Techniques for adaptive driving using language models

One or more non-transitory computer-readable media storing instructions that, when executed by at least one processor, cause the at least one processor to perform the steps of:

• receiving first text that includes a description of a scene and a first plan for driving a vehicle;
• extracting at least one portion of a set of traffic rules based on the description of the scene and the first plan;
• generating a first prompt that requests driving instructions and includes the description of the scene, the first plan, and the at least one portion of the set of traffic rules;
• processing the first prompt via a first trained language model to generate a second plan for driving the vehicle;
• and
• generating driving instructions based on the second plan.

A system, comprising:

• one or more memories storing instructions;
• and
• one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to:
• receive first text that includes a description of a scene and a first plan for driving a vehicle,
• extract at least one portion of a set of traffic rules based on the description of the scene and the first plan,
• generate a first prompt that requests driving instructions and includes the description of the scene, the first plan, and the at least one portion of the set of traffic rules,
• process the first prompt via a first trained language model to generate a second plan for driving the vehicle, and
• generate driving instructions based on the second plan.