Low quality pose

1. An autonomous vehicle comprising:

a vehicle computing system comprising one or more processors, wherein the vehicle computing system is configured to:

receive map data associated with a map of a geographic location, the map comprising a plurality of submaps where an autonomous vehicle can travel, the plurality of submaps comprising one or more roadways;

obtain position estimate data associated with a position estimate of the autonomous vehicle in the geographic location;

determine a route of the autonomous vehicle including a subset of submaps in the plurality of submaps;

determine a first submap in the subset of submaps of the route closest to the position estimate of the autonomous vehicle;

determine a second submap outside the subset of submaps of the route closest to the position estimate of the autonomous vehicle;

determine a distance between the position estimate of the autonomous vehicle and a submap associated with a prior pose of the autonomous vehicle;

determine a vehicle pose relative to the first submap or the second submap based on the distance; and

control travel of the autonomous vehicle based on the vehicle pose.

2. The autonomous vehicle of claim 1 , wherein the vehicle computing system, when determining the vehicle pose relative to the first submap or the second submap, is further configured to:

determine that the first submap satisfies a threshold based on the distance between the position estimate of the autonomous vehicle and the submap associated with the prior pose;

determine a projection point associated with the first submap; and

determine a vehicle pose in the first submap based on the position estimate data and the projection point.

3. The autonomous vehicle of claim 2 , wherein the vehicle computing system, when determining a pose of the autonomous vehicle in the first submap, is further configured to:

determine a roadway segment including the vehicle pose in the first submap based on the map data where the autonomous vehicle can travel under a non-autonomous mode.

4. The autonomous vehicle of claim 1 , wherein the vehicle computing system, when determining the vehicle pose relative to a submap, is further configured to:

determine that the first submap does not satisfy a threshold based on the distance between the position estimate of the autonomous vehicle and the submap associated with the prior pose; and

in response to determining the first submap does not satisfy the threshold:

determine a projection point associated with the second submap; and

determine a vehicle pose in the second submap based on the position estimate data and the projection point.

5. The autonomous vehicle of claim 1 , wherein determining a distance between the position estimate of the autonomous vehicle and a submap associated with a prior vehicle pose of the autonomous vehicle is based on at least one or more of the following:

a number of transitions of the autonomous vehicle between submaps;

a distance of a route between the position estimate of the autonomous vehicle and the submap associated with the prior vehicle pose; and

a centroid of a submap associated with the prior vehicle pose.

6. The autonomous vehicle of claim 1 , wherein the vehicle computing system is further configured to determine orientation information based on map data associated with one or more transitions between a submap associated with the prior pose of the autonomous vehicle and a submap of the vehicle pose of the autonomous vehicle.

7. The autonomous vehicle of claim 6 , wherein:

the orientation information is associated with an indication of a travel direction for the autonomous vehicle in the submap; and

the vehicle pose is non-viable when a submap of the vehicle pose has a travel direction that is different than a prior travel direction of the autonomous vehicle.

8. The autonomous vehicle of claim 1 , wherein the position estimate data includes at least one of latitude, longitude and altitude coordinates, and coordinated time coordinates.

9. A method comprising:

receiving, with a computer system comprising one or more processors, map data associated with a map of a geographic location, the map comprising a plurality of submaps where an autonomous vehicle can travel, the plurality of submaps comprising one or more roadways;

obtaining, with the computer system, position estimate data associated with a position estimate of the autonomous vehicle in the geographic location;

determining, with the computer system, a route of an autonomous vehicle including a subset of submaps in the plurality of submaps;

determining, with the computer system, a first submap in the subset of submaps of the route closest to the position estimate of the autonomous vehicle;

determining, with the computer system, a second submap outside the subset of submaps of the route closest to the position estimate of the autonomous vehicle;

determining, with the computer system, a distance between the position estimate of the autonomous vehicle and a submap associated with a prior pose of the autonomous vehicle;

determining, with the computer system, a vehicle pose relative to the first submap or the second submap based on the distance; and

controlling the autonomous vehicle on a submap of the map based on the vehicle pose.

