Lateral gap planning for autonomous vehicles
Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, a trajectory for the autonomous vehicle to traverse in order to follow a route to a destination may be generated. A first error value for a boundary of an object, a second error value for a location of the autonomous vehicle, a third error value for a predicted future location of the object may be received. An uncertainty value for the object may be determined by combining the first error value, the second error value, and the third error value. A lateral gap threshold for the object may be determined based on the uncertainty value. The autonomous vehicle may be controlled in an autonomous driving mode based on the lateral gap threshold for the object.
1. A method for controlling an autonomous vehicle, the method comprising:
receiving, by one or more processors, a first error value associated with a boundary of an object, a second error value associated with a location of the autonomous vehicle, and a third error value associated with a predicted future location of the object;
determining, by the one or more processors, a total error value by summing the first error value, the second error value, and the third error value together;
determining, by the one or more processors, a lateral gap threshold for the object based on the total error value and a baseline lateral gap threshold, wherein the baseline lateral gap threshold defines a margin of safety for driving next to the object; and
controlling, by the one or more processors, the autonomous vehicle in an autonomous driving mode based on the lateral gap threshold for the object.
2. The method of claim 1 , wherein the first error value, the second error value, and the third error value are standard deviation values.
3. The method of claim 1 , further comprising taking a square root of a sum of squares of the first error value, the second error value, and the third error value.
4. The method of claim 1 , wherein the first error value, the second error value, and the third error value are mean values.
5. The method of claim 1 , wherein determining the lateral gap threshold includes: adding the total error value to the baseline lateral gap threshold.
6. The method of claim 1 , further comprising determining the baseline lateral gap threshold based on current driving conditions.
7. The method of claim 6 , wherein the current driving conditions include whether it is currently precipitating in a driving environment of the autonomous vehicle.
8. The method of claim 6 , wherein the current driving conditions include whether the autonomous vehicle is driving in an urban area.
9. The method of claim 6 , wherein the current driving conditions include whether the autonomous vehicle is driving in a suburban area.
10. The method of claim 1 , further comprising determining the baseline lateral gap threshold based on a type of the object.
11. The method of claim 1 , wherein determining the lateral gap threshold for the object further includes identifying an interaction threshold corresponding to a predetermined percentage of an expected interaction rate with objects.
12. The method of claim 11 , wherein identifying the interaction threshold is based on a type of the object.
13. The method of claim 1 , wherein controlling the autonomous vehicle further includes:
attempting to solve for a trajectory that meets the lateral gap threshold for the object; and
when a trajectory that meets the lateral gap threshold for the object cannot be solved for, adjusting the baseline lateral gap threshold to determine an adjusted lateral gap threshold until a trajectory that meets the adjusted lateral gap threshold for the object is found.
14. The method of claim 1 , further comprising, prior to determining the lateral gap threshold, determining the baseline lateral gap threshold based on acceptable driving behaviors for the autonomous vehicle.
15. A system for controlling an autonomous vehicle, the system comprising one or more processors configured to:
receive a first error value associated with a boundary of an object, a second error value associated with a location of the autonomous vehicle, and a third error value associated with a predicted future location of the object;
determine a total error value by summing the first error value, the second error value, and the third error value together;
determine a lateral gap threshold for the object based on the total error value and a baseline lateral gap threshold, wherein the baseline lateral gap threshold defines a margin of safety for driving next to the object; and
control the autonomous vehicle in an autonomous driving mode based on the lateral gap threshold for the object.
16. The system of claim 15 , wherein the one or more processors are further configured to determine the lateral gap threshold by: adding the total error value to the baseline lateral gap threshold.
17. The system of claim 15 , wherein the baseline lateral gap threshold is determined further based on current driving conditions.
18. The system of claim 15 , wherein the baseline lateral gap threshold is determined further based on a type of the object.
19. The system of claim 15 , wherein the one or more processors are further configured to determine the lateral gap threshold for the object by identifying an interaction threshold corresponding to a predetermined percentage of an expected interaction rate with objects.
20. The system of claim 15 , wherein the one or more processors are further configured to control the autonomous vehicle by:
attempting to solve for a trajectory that meets the lateral gap threshold for the object; and
when a trajectory that meets the lateral gap threshold for the object cannot be solved for, adjusting the baseline lateral gap threshold to determine an adjusted lateral gap threshold until a trajectory that meets the adjusted lateral gap threshold for the object is found.
21. The system of claim 15 , wherein prior to determining the lateral gap threshold, the one or more processors are further configured to determine the baseline lateral gap threshold based on acceptable driving behaviors for the autonomous vehicle.