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 computer-implemented method of controlling autonomous vehicle motion, comprising:
obtaining, by a computing system comprising one or more computing devices, data associated with an object that is proximate to an autonomous vehicle, wherein the data comprises a predicted path of the object;
performing, by the computing system, a cost analysis of controlling a motion of the autonomous vehicle to maintain travel behind the object at a following distance or in front of the object at a leading distance in a manner that corresponds to a motion of the object;
determining, by the computing system, a motion plan for the autonomous vehicle based at least in part on the cost analysis; and
causing, by the computing system, the autonomous vehicle to implement at least a portion of the motion plan for the autonomous vehicle.
2. The computer-implemented method of claim 1 , wherein the object comprises a lead vehicle and wherein traveling in the manner that corresponds to the object comprises following the lead vehicle.
3. The computer-implemented method of claim 1 , wherein the object is located behind the autonomous vehicle and wherein traveling in the manner that corresponds to the object comprises travelling in front of the object.
4. The computer-implemented method of claim 1 , further comprising:
identifying, by the computing system, the object as a collision risk with respect to the autonomous vehicle.
5. The computer-implemented method of claim 1 , wherein performing the cost analysis comprises:
generating, by the computing system, cost data associated with the object, wherein the cost data is indicative of a cost of controlling the motion of the autonomous vehicle to maintain travel behind the object at the following distance or in front of the object at the leading distance in a manner that corresponds to the motion of the object.
6. The computer-implemented method of claim 5 , 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 object, a time to a potential collision between the autonomous vehicle and the object, and a minimum preferred distance between the autonomous vehicle and the object.
7. The computer-implemented method of claim 1 , wherein performing the cost analysis comprises:
generating, by the computing system, a cost function that is indicative of a cost of controlling the motion of the autonomous vehicle in the manner that corresponds to the motion of the object.
8. The computer-implemented method of claim 7 , wherein one or more inputs of the cost function comprise at least a subset of the data associated with the object and a travel route of the autonomous vehicle.
9. The computer-implemented method of claim 1 , wherein the motion plan comprises a trajectory by which the autonomous vehicle is to travel behind the object or a trajectory by which the autonomous vehicle is to travel in front of the object.