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Closed-loop Planning on nuPlan (val14)

93.7CLS-NRLog Replay
48.4660.20571.9583.695Sep 26, 2024Jan 12, 2025Apr 30, 2025Aug 16, 2025Dec 2, 2025Mar 20, 2026Jul 6, 2026

Evaluation results

MethodLinks
Log ReplayType=Expert2024.0993.798.794.498.199.398.996.581.2—
Log-replay (Expert)2026.0793.53——————80.32—
PDM-ClosedType=Rule2024.0993.298.193.399.895.592.199.893—
Intent2Drive2026.0793.02——————84.05—
LLM-ASSIST2026.0793——————92.2—
PLUTO2026.0792.88——————76.88—
PDM-Closed2026.0792.84——————92.12—
PDM-Hybrid2026.0792.77——————92.11—
Flow Planner2026.0790.43——————83.31—
Diffusion Planner2026.0789.87——————82.8—
PLUTOType=Learning2024.098996.193.398.596.489.598.180—
BeTopNetType=Learning2024.0988.396.691.699.593.286.697.183.7—
KnowDiffuserType=Learning-based2026.0387.5——————81.25—
PlanTFType=Learning2024.0985.394.190.796.893.789.897.777.1—
PlanTFType=Learning-based2026.0384.83——————76.78—
PlanTF2026.0784.27——————76.95—
GameFormerType=Hybrid2024.0982.994.386.794.893.38998.783.8—
GameFormerType=Learning-based2026.0380.8——————79.31—
GameFormer2026.0779.94——————79.78—
IDMType=Rule2024.0979.390.983.494.194.486.297.379.3—
IDMType=Rule-based2026.0377.02——————76.5—
IDM2026.0775.6——————77.33—
PlanCNNType=Learning-based2026.0372.89——————71.75—
UrbanDriver2026.0768.57——————64.11—
UrbanDriverType=Learning2024.0967.785.680.390.810080.891.564.8—
PlanCNNType=Learning2024.0966.986.981.48581.480.69864.6—
UrbanDriverType=Learning-based2026.0363.27——————61.02—
GC-PGPType=Learning2024.0961.185.880.189.79060.399.354.9—
GC PGPType=Learning-based2026.0355.99——————51.39—
PDM-OpenType=Learning2024.0950.274.569.187.999.569.897.754.8—
CoPlannerType=Learning-based, Evaluation Protocol=NR2026.06————————89.48
CoPlannerType=Learning-based, Evaluation Protocol=R2026.06————————79
DFPType=Learning-based, Evaluation Protocol=NR2026.06————————90.33
DFPType=Learning-based, Evaluation Protocol=R2026.06————————79.97
DFP-FMType=Learning-based, Evaluation Protocol=NR2026.06————————92.68
DFP-FMType=Learning-based, Evaluation Protocol=R2026.06————————81.3
Diffusion PlannerType=Learning-based, Evaluation Protocol=NR2026.06————————89.87
Diffusion PlannerType=Learning-based, Evaluation Protocol=R2026.06————————82.8
Diffusion Planner*Type=Learning-based, Evaluation Protocol=NR, Note=best reimplementation result2026.06————————87.87
Diffusion Planner*Type=Learning-based, Evaluation Protocol=R, Note=best reimplementation result2026.06————————77.48
GameFormerType=Learning-based, Evaluation Protocol=NR2026.06————————13.32
GameFormerType=Learning-based, Evaluation Protocol=R2026.06————————8.69
Log-replayType=Expert, Evaluation Protocol=NR2026.06————————93.53
Log-replayType=Expert, Evaluation Protocol=R2026.06————————80.32
PDM-OpenType=Learning-based, Evaluation Protocol=NR2026.06————————53.53
PDM-OpenType=Learning-based, Evaluation Protocol=R2026.06————————54.24
PlanTFType=Learning-based, Evaluation Protocol=NR2026.06————————84.27
PlanTFType=Learning-based, Evaluation Protocol=R2026.06————————76.95
PLUTOType=Learning-based, Evaluation Protocol=NR2026.06————————88.89
PLUTOType=Learning-based, Evaluation Protocol=R2026.06————————78.11
UrbanDriverType=Learning-based, Evaluation Protocol=NR2026.06————————68.57
UrbanDriverType=Learning-based, Evaluation Protocol=R2026.06————————64.11