Inferring pickup or drop-off locations using curated data
Aspects of the technology provide a method including receiving a request for a user to be picked up or dropped off by an autonomous vehicle, in which the request identifying a location, and determining a land parcel containing the identified location. The method also includes identifying a set of features that are within a selected distance from the identified location, filtering the set of identified features to obtain only curated features that are within the selected distance from the identified location, determining a distance between each curated feature and the identified location, and inferring an access point for the identified location based on the distances determined between each curated feature and the identified location. The inferred access point can then be provided to enable the autonomous vehicle to perform a pickup or drop-off.
1. A computer-implemented method comprising:
receiving a request for a user to be picked up or dropped off by an autonomous vehicle, the request identifying a location;
determining, by one or more processors, a land parcel containing the identified location based on parcel information that is derived from a first map data source;
identifying, by the one or more processors, a set of features within the determined land parcel that are within a selected distance from the identified location;
filtering, by the one or more processors, the set of identified features to obtain curated features that are: (1) within the selected distance from the identified location, and (2) within the determined land parcel;
determining, by the one or more processors, a distance between each curated feature and the identified location;
inferring, by the one or more processors, an access point for the identified location based on the distances determined between each curated feature and the identified location;
determining, by the one or more processors, whether the inferred access point satisfies a criterion;
when the inferred access point is determined to satisfy the criterion, providing the inferred access point to enable the autonomous vehicle to perform a pickup or drop-off; and
when the inferred access point is determined not to satisfy the criterion, using a feature of the set of identified features that is determined to be nearest to an estimated location of the user as the inferred access point to enable the autonomous vehicle to perform the pickup or drop-off.
2. The method of claim 1 , wherein each curated feature is associated with a corresponding roadgraph feature.
3. The method of claim 2 , wherein the curated features are derived from a second map data source, and the corresponding roadgraph feature is derived from the first map data source which is distinct from the second map data source.
4. The method of claim 1 , wherein the curated features include one or more of:
a specific building in a multi-building complex, a residential driveway, a loading zone, a preferred pullover zone, an unmapped region driveway, a special designation parking space, a mailbox location, a seating spot, a covered parking area, or a designated walking path.
5. The method of claim 1 , wherein inferring the access point is further based on at least one of an estimated walking time or a walking cost.
6. The method of claim 1 , wherein the selected distance is a radius around the identified location.
7. The method of claim 1 , wherein
the request identifying the location is associated with roadgraph information derived from a second map data source that is distinct from the first map data source.
8. The method of claim 1 , wherein when the identified location is an indoor location, the method further includes identifying at which indoor space of the determined land parcel the user is located.
9. The method of claim 1 , wherein when the inferred access point is determined not to satisfy the criterion, the method further comprises:
identifying distances to a set of roadgraph features from the estimated location of the user,
determining a nearest roadgraph feature of the set of roadgraph features, and
selecting the nearest roadgraph feature for use as the inferred access point.
10. The method of claim 1 , wherein the identified location is a roadgraph feature obtained from a set of roadgraph data.
11. The method of claim 10 , wherein the roadgraph feature is a driveway segment or a parking lot segment.
12. The method of claim 1 , wherein when the location is associated with a pickup of a rider by the autonomous vehicle, the filtering the set of identified features to obtain only curated features that are within the selected distance from the identified location further includes discarding identified features that do not support a selected wait time for the autonomous vehicle to park.
13. The method of claim 1 , wherein when the location is associated with a delivery of a package by the autonomous vehicle, the filtering the set of identified features to obtain only curated features that are within the selected distance from the identified location further includes discarding identified features that do not support a selected wait time for the autonomous vehicle to park.
14. A computing system, comprising:
memory configured to store sets of digital map information for locations of interest; and
one or more processors operatively coupled to the memory, the one or more processors being configured to:
receive a request for a user to be picked up or dropped off by an autonomous vehicle, the request identifying a location;
determine a land parcel containing the identified location based on parcel information that is derived from a first map data source;
identify a set of features within the determined land parcel that are within a selected distance from the identified location;
filter the set of identified features to obtain curated features that are: (1) within the selected distance from the identified location, and (2) within the determined land parcel;
determine a distance between each curated feature and the identified location;
infer an access point for the identified location based on the distances determined between each curated feature and the identified location;
determine whether the inferred access point satisfies a criterion;
when the inferred access point is determined to satisfy the criterion, provide the inferred access point in order to enable the autonomous vehicle to perform a pickup or drop-off; and
when the inferred access point is determined not to satisfy the criterion, use a feature of the set of identified features that is determined to be nearest to an estimated location of the user as the inferred access point to enable the autonomous vehicle to perform the pickup or drop-off.
15. The computing system of claim 14 , wherein each curated feature is associated with a corresponding roadgraph feature.
16. The computing system of claim 15 , wherein the curated features are derived from a second map data source, and the corresponding roadgraph feature is derived from the first map data source which is distinct from the second map data source.
17. The computing system of claim 14 , wherein
the request identifying the location is associated with roadgraph information derived from a second map data source that is distinct from the first map data source.
18. The computing system of claim 14 , wherein when the inferred access point is determined not to satisfy the criterion, the one or more processors are configured to:
identify distances to a set of roadgraph features from the estimated location of the user,
determine a nearest roadgraph feature of the set of roadgraph features, and
select the nearest roadgraph feature for use as the inferred access point.
19. The computing system of claim 14 , wherein the identified location is a roadgraph feature obtained from a set of roadgraph data.