10. The method of claim 9 , when determining the vehicle pose relative to the first submap or the second submap, further comprising:

determining that the first submap satisfies a threshold based on the distance between the position estimate of the autonomous vehicle and the submap associated with the prior pose;

determining a projection point associated with the first submap; and

determining a vehicle pose in the first submap based on the position estimate data and the projection point.

11. The method of claim 9 , wherein the map data is associated with a location of the autonomous vehicle in the submap in a subset of submaps of the route, the method further comprising:

determining a roadway segment including the vehicle pose in the first submap based on the map data where the autonomous vehicle can travel under a non-autonomous mode.

12. The method of claim 9 , wherein determining the vehicle pose relative to a submap comprises:

determining that the first submap does not satisfy a threshold based on the distance between the position estimate of the autonomous vehicle and the submap associated with the prior pose; and

in response to determining the first submap does not satisfy the threshold:

determining a projection point associated with the second submap; and

determining a vehicle pose in the second submap based on the position estimate data and the projection point.

13. The method of claim 9 , wherein determining a distance between the position estimate of the autonomous vehicle and a submap associated with a prior vehicle pose of the autonomous vehicle, is based on at least one or more of the following:

a number of transitions of the autonomous vehicle between submaps;

a distance of a route between the position estimate of the autonomous vehicle and the submap associated with the prior vehicle pose; and

a centroid of a submap associated with the prior vehicle pose.

14. The method of claim 9 , when determining the vehicle pose of the autonomous vehicle, determining orientation information based on map data associated with one or more transitions between a submap associated with the prior pose of the autonomous vehicle and a submap of the vehicle pose of the autonomous vehicle.

15. The method of claim 14 , wherein:

the orientation information is associated with an indication of a travel direction for the autonomous vehicle in the submap; and

a vehicle pose is non-viable when a submap of the vehicle pose has a travel direction that is different than a prior travel direction of the autonomous vehicle.

16. A computing system comprising:

one or more processors configured to:

receive map data associated with a map of a geographic location, the map comprising a plurality of submaps where an autonomous vehicle can travel, the plurality of submaps comprising one or more roadways;

obtain position estimate data associated with a position estimate of the autonomous vehicle in the geographic location;

determine a route of the autonomous vehicle including a subset of submaps in the plurality of submaps;

determine a first submap in the subset of submaps of the route closest to the position estimate of the autonomous vehicle;

determine a second submap outside the subset of submaps of the route closest to the position estimate of the autonomous vehicle;

determine a distance between the position estimate of the autonomous vehicle and a submap associated with a prior pose of the autonomous vehicle;

determine a vehicle pose relative to the first submap or the second submap based on the distance; and

control travel of the autonomous vehicle based on the vehicle pose.

17. The computing system of claim 16 , wherein the one or more processors, when determining the vehicle pose relative to a submap, are further configured to:

determine that the first submap satisfies a threshold based on the distance between the position estimate of the autonomous vehicle and the submap associated with the prior pose;

determine a projection point associated with the first submap; and

determine a vehicle pose in the first submap based on the position estimate data and the projection point.

18. The computing system of claim 16 , wherein determining a distance between the position estimate of the autonomous vehicle and a submap associated with a prior location of the autonomous vehicle, is based on at least one or more of the following:

a number of transitions of the autonomous vehicle between submaps;

a distance of a route between the position estimate of the autonomous vehicle and the submap associated with the prior vehicle pose; and

a centroid of a submap associated with the prior vehicle pose.

19. The computing system of claim 16 , wherein the one or more processors, when determining a vehicle pose relative to a submap, are further configured to:

determine that the first submap does not satisfy a threshold based on the distance between the position estimate of the autonomous vehicle and the submap associated with the prior pose; and

in response to determining the first submap does not satisfy the threshold:

determine a projection point associated with the second submap; and

determine a vehicle pose in the second submap based on the position estimate data and the projection point.

20. The computing system of claim 16 , when determining the vehicle pose of the autonomous vehicle, determining orientation information based on map data associated with one or more transitions between a submap associated with the prior pose of the autonomous vehicle and a submap of the vehicle pose of the autonomous vehicle.