the transportation network information, the waypoint proximal to the current geographic location.

15. The autonomous vehicle of claim 1, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to output or store the optimal route.

16. An autonomous vehicle comprising:

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

identify transportation network information, the transportation network information including road segment information representing a plurality of road segments, the road segment information including lane information representing at least one lane for each respective road segment, the lane information including waypoint information representing at least one waypoint for each respective lane, wherein the road segment information for at least one road segment from the plurality of road segments includes lane information representing at least two adjacent lanes,

identify an origin,

identify a destination,

generate 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, and wherein at least one candidate route from the plurality of candidate routes includes at least one of the adjacent lanes,

for at least one candidate route from the plurality of candidate routes;

identify a first routing state, the first routing state including an indication of a first road segment, an indication of a first lane associated with the first road segment, and an indication of a first waypoint associated with the first lane;

identify a second routing state, the second routing state including an indication of a second road segment, an indication of a second lane associated with the second road segment, and an indication of a second waypoint associated with the second lane such that the second waypoint is immediately adjacent to the first waypoint; and

generate an action cost representing a cost to transition from the first routing state to the second routing state, and

identify an optimal route from the plurality of candidate routes, the optimal route having a minimal route cost; and

a trajectory controller configured to operate the autonomous vehicle to travel from the origin to the destination using the optimal route.

17. The autonomous vehicle of claim 16, wherein estimating the action cost includes evaluating at least one of a distance cost metric, a duration cost metric, a fuel cost metric, or an acceptability cost metric.

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

identify a third routing state, the third routing state including an indication of a third road segment, an indication of a third lane associated with the third road segment, and an indication of a third waypoint associated with the third lane such that the third waypoint is immediately adjacent to the first waypoint; and

generate an action cost representing a cost to transition from the first routing state to the third routing state.

19. The autonomous vehicle of claim 18, wherein the processor is configured to execute instructions stored on the non-transitory computer readable medium to identify the optimal route by:

selecting the minimal action cost from among the action cost representing the cost to transition from the first routing state to the second routing state and the action cost representing the cost to transition from the first routing state to the third routing state.

20. An autonomous vehicle comprising:

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

identify transportation network information, the transportation network information including road segment information representing a plurality of road segments, the road segment information including lane information representing at least one lane for each respective road segment, the lane information including waypoint information representing at least one waypoint for each respective lane, wherein the road segment information for at least one road segment from the plurality of road segments includes lane information representing at least two adjacent lanes,

identify an origin,

identify a destination,

generate 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, and wherein at least one candidate route from the plurality of candidate routes includes at least one of the adjacent lanes,

for at least one candidate route from the plurality of candidate routes;

identify a first routing state, the first routing state including an indication of a first road segment, an indication of a first lane associated with the first road segment, and an indication of a first waypoint associated with the first lane;

identify a second routing state, the second routing state including an indication of a second road segment, an indication of a second lane associated with the second road segment, and an indication of a second waypoint associated with the second lane such that the second waypoint is immediately adjacent to the first waypoint;

identify a third routing state, the third routing state including an indication of a third road segment, an indication of a third lane associated with the third road segment, and an indication of a third waypoint associated with the third lane such that the third waypoint is immediately adjacent to the first waypoint;

generate an action cost representing a cost to transition from the first routing state to the third routing state;

generate an action cost representing a cost to transition from the first routing state to the second routing state; and

select the minimal action cost from among the action cost representing the cost to transition from the first routing state to the second routing state and the action cost representing the cost to transition from the first routing state to the third routing state, and

identify an optimal route from the plurality of candidate routes, the optimal route having a minimal route cost, based at least in part on the minimal action cost; and

a trajectory controller configured to operate the autonomous vehicle to travel from the origin to the destination using the optimal route.