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Closed-loop Planning on nuPlan 14 (test)

95.02NRFlowDrive*
8.013630.601853.1975.7782Sep 26, 2025Nov 12, 2025Dec 29, 2025Feb 14, 2026Apr 2, 2026May 19, 2026Jul 6, 2026

Evaluation results

MethodLinks
FlowDrive*Type=Rule-based & Hybrid2025.0995.0293.96—
Pluto-SoEType=Hybrid, Time (ms)=2592025.1294.8290.47—
DiffusionType=Hybrid2025.1294.891.75—
Diffusion PlannerType=Rule-based & Hybrid, Refinement=Enabled2025.0994.891.75—
Diffusion Planner w/ refineType=Rule-based & Hybrid2026.0294.891.75—
Log-ReplayType=Rule2025.1294.0375.86—
Log-replayType=Expert2025.0994.0375.86—
Log-replayType=Expert2026.0294.0375.86—
Log-replay (Expert)2026.0794.0375.86—
PlutoType=Hybrid, Time (ms)=2592025.1292.5590.29—
PLUTOType=Rule-based & Hybrid2025.0992.2390.29—
PLUTOType=Rule-based & Hybrid2026.0292.2390.29—
PLUTO2026.0792.2390.29—
Pluto w/o-SoE1Type=Learning, Time (ms)=1072025.1291.3982.29—
FlowDriveType=Learning-based2025.0991.0287.28—
Pluto w/o-SoE2Type=Learning, Time (ms)=1072025.1290.8583.07—
Pluto w/oType=Learning, Time (ms)=1072025.1290.6778.06—
FlowDrive-Type=Learning-based2025.0990.1983.47—
PDM-HybridType=Rule-based & Hybrid2025.0990.191.28—
PDM-HybridType=Rule-based & Hybrid2026.0290.191.28—
PDM-Hybrid2026.0790.191.28—
PDM-ClosedType=Rule, Time (ms)=1222025.1290.0591.64—
PDM-ClosedType=Rule-based & Hybrid2025.0990.0591.63—
PDM-ClosedType=Rule-based & Hybrid2026.0290.0591.63—
PDM-Closed2026.0790.0591.63—
RAPiDType=Learning-based2026.0289.9881.86—
PLUTOType=Learning-based, Refinement=None2025.0989.978.62—
PLUTO w/o refineType=Learning-based, Pre-computed reference paths=true2026.0289.978.62—
Flow Planner2026.0789.8882.93—
Diffusion w/oType=Learning, Time (ms)=1592025.1289.482.67—
Diffusion PlannerType=Learning-based2025.0989.1982.93—
DiffusionPlannerType=Learning-based2026.0289.1982.93—
Diffusion Planner2026.0789.1982.93—
planTF-SoEType=Learning, Time (ms)=782025.1288.0678.88—
Intent2Drive2026.0787.281.35—
PlanTFType=Learning-based2025.0985.6279.58—
PlanTFType=Learning-based2026.0285.6279.58—
PlanTF2026.0785.6279.58—
planTFType=Learning, Time (ms)=782025.1285.678.86—
GameFormerType=Rule-based & Hybrid2025.0983.8882.05—
GameFormerType=Rule-based & Hybrid2026.0283.8882.05—
GameFormer2026.0783.8882.05—
IDMType=Rule, Time (ms)=412025.1270.3972.42—
IDMType=Rule-based & Hybrid2025.0970.3974.42—
IDMType=Rule-based & Hybrid2026.0270.3974.42—
IDM2026.0770.3974.42—
Raster-SoEType=Learning, Time (ms)=372025.1269.8972.86—
RasterType=Learning, Time (ms)=372025.1265.8769.93—
PDM-OpenType=Learning, Time (ms)=652025.1252.9158.1—
PDM-OpenType=Learning-based2025.0952.8157.23—
PDM-OpenType=Learning-based, Pre-computed reference paths=true2026.0252.8157.23—
PDM-Open-SoEType=Learning, Time (ms)=652025.1252.7559.85—
UrbanDriverType=Learning-based2026.0251.8367.15—
UrbanDriver2026.0751.8367.15—
GameFormerType=Learning-based, Refinement=None2025.0911.369.31—
GameFormer w/o refineType=Learning-based2026.0211.369.31—
Diffusion PlannerType=Rule-based & Hybrid, Refinement=true2025.11——94.13
Diffusion PlannerType=Learning-based2025.11——88.84
Diffusion PlannerReactive setting=Non-reactive (NR), Refinement module=with refinement2026.04——94.8
Diffusion PlannerReactive setting=Reactive (R), Refinement module=with refinement2026.04——91.75
Diffusion PlannerReactive setting=Non-reactive (NR)2026.04——89.19
Diffusion PlannerReactive setting=Reactive (R)2026.04——82.93
GameFormerReactive setting=Non-reactive (NR)2026.04——83.88
GameFormerReactive setting=Reactive (R)2026.04——82.05
GC-PGPType=Learning-based2025.11——61.16
IDMType=Rule-based & Hybrid2025.11——70.39
IDMReactive setting=Non-reactive (NR)2026.04——70.39
IDMReactive setting=Reactive (R)2026.04——74.42
LAPType=Rule-based & Hybrid, Refinement=true, Solver order (o)=1, Denoising steps (s)=12025.11——93.9
LAPType=Rule-based & Hybrid, Refinement=true, Solver order (o)=1, Denoising steps (s)=22025.11——94.4
LAPType=Learning-based, Solver order (o)=1, Denoising steps (s)=12025.11——89.85
LAPType=Learning-based, Solver order (o)=1, Denoising steps (s)=22025.11——90.42
Log-replayReactive setting=Non-reactive (NR)2026.04——94.03
Log-replayReactive setting=Reactive (R)2026.04——75.86
Log-ReplayType=Expert2025.11——94.03
MISTYReactive setting=Non-reactive (NR), Refinement module=with refinement2026.04——91.24
MISTYReactive setting=Reactive (R), Refinement module=with refinement2026.04——90.7
MISTYReactive setting=Non-reactive (NR), Refinement module=without refinement2026.04——78.88
MISTYReactive setting=Reactive (R), Refinement module=without refinement2026.04——82.25
PDM-ClosedType=Rule-based & Hybrid2025.11——90.05
PDM-ClosedReactive setting=Non-reactive (NR)2026.04——90.05
PDM-ClosedReactive setting=Reactive (R)2026.04——91.63
PDM-HybridType=Rule-based & Hybrid2025.11——90.1
PDM-OpenType=Learning-based, Pre-searched reference lines=true2025.11——52.81
PlanTFReactive setting=Non-reactive (NR)2026.04——85.62
PlanTFReactive setting=Reactive (R)2026.04——79.58
PLUTOType=Rule-based & Hybrid2025.11——92.6
PLUTOType=Learning-based, Refinement=false, Pre-searched reference lines=true2025.11——90.11
PLUTOReactive setting=Non-reactive (NR)2026.04——92.23
PLUTOReactive setting=Reactive (R)2026.04——90.29
PLUTOReactive setting=Non-reactive (NR), Refinement module=without refinement2026.04——89.9
PLUTOReactive setting=Reactive (R), Refinement module=without refinement2026.04——78.62
UrbanDriverType=Learning-based2025.11——51.83