Architecture for variable motion control envelope
The technology employs a variable motion control envelope that enables an on-board computing system of a self-driving vehicle to estimate future vehicle driving behavior along an upcoming path, in order to maintain a desired amount of control during autonomous driving. Factors including intrinsic vehicle properties, extrinsic environmental influences and road friction information are evaluated. Such factors can be evaluated to derive an available acceleration model, which defines an envelope of maximum longitudinal and lateral accelerations for the vehicle. This model, which may identify dynamically varying acceleration limits that can be affected by road conditions and road configurations, may be used by the on-board control system (e.g., a planner module of the processing system) to control driving operations of the vehicle in an autonomous driving mode.
1. A method of operating a vehicle in an autonomous driving mode, the method comprising:
generating, by one or more processors of the vehicle, an initial friction estimation based on a road surface classification for a portion of a roadway and weather data for an external environment of the vehicle;
generating, by the one or more processors, an on-line friction estimate based on the initial friction estimation, pose information of the vehicle on the portion of the roadway, and wheel speed information of the vehicle;
generating, by the one or more processors, a set of acceleration limits based on the on-line friction estimate and the pose information, the set of acceleration limits corresponding to an acceleration envelope of both longitudinal acceleration and lateral acceleration; and
controlling the vehicle along the roadway, by the one or more processors in the autonomous driving mode, according to the set of acceleration limits;
wherein the set of acceleration limits is associated with a set of corrective control inputs and a set of primary control inputs, the set of corrective control inputs being obtained from the on-line friction estimate and the pose information, and the set of primary control inputs being obtained from the on-line friction estimate and trajectory information of the vehicle.
2. The method of claim 1 , wherein generating the initial friction estimate includes adjusting friction bounds according to a wetness along the portion of the roadway.
3. The method of claim 1 , wherein generating the initial friction estimate includes weighting the road surface classification more heavily than the weather data.
4. The method of claim 1 , wherein the on-line friction estimate is further based on additional information associated with how much torque is applied to one or more tires of the vehicle.
5. The method of claim 4 , wherein the additional information includes at least one of actuation forces or a tire normal force estimation.
6. The method of claim 1 , wherein the on-line friction estimate is adaptive in real-time during driving along the portion of the roadway in accordance with the pose information and wheel speed information.
7. The method of claim 1 , wherein generating the set of acceleration limits includes generating a set of corrective control inputs and recovery state information, the recovery state information being provided to a motion planner of the vehicle.
8. The method of claim 7 , wherein the recovery state information provides a target trajectory for stabilizing the vehicle.
9. The method of claim 1 , wherein controlling the vehicle is performed based on a combination of the corrective control inputs and the primary control inputs.
10. A vehicle configured to operate in an autonomous driving mode, the vehicle comprising:
a driving system including a steering subsystem, an acceleration subsystem and a deceleration subsystem to control driving of the vehicle in the autonomous driving mode;
a positioning system configured to determine a current position of the vehicle; and
a control system including one or more processors, the control system operatively coupled to the driving system and the positioning system, the control system being configured to:
generate an initial friction estimation based on a road surface classification for a portion of a roadway and weather data for an external environment of the vehicle;
generate an on-line friction estimate based on the initial friction estimation, pose information of the vehicle on the portion of the roadway, and wheel speed information of the vehicle;
generate a set of acceleration limits based on the on-line friction estimate and the pose information, the set of acceleration limits corresponding to an acceleration envelope of both longitudinal acceleration and lateral acceleration; and
control the vehicle along the roadway in the autonomous driving mode according to the set of acceleration limits;
wherein the set of acceleration limits is associated with a set of corrective control inputs and a set of primary control inputs, the set of corrective control inputs being obtained from the on-line friction estimate and the pose information, and the set of primary control inputs being obtained from the on-line friction estimate and trajectory information of the vehicle.
11. The vehicle of claim 10 , wherein generation of the initial friction estimate includes adjustment of friction bounds according to a wetness along the portion of the roadway.
12. The vehicle of claim 10 , wherein generation of the initial friction estimate includes weighting the road surface classification more heavily than the weather data.
13. The vehicle of claim 10 , wherein the on-line friction estimate is further based on additional information associated with how much torque is applied to one or more tires of the vehicle.
14. The vehicle of claim 13 , wherein the additional information includes at least one of actuation forces or a tire normal force estimation.
15. The vehicle of claim 10 , wherein the on-line friction estimate is adaptive in real-time during driving along the portion of the roadway in accordance with the pose information and wheel speed information.
16. The vehicle of claim 10 , wherein generation of the set of acceleration limits includes generation of a set of corrective control inputs and recovery state information, the recovery state information being provided to a motion planner module of the control system.
17. The vehicle of claim 16 , wherein the recovery state information provides a target trajectory for stabilizing the vehicle.
18. The vehicle of claim 10 , wherein control of the vehicle is performed based on a combination of the corrective control inputs and the primary control inputs.