τ = T ({(x1, y1),··· , (x6, y6)}) = {w1,··· , wn}.

(7)

With these language tokens, we then reformulate motion
planning as a language modeling problem:

enables the LLMs to generate more diverse reasoning
outputs, and results in better motion planning performance.
4.2. Task Planning

Task planning aims to generate high-level driving plans P
for autonomous vehicles, taking the reasoning results R as
well as the environmental information O and memory data
M as inputs. The process can be formulated as

P = FLLM(O,M,R).

(5)
ALanguageAgentforAutonomousDriving