Adaptive vehicle motion control system
Systems and methods for controlling the motion of an autonomous are provided. In one example embodiment, a computer implemented method includes obtaining, by one or more computing devices on-board an autonomous vehicle, data associated with one or more objects that are proximate to the autonomous vehicle. The data includes a predicted path of each respective object. The method includes identifying at least one object as an object of interest based at least in part on the data associated with the object of interest. The method includes generating cost data associated with the object of interest. The method includes determining a motion plan for the autonomous vehicle based at least in part on the cost data associated with the object of interest. The method includes providing data indicative of the motion plan to one or more vehicle control systems to implement the motion plan for the autonomous vehicle.
1. A computing system for controlling autonomous vehicle motion, comprising:
one or more processors on-board an autonomous vehicle; and
one or more memory devices on-board the autonomous vehicle, the one or more memory devices storing instructions that when executed by the one or more processors cause the computing system to perform operations, the operations comprising:
obtaining data associated with a plurality of objects that are within an environment of the autonomous vehicle, wherein the data comprises respective predicted paths for the plurality of objects;
generating cost data associated with the plurality of objects, wherein the cost data for a respective object, of the plurality of objects, is indicative of an effect of controlling a motion of the autonomous vehicle such that the autonomous vehicle travels behind or in front of the respective object;
outputting data indicative of the cost data associated with the plurality of objects;
determining a motion plan for the autonomous vehicle based at least in part on the cost data; and
causing the autonomous vehicle to implement at least a portion of the motion plan for the autonomous vehicle.
2. The computing system of claim 1 , wherein the motion plan comprises one or more parameters associated with the motion of the autonomous vehicle.
3. The computing system of claim 1 , wherein implementation of the motion plan causes the autonomous vehicle to travel in a manner that corresponds to a motion of at least one object of the plurality of objects with at least a minimum distance between the autonomous vehicle and the at least one object.
4. The computing system of claim 1 , wherein the cost data is based at least in part on one or more constraints, and wherein the one or more constraints comprise at least one of a headway between the autonomous vehicle and the respective object and a time to a potential collision between the autonomous vehicle and the respective object.
5. The computing system of claim 1 , wherein the predicted paths indicate that at least one object of the plurality of objects is predicted to travel through an intersection.
6. The computing system of claim 1 , wherein the predicted paths indicate that at least one object of the plurality of objects is predicted to merge into a current travel lane of the autonomous vehicle.
7. The computing system of claim 1 , wherein at least one object of the plurality of objects is located in a travel lane and wherein the autonomous vehicle is to merge into the travel lane.
8. An autonomous vehicle comprising:
one or more processors; and
one or more memory devices, the one or more memory devices storing instructions that when executed by the one or more processors cause the one or more processors to perform operations, the operations comprising:
obtaining data associated with a plurality of objects that are within an environment of the autonomous vehicle, wherein the data associated with the plurality of objects comprises respective predicted paths of the plurality of objects;
performing a cost analysis associated with the plurality of objects, wherein the cost analysis for a respective object, of the plurality of objects, is associated with an effect of controlling a motion of the autonomous vehicle such that the autonomous vehicle travels behind or in front of the respective object;
determining a motion plan for the autonomous vehicle based at least in part on the cost analysis; and
causing the autonomous vehicle to implement at least a portion of the motion plan for the autonomous vehicle.
9. The autonomous vehicle of claim 8 , wherein the plurality of objects comprise a first object that is in a current travel lane of the autonomous vehicle.
10. The autonomous vehicle of claim 8 , wherein performing the cost analysis associated with the plurality of objects comprises:
performing a cost analysis associated with a second object of the plurality of objects, wherein the second object is in another travel lane that is different from a current travel lane of the autonomous vehicle, and wherein the cost analysis associated with the second object is indicative of an effect of controlling the motion of the autonomous vehicle based at least in part on a motion of the second object.
11. The autonomous vehicle of claim 8 , wherein the cost analysis is based at least in part on one or more constraints, and wherein the one or more constraints comprise at least one of: (i) a headway, (ii) a time, or (iii) a preferred distance between the autonomous vehicle and the respective object.
12. The autonomous vehicle of claim 8 , wherein the operations further comprise:
determining that the autonomous vehicle and a first object of the plurality of objects will travel in a same travel lane based at least in part on the predicted path of the first object.
13. The autonomous vehicle of claim 8 , wherein the motion plan comprises one or more parameters associated with the motion of the autonomous vehicle.
14. The autonomous vehicle of claim 13 , wherein the one or more parameters associated with the motion of the autonomous vehicle comprise at least one of a trajectory of the autonomous vehicle or a speed of the autonomous vehicle.
15. A computer-implemented method, comprising:
obtaining data associated with a plurality of objects that are within an environment of an autonomous vehicle, wherein the data comprises respective predicted paths for the plurality of objects;
generating cost data associated with the plurality of objects, wherein the cost data for a respective object, of the plurality of objects, is indicative of an effect of controlling a motion of the autonomous vehicle such that the autonomous vehicle travels behind or in front of the respective object;
outputting data indicative of the cost data associated with the plurality of objects;
determining a motion plan for the autonomous vehicle based at least in part on the cost data; and
causing the autonomous vehicle to implement at least a portion of the motion plan for the autonomous vehicle.
16. The computer-implemented method of claim 15 , wherein the motion plan comprises one or more parameters associated with the motion of the autonomous vehicle.
17. The computer-implemented method of claim 16 , wherein the motion plan comprises a distance between the autonomous vehicle and at least one object of the plurality of objects, and wherein the motion plan is indicative of a modulation of a speed of the autonomous vehicle such that the autonomous vehicle maintains at least the distance between the autonomous vehicle and the at least one object.
18. The computer-implemented method of claim 15 , wherein the predicted path of at least one object of the plurality of objects indicates that the at least one object is predicted to travel in a travel lane in which the autonomous vehicle is currently or will be travelling.
19. The computer-implemented method of claim 15 , wherein the cost data is further indicative of an effect of controlling the motion of the autonomous vehicle such that the autonomous vehicle travels behind or in front of the respective object.
20. The computing system of claim 1 , wherein the autonomous vehicle is an autonomous truck.