System and method for identifying travel way features for autonomous vehicle motion control
Systems and methods for identifying travel way features in real time are provided. A method can include receiving two-dimensional and three-dimensional data associated with the surrounding environment of a vehicle. The method can include providing the two-dimensional data as one or more input into a machine-learned segmentation model to output a two-dimensional segmentation. The method can include fusing the two-dimensional segmentation with the three-dimensional data to generate a three-dimensional segmentation. The method can include storing the three-dimensional segmentation in a classification database with data indicative of one or more previously generated three-dimensional segmentations. The method can include providing one or more datapoint sets from the classification database as one or more inputs into a machine-learned enhancing model to obtain an enhanced three-dimensional segmentation. And, the method can include identifying one or more travel way features based at least in part on the enhanced three-dimensional segmentation.
1. A computer-implemented method comprising:
obtaining three-dimensional data associated with an environment of an autonomous vehicle at a current time;
generating a current three-dimensional segmentation based on the three dimensional data associated with the environment of the autonomous vehicle at the current time;
obtaining a previously generated three-dimensional segmentation associated with the environment of the autonomous vehicle;
generating an updated three-dimensional segmentation based on the current three-dimensional segmentation and the previously generated three-dimensional segmentation;
determining a travel way feature within the environment based on the updated three-dimensional segmentation; and
controlling an operation of the autonomous vehicle based on the travel way feature within the environment.
2. The computer-implemented method of claim 1 , comprising:
providing, for storage in a memory, the current three-dimensional segmentation, wherein storage of the current three-dimensional segmentation in the memory updates the previously generated three-dimensional segmentation.
3. The computer-implemented method of claim 1 , wherein the updated three-dimensional segmentation comprises a plurality of three-dimensional datapoints, the plurality of three-dimensional datapoints indicative of an estimated segmentation of aggregated three-dimensional points at the current time.
4. The computer-implemented method of claim 3 , wherein the plurality of datapoints correspond to the travel way feature associated with the previously generated three-dimensional segmentation.
5. The computer-implemented method of claim 1 , comprising:
iteratively updating the current three-dimensional segmentation at one or more times succeeding the current time.
6. The computer-implemented method of claim 1 , wherein the operation of the autonomous vehicle comprises controlling a motion of the autonomous vehicle, the method comprising:
initiating a motion control of the autonomous vehicle based on the travel way feature within the environment.
7. The computer-implemented method of claim 6 , comprising:
generating a motion plan based on the travel way feature within the environment; and
providing, to a vehicle control system, data based on the motion plan of the autonomous vehicle.
8. The computer-implemented method of claim 1 , wherein the previously generated three-dimensional segmentation and the updated three-dimensional segmentation are stored in non-parametric memory.
9. The computer-implemented method of claim 1 , wherein the previously generated three-dimensional segmentation and the updated three-dimensional segmentation are stored remote from the autonomous vehicle.
10. An autonomous vehicle control system comprising:
one or more processors; and
one or more tangible, non-transitory, computer readable media storing instructions that are executable by the one or more processors to cause the autonomous vehicle control system to perform operations, the operations comprising:
obtaining three-dimensional data associated with an environment of an autonomous vehicle at a current time;
generating a current three-dimensional segmentation based on the three dimensional data associated with the environment of the autonomous vehicle at the current time;
obtaining a previously generated three-dimensional segmentation associated with the environment of the autonomous vehicle;
generating an updated three-dimensional segmentation based on the current three-dimensional segmentation and the previously generated three-dimensional segmentation;
determining a travel way feature within the environment based on the updated three-dimensional segmentation; and
controlling the autonomous vehicle based on the travel way feature within the environment.
11. The autonomous vehicle control system of claim 10 , wherein the operations comprise:
providing, for storage in a memory, the current three-dimensional segmentation, wherein storage of the current three-dimensional segmentation in the memory updates the previously generated three-dimensional segmentation.
12. The autonomous vehicle control system of claim 10 , wherein the operations comprise:
iteratively updating the current three-dimensional segmentation at one or more times succeeding the current time.
13. The autonomous vehicle control system of claim 10 , wherein the operations comprise:
initiating a motion control of the autonomous vehicle based on the travel way feature within the environment.
14. The autonomous vehicle control system of claim 10 , wherein the previously generated three-dimensional segmentation and the updated three-dimensional segmentation are stored in non-parametric memory.
15. The autonomous vehicle control system of claim 10 , wherein the previously generated three-dimensional segmentation and the updated three-dimensional segmentation are stored remote from the autonomous vehicle.
16. One or more tangible, non-transitory, computer readable media storing instructions that are executable by one or more processors to perform operations, the operations comprising:
obtaining three-dimensional data associated with an environment of an autonomous vehicle at a current time;
generating a current three-dimensional segmentation based on the three dimensional data associated with the environment of the autonomous vehicle at the current time;
obtaining a previously generated three-dimensional segmentation associated with the environment of the autonomous vehicle;
generating an updated three-dimensional segmentation based on the current three-dimensional segmentation and the previously generated three-dimensional segmentation;
determining a travel way feature within the environment based on the updated three-dimensional segmentation; and
controlling the autonomous vehicle based on the travel way feature within the environment.
17. The one or more tangible, non-transitory, computer readable media of claim 16 , wherein the operations comprise:
providing, for storage in a memory, the current three-dimensional segmentation, wherein storage of the current three-dimensional segmentation in the memory updates the previously generated three-dimensional segmentation.
18. The one or more tangible, non-transitory, computer readable media of claim 17 , wherein the memory stores one or more past observations associated with the environment of the autonomous vehicle.
19. The one or more tangible, non-transitory, computer readable media of claim 16 , wherein the operations comprise:
initiating a motion control of the autonomous vehicle based on the travel way feature within the environment; and
initiating a motion of the autonomous vehicle based on the travel way feature within the environment.
20. The one or more tangible, non-transitory, computer readable media of claim 16 , wherein the operations comprise:
iteratively updating the current three-dimensional segmentation at one or more times succeeding the current time.