ASSOCIATING PASSENGER DOCKING LOCATIONS WITH DESTINATIONS USING VEHICLE TRANSPORTATION NETWORK PARTITIONING
First Claim
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, the vehicle transportation network including a primary destination, wherein identifying the transportation network information includes identifying the transportation network information such that the transportation network information includes docking location information representing a plurality of docking locations, wherein each docking location from the plurality of docking locations corresponds with a respective location in the vehicle transportation network, and such that at least one docking location from the plurality of docking locations is associated with the primary destination based on pedestrian travel time,determine a target docking location from the plurality of docking locations for the primary destination based on the transportation network information, andidentify a route from an origin to the target docking location 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 target docking location using the route.
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Accused Products
Abstract
A method and apparatus for associating passenger docking locations with destinations using vehicle transportation network partitioning are disclosed. Associating passenger docking locations with destinations using vehicle transportation network partitioning may include an autonomous vehicle identifying transportation network information representing a vehicle transportation network, the vehicle transportation network including a primary destination, wherein identifying the transportation network information includes identifying the transportation network information such that it includes docking location information representing a plurality of docking locations, wherein each docking location corresponds with a respective location in the vehicle transportation network, such that at least one docking location is associated with the primary destination based on pedestrian travel time, determining a target docking location, identifying a route from an origin to the target docking location in the vehicle transportation network using the transportation network information, and traveling from the origin to the target docking location using the route.
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Citations
25 Claims
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1. An autonomous vehicle comprising:
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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 primary destination, wherein identifying the transportation network information includes identifying the transportation network information such that the transportation network information includes docking location information representing a plurality of docking locations, wherein each docking location from the plurality of docking locations corresponds with a respective location in the vehicle transportation network, and such that at least one docking location from the plurality of docking locations is associated with the primary destination based on pedestrian travel time, determine a target docking location from the plurality of docking locations for the primary destination based on the transportation network information, and identify a route from an origin to the target docking location 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 target docking location using the route. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. An autonomous vehicle comprising:
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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 primary destination, wherein identifying the transportation network information includes identifying the transportation network information such that the transportation network information includes docking location information representing a plurality of docking locations, wherein each docking location from the plurality of docking locations corresponds with a respective location in the vehicle transportation network, and road segment information representing a plurality of road segments in the vehicle transportation network, and such that a target docking location from the plurality of docking locations is associated with the primary destination based on pedestrian travel time, wherein the target docking location is associated with the primary destination based on pedestrian travel time by; associating each docking location from the plurality of docking locations with a respective road segment from the plurality of road segments; identifying a plurality of docking location clusters within respective road segments from the plurality of road segments, wherein each docking location cluster from the plurality of docking location clusters includes at least one docking location from the plurality of docking locations; identifying a plurality of docking location cluster medians, wherein each docking location cluster median form the plurality of docking location cluster medians indicates a median of a respective docking location cluster from the plurality of docking location clusters; and partitioning the vehicle transportation network to generate the plurality of vehicle transportation network regions based on the plurality of docking location cluster medians such that each vehicle transportation network region from the plurality of vehicle transportation network regions includes a docking location cluster median, and such that each vehicle transportation network region from the plurality of vehicle transportation network regions includes a plurality of location points from the vehicle transportation network, wherein a respective estimated pedestrian travel time between each location point from the plurality of location points and the docking location cluster median associated with the vehicle transportation network region is within the respective estimated pedestrian travel time between the location point and each docking location cluster median from the plurality of docking location cluster medians, determine whether to use the target docking location based on the transportation network information, and identify a route from an origin to the target docking location 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 target docking location using the route. - View Dependent Claims (17, 18, 19, 20, 21, 22)
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23. An autonomous vehicle comprising:
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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 primary destination, wherein identifying the transportation network information includes identifying the transportation network information such that the transportation network information includes docking location information representing a plurality of docking locations and road segment information representing a plurality of road segments, wherein each docking location from the plurality of docking locations corresponds with a respective location in the vehicle transportation network, and such that a docking location from the plurality of docking locations is associated with the primary destination based on pedestrian travel time, wherein the target docking location is associated with the primary destination based on pedestrian travel time by; associating each docking location from the plurality of docking locations with a respective road segment from the plurality of road segments; identifying a plurality of docking location clusters within respective road segments from the plurality of road segments, wherein each docking location cluster from the plurality of docking location clusters includes at least one docking location from the plurality of docking locations; identifying a plurality of docking location cluster medians, wherein each docking location cluster median form the plurality of docking location cluster medians indicates a median of a respective docking location cluster from the plurality of docking location clusters; partitioning the vehicle transportation network to generate the plurality of vehicle transportation network regions based on the plurality of docking location cluster medians such that each vehicle transportation network region from the plurality of vehicle transportation network regions includes a docking location cluster median from the plurality of docking location cluster medians, and such that each vehicle transportation network region from the plurality of vehicle transportation network regions includes a plurality of location points from the vehicle transportation network, wherein a respective estimated pedestrian travel time between each location point from the respective plurality of location points and the docking location cluster median associated with the vehicle transportation network region is within the respective estimated pedestrian travel time between the location point and each respective docking location cluster median from the plurality of docking location cluster medians; identifying a defined entrance location in the vehicle transportation network as the primary destination location, on a condition that the transportation network information includes entrance location information identifying the defined entrance location; generating a predicted entrance location as the primary destination location, on a condition that the transportation network information omits entrance location information identifying the defined entrance location, wherein generating the predicted entrance location includes; identifying a set of road segments from the plurality of road segments, wherein each road segment from the set of road segments is proximal to the primary destination, generating a set of lines, wherein each line from the set of lines is perpendicular to a road segment from the set of road segments and intersects with the primary destination, and identifying candidate predicted entrance locations, wherein each candidate predicted entrance location indicates an intersection of a line from the set of lines with a road segment from the set of road segments, wherein, on a condition that generating the predicted entrance location includes identifying a plurality of candidate predicted entrance locations, generating the predicted entrance location includes, for each docking location cluster median in the vehicle transportation network region that includes the primary destination, ordering the plurality of candidate predicted entrance locations based on pedestrian travel time between the docking location cluster median and the respective predicted entrance location; and associating the primary destination location with a docking location cluster median from the vehicle transportation network region, determine whether to use the target docking location based on the transportation network information, and identify a route from an origin to the target docking location 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 target docking location using the route. - View Dependent Claims (24, 25)
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Specification