Pith Number

pith:OHWF4I4T

pith:2021:OHWF4I4TYR4Q2YGBDH4WJAKMLM

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NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

Alex Lang, Eric Wolff, Holger Caesar, Juraj Kabzan, Kok Seang Tan, Luke Fletcher, Oscar Beijbom, Sammy Omari, Whye Kit Fong

NuPlan establishes the first closed-loop benchmark for machine learning planners in autonomous driving.

arxiv:2106.11810 v4 · 2021-06-22 · cs.CV

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Claims

C1strongest claim

In this work, we propose the world's first closed-loop ML-based planning benchmark for autonomous driving.

C2weakest assumption

That the chosen metrics and reactive-agent simulator will produce rankings that correlate with real-world safety and performance once deployed on physical vehicles.

C3one line summary

NuPlan is the first closed-loop benchmark for ML-based autonomous vehicle planning, with 1500h multi-city driving data, reactive simulation, and scenario-specific metrics.

References

24 extracted · 24 resolved · 0 Pith anchors

[1] CommonRoad: Composable benchmarks for motion plan- ning on roads 2017

[2] Chauf- feurnet: Learning to drive by imitating the best and synthe- sizing the worst 2019

[3] Learning to drive from simulation without real world labels

[4] Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom 2020

[5] MP3: A uniﬁed model to map, perceive, predict and plan

Formal links

2 machine-checked theorem links

Cited by

37 papers in Pith

Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving

Distill to Think, Foresee to Act: Cognitive-Physical Reinforcement Learning for Autonomous Driving

CHARMS: A Cognitive Hierarchical Agent for Reasoning and Motion Stylization in Autonomous Driving

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios

Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving

Receipt and verification

First computed	2026-05-17T23:38:52.946943Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

71ec5e2393c4790d60c119f964814c5b102dda94ab6c4e7ff0173c5c8d7a440d

Aliases

arxiv: 2106.11810 · arxiv_version: 2106.11810v4 · doi: 10.48550/arxiv.2106.11810 · pith_short_12: OHWF4I4TYR4Q · pith_short_16: OHWF4I4TYR4Q2YGB · pith_short_8: OHWF4I4T

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/OHWF4I4TYR4Q2YGBDH4WJAKMLM \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 71ec5e2393c4790d60c119f964814c5b102dda94ab6c4e7ff0173c5c8d7a440d

Canonical record JSON

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    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2021-06-22T14:24:55Z",
    "title_canon_sha256": "dc5b7ba36498f684b928c4f9cd994b1b27aeaa522c3c1ce6be58b18844e67273"
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    "kind": "arxiv",
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