High definition map and route storage management system for autonomous vehicles
High definition maps for autonomous vehicles are very high resolution and detailed, and hence require storage of a great deal of data. A vehicle computing system provides multi-layered caching makes this data usable in a system that requires very low latency on every operation. The system determines which routes are most likely to be driven in the near future by the car, and ensures that the route is cached on the vehicle before beginning the route. The system provides efficient formats for moving map data from server to car and for managing the on-car disk. The system further provides real-time accessibility of nearby map data as the car moves, while providing data access at optimal speeds.
1. A method of caching high-definition (HD) map data by a vehicle comprising:
storing, by a vehicle, a plurality of map tiles, each map tile representing a portion of the HD map data;
determining a location of the vehicle based on sensor data;
predicting movement of the vehicle within a threshold time interval from the location;
determining a subset of map tiles based on the location and the predicted movement, each map tile of the subset of map tiles corresponding to a portion of a route that the vehicle is likely to drive through within the threshold time interval;
loading the subset of map tiles in the RAM; and
providing access to the subset of map tiles loaded in the RAM during navigation of the vehicle along the route.
2. The method of claim 1 , further comprising loading the subset of map tiles from a first cache of decompressed map tiles.
3. The method of claim 2 , further comprising:
obtaining a compressed subset of map tiles from a second cache of compressed map tiles;
decompressing the compressed subset of map tiles to obtain the subset of map tiles; and
storing the decompressed subset of map tiles in the first cache.
4. The method of claim 1 , wherein predicting the movement of the vehicle is based on localization data of the vehicle obtained at a plurality of time intervals.
5. The method of claim 4 , further comprising determining the localization data based on the sensor data and the HD map data.
6. The method of claim 1 , wherein the sensor data is obtained from one or more sensors selected from a group of sensors comprising: a detection and ranging sensor; a Global Positioning System (GPS) receiver, a camera, and an inertial measurement unit (IMU).
7. The method of claim 1 , wherein determining the subset of map tiles based on the location and the predicted movement further comprises:
identifying, based on the location, a first map tile in which the vehicle is currently located; and
determining a second map tile adjacent to the first map tile that is located with respect to the first map tile according to the predicted movement, wherein the first map tile and the second map tile are included in the subset of map tiles.
8. One or more non-transitory computer-readable storage media having instructions stored thereon that, in response to being executed by one or more processors, cause a system to perform operations comprising:
storing, by a vehicle, a plurality of map tiles, each map tile representing a portion of Hight Definition (HD) map data;
determining a location of the vehicle based on sensor data;
predicting movement of the vehicle within a threshold time interval from the location;
determining a subset of map tiles based on the location and the predicted movement, each map tile of the subset of map tiles corresponding to a portion of a route that the vehicle is likely to drive through within the threshold time interval;
loading the subset of map tiles in the RAM; and
providing access to the subset of map tiles loaded in the RAM during navigation of the vehicle along the route.
9. The one or more non-transitory computer-readable storage media of claim 8 , the operations further comprising loading the subset of map tiles from a first cache of decompressed map tiles.
10. The one or more non-transitory computer-readable storage media of claim 9 , the operations further comprising:
obtaining a compressed subset of map tiles from a second cache of compressed map tiles;
decompressing the compressed subset of map tiles to obtain the subset of map tiles; and
storing the decompressed subset of map tiles in the first cache.
11. The one or more non-transitory computer-readable storage media of claim 8 , wherein predicting the movement of the vehicle is based on localization data of the vehicle obtained at a plurality of time intervals.
12. The one or more non-transitory computer-readable storage media of claim 11 , the operations further comprising determining the localization data based on the sensor data and the HD map data.
13. The one or more non-transitory computer-readable storage media of claim 8 , wherein the sensor data is obtained from one or more sensors selected from a group of sensors comprising: a detection and ranging sensor; a Global Positioning System (GPS) receiver, a camera, and an inertial measurement unit (IMU).
14. The one or more non-transitory computer-readable storage media of claim 8 , wherein determining the subset of map tiles based on the location and the predicted movement further comprises:
identifying, based on the location, a first map tile in which the vehicle is currently located; and
determining a second map tile adjacent to the first map tile that is located with respect to the first map tile according to the predicted movement, wherein the first map tile and the second map tile are included in the subset of map tiles.
15. A system comprising:
one or more processors; and
one or more non-transitory computer-readable storage media having instructions stored thereon that, in response to being executed by the one or more processors, cause the system to perform operations comprising:
storing, by a vehicle, a plurality of map tiles, each map tile representing a portion of High Definition (HD) map data;
determining a location of the vehicle based on sensor data;
predicting movement of the vehicle within a threshold time interval from the location;
determining a subset of map tiles based on the location and the predicted movement, each map tile of the subset of map tiles corresponding to a portion of a route that the vehicle is likely to drive through within the threshold time interval;
loading the subset of map tiles in the RAM; and
providing access to the subset of map tiles loaded in the RAM during navigation of the vehicle along the route.
16. The system of claim 15 , the operations further comprising loading the subset of map tiles from a first cache of decompressed map tiles.
17. The system of claim 16 , the operations further comprising:
obtaining a compressed subset of map tiles from a second cache of compressed map tiles;
decompressing the compressed subset of map tiles to obtain the subset of map tiles; and
storing the decompressed subset of map tiles in the first cache.
18. The system of claim 15 , wherein predicting the movement of the vehicle is based on localization data of the vehicle obtained at a plurality of time intervals.
19. The system of claim 18 , the operations further comprising determining the localization data based on the sensor data and the HD map data.
20. The system of claim 15 , wherein the sensor data is obtained from one or more sensors selected from a group of sensors comprising: a detection and ranging sensor; a Global Positioning System (GPS) receiver, a camera, and an inertial measurement unit (IMU).
21. The system of claim 15 , wherein determining the subset of map tiles based on the location and the predicted movement further comprises:
identifying, based on the location, a first map tile in which the vehicle is currently located; and
determining a second map tile adjacent to the first map tile that is located with respect to the first map tile according to the predicted movement, wherein the first map tile and the second map tile are included in the subset of map tiles.