Back to results
US 11,529,961 B2Granted
Tracking object path in map prior layer
AssigneeGM Cruise Holdings LLC
InventorsZachary Garcia, Chen “Steve” Xie
Life of this patent
Estimating the term…
Abstract
Systems, methods, and devices are disclosed for predicting behaviors of objects (vehicles, bicycles, pedestrians, etc.) at a location. A model descriptive of a possible object behavior can be received by an autonomous vehicle, where the model provides conditional predictions about a future behavior of an object based on a position of the object in a lane. The autonomous vehicle can detect the position of a specific object in the lane, and the model can then be applied to determine probabilities of a future behavior of the specific object.
Claims17
A non-transitory computer-readable medium comprising instructions that are effective to cause at least one processor to:
- receive a map descriptive of observed vehicle paths, wherein the map provides observed paths that have been taken by multiple vehicles in a map segment over a period of time, wherein the map describes probable vehicle paths from a specific lane at a specific geographic location;
- determine a prediction model that determines a path based on a yield probability of a vehicle, wherein the yield probability predicts that the vehicle will come to a stop at, prior to, or past a stop sign at the specific lane;
- as an autonomous vehicle approaches the stop sign, determine a first planned path that brings the autonomous vehicle to a stop at or prior to the stop sign;
- as the autonomous vehicle approaches the stop sign, detect a position of a specific vehicle separate from the autonomous vehicle, wherein the specific vehicle is detected to be in the lane represented by the map segment;
- apply the prediction model to determine probabilities of future paths of the specific vehicle at the specific lane, wherein at least one of the future paths has a yield probability that predicts that the specific vehicle will stop past the stop sign;
- generate a second planned path for the autonomous vehicle by modifying the first planned path to account for the determined probabilities of the future paths of the specific vehicle, including the determined yield probability that the specific vehicle will stop past the stop sign;
- and
- pilot the autonomous vehicle along the second planned path.
5 more elements
A method comprising:
- mapping historical information about vehicle paths from a specific lane at a specific geographic location and a subsequent behavior of the vehicles;
- generating a model of vehicle behavior in the lane based on the historical information, wherein the model provides conditional predictions about a future behavior of a specific vehicle based on the specific vehicle coming to a stop at, prior to, or past a stop sign at the specific lane;
- based on the mapped historical information, determining a prediction about the future behavior of the specific vehicle at the specific lane, the prediction based on a yield probability that predicts that the specific vehicle will stop past the stop sign;
- and
- piloting an autonomous vehicle along a planned path based on the prediction about the future behavior of the specific vehicle at the specific lane.
2 more elements
A system comprising:
- a non-transitory computer-readable medium comprising instructions stored thereon;
- and
- at least one processor, wherein the instructions are effective to cause the at least one processor to:
- receive a map descriptive of observed vehicle paths, wherein the map provides observed paths that have been taken by multiple vehicles in a map segment over a period of time, wherein the map describes probable vehicle paths from a specific lane at a specific geographic location;
- determine a prediction model that determines a path based on a yield probability of a vehicle, wherein the yield probability predicts that the vehicle will come to a stop at, prior to, or past a stop sign at the specific lane;
- as an autonomous vehicle approaches the stop sign, determine a first planned path that brings the autonomous vehicle to a stop at or prior to the stop sign;
- as the autonomous vehicle approaches the stop sign, detect a position of a specific vehicle separate from the autonomous vehicle, wherein the specific vehicle is detected to be in a lane represented by the map segment;
- apply the prediction model to determine probabilities of future paths of the specific vehicle at the specific lane, wherein at least one of the future paths has a yield probability that the specific vehicle will stop past the stop sign;
- generate a second planned path for the autonomous vehicle by modifying the first planned path to account for the determined probabilities of the future paths of the vehicle, including the determined yield probability that predicts that the specific vehicle will stop past the stop sign;
- and
- pilot the autonomous vehicle along the second planned path.
8 more elements
Dependencies are inferred from the claim text.