Systems and methods for vehicle motion planning

1. A method for operating an autonomous vehicle, comprising:

detecting, by a computing device, an object in proximity to the autonomous vehicle;

determining, by the computing device, a path of travel for the object that comprises a number of data points that is equal to a given number of vehicle locations selected based on a geometry of a lane in which the object is positioned;

generating, by the computing device, cost curves respectively associated with the data points, each cost curve representing a displacement cost to be at a particular location along a given cross line that (i) passes through a respective data point of said data points and (ii) extends perpendicular to and between boundary lines of the lane;

determining, by the computing device, a polyline representing displacements of the cost curves from a center of the lane;

defining, by the computing device, a predicted path of travel for the object based on the polyline; and

using, by the computing device, the predicted path of travel for the object to facilitate at least one autonomous driving operation of the autonomous vehicle.

2. The method according to claim 1 , further comprising determining, by the computing device, whether the object has a driving intention.

3. The method according to claim 2 , wherein the computing device determines the path of travel for the object when a determination is made that the object has a driving intention.

4. The method according to claim 1 , wherein the given number of vehicle locations has different values for straight and curved lanes.

5. The method according to claim 1 , wherein each data point of the path of travel is aligned with and resides on a center of the lane in a road map.

6. The method according to claim 1 , wherein each data point is longitudinally offset from a current location of the object.

7. The method according to claim 1 , wherein the cost curves are generated using at least one of a cost function representing a distance from the object to a left boundary of the lane, a cost function representing a distance from the object to a right boundary of the lane, a cost function representing how close the object should follow a center of the lane, a cost function representing location consistencies to the left and right boundaries of the lane, and a cost function representing locations that are close to static obstacles.

8. The method according to claim 1 , further comprising generating combined cost curves by combining the cost curves associated with each said data points.

9. The method according to claim 8 , wherein the polyline comprises data points with coordinate values determined based on the minimum values of the combined cost curves.

10. The method according to claim 1 , further comprising determining a forecasted path of travel for the object based on the predicted path of travel.

11. A system, comprising:

a processor;

a non-transitory computer-readable storage medium comprising programming instructions that are configured to cause the processor to implement a method for operating an autonomous vehicle, wherein the programming instructions comprise instructions to:

detect an object in proximity to the autonomous vehicle;

determine a path of travel for the object that comprises a number of data points that is equal to a given number of vehicle locations selected based on a geometry of a lane in which the object is positioned;

generate cost curves respectively associated with the data points, each cost curve representing a displacement cost to be at a particular location along a given cross line that (i) passes through a respective data point of said data points and (ii) extends perpendicular to and between boundary lines of the lane;

determine a polyline representing displacements of the cost curves from a center of the lane;

define a predicted path of travel for the object based on the polyline; and

use the predicted path of travel for the object to facilitate at least one autonomous driving operation of the autonomous vehicle.

12. The system according to claim 11 , wherein the programming instructions further comprise instruction to determine whether the object has a driving intention.

13. The system according to claim 12 , wherein the path of travel for the object is determined when a determination is made that the object has a driving intention.

14. The system according to claim 11 , wherein the given number of vehicle locations has different values for straight and curved lanes.

15. The system according to claim 11 , wherein each data point of the path of travel is aligned with and resides on a center of the lane in a road map.

16. The system according to claim 11 , wherein each data point is longitudinally offset from a current location of the object.

17. The system according to claim 11 , wherein the cost curves are generated using at least one of a cost function representing a distance from the object to a left boundary of the lane, a cost function representing a distance from the object to a right boundary of the lane, a cost function representing how close the object should follow a center of the lane, a cost function representing location consistencies to the left and right boundaries of the lane, and a cost function representing locations that are close to static obstacles.

18. The system according to claim 11 , wherein the programming instructions further comprise instruction to generate combined cost curves by combining the cost curves associated with each said data points.

19. The system according to claim 18 , wherein the polyline comprises data points with coordinate values determined based on the minimum values of the combined cost curves.

20. The system according to claim 11 , wherein the programming instructions further comprise instruction to determine a forecasted path of travel for the object based on the predicted path of travel.