Station-time scene representation for machine learning (ml)-based planning

A method for performing trajectory planning for an object, comprising:

• obtaining an ST scene representing 1) a displacement of one or more agents over time with respect to a reference point corresponding to a current position of the object and 2) a target location of the object;
• inputting the ST scene into a first machine learning model;
• outputting, by the first machine learning model, based on the input ST scene, a first target trajectory for the object to follow to occupy the target location;
• sending the first target trajectory to a second machine learning model;
• and
• obtaining, from the second machine learning model, a second target trajectory for the object to follow to occupy the target location.

A non-transitory computer-readable medium comprising instructions, which when executed by one or more processors, cause the one or more processors to perform operations for trajectory planning for an object, the operations comprising:

• obtaining an ST scene representing 1) a displacement of one or more agents over time with respect to a reference point corresponding to a current position of the object and 2) a target location of the object;
• inputting the ST scene into a first machine learning model;
• outputting, by the first machine learning model, based on the input ST scene, a first target trajectory for the object to follow to occupy the target location;
• sending the first target trajectory to a second machine learning model;
• and
• obtaining, from the second machine learning model, a second target trajectory for the object to follow to occupy the target location.