NHTSA vehicle complaint intelligence (monthly)

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Le jeu complet n’est pas encore publié — revenez après la prochaine actualisation.Télécharger l'exemple CSV Télécharger l'exemple JSONLignes d’exemple seulement (jusqu’à 20) — pas le jeu de données complet.

Monthly complaint-burden ranking of US-market passenger vehicles by model year, from the official keyless NHTSA ODI complaints API (universe enumerated via vPIC). Per model-year: ODI-deduped complaint counts, crash/fire/injury/death tallies folded into a documented severity model (3*crash + 5*fire + 2*injuries + 10*deaths), a top-level NHTSA component taxonomy (VISIBILITY/WIPER -> VISIBILITY) with the dominant component and its share, year-over-year complaint change vs the prior model year, and a 0-100 complaint-burden composite (50% min-max(log1p(complaints)) + 50% min-max(severity rate)) ranked with deterministic tie-breaks. Vehicles with fewer than 5 complaints are excluded (noise gate; also screens out model keys the complaints index cannot resolve, e.g. dashed F-series keys). VINs and free-text summaries are never stored. The score is a complaint burden signal, not a defect rate: complaints are self-reported and counts are not normalized by sales volume. Primary key: (model_year, make_slug, model_slug). Cadence: monthly. Caveats: complaint counts tick as new complaints are filed, so same-month re-runs may differ slightly.

Les titres et les descriptions proviennent des sources de données, en anglais.

Source: NHTSA vehicle complaint intelligence (agent-curated)
Lignes: 833
Colonnes: 23
Cadence de la source: Mensuelle
Dernière actualisation: 25 sept. 2026
Thème: transport

Colonne	Type	Description
model_year	integer	Vehicle model year. (unit: year)
make	string	Vehicle make, vPIC canonical name.
make_slug	string	URL-safe slug of the make.
model	string	Vehicle model, vPIC canonical name.
model_slug	string	URL-safe slug of the model.
vehicle_label	string	Human-readable 'YEAR Make Model' label.
nhtsa_url	string	Exact NHTSA complaints API query behind this row. (unit: URL)
complaint_count	integer	ODI-deduped complaints against this model year. (unit: count)
crash_count	integer	Complaints reporting a crash. (unit: count)
fire_count	integer	Complaints reporting a fire. (unit: count)
injury_total	integer	Total injuries reported. (unit: count)
death_total	integer	Total deaths reported. (unit: count)
severity_raw	float	Weighted severity: 3crash+5fire+2injuries+10deaths. (unit: score)
severity_rate	float	severity_raw per complaint. (unit: score)
severity_score	float	0-100 min-max normalized severity_rate. (unit: 0-100)
top_component	string	Most-complained top-level NHTSA component category.
top_component_share_pct	float	Share of complaints mentioning the top component. (unit: percent)
n_distinct_components	integer	Distinct top-level component categories. (unit: count)
complaints_yoy_pct	float	YoY complaint change vs prior model year of same make+model; null when the prior year is absent. (unit: percent)
burden_score	float	0-100 burden composite: 50% min-max(log1p(complaints)) + 50% severity_score. Burden, not a defect rate. (unit: 0-100)
burden_rank	integer	Deterministic rank: burden_score desc, then complaint_count desc, make_slug, model_slug, model_year desc. (unit: rank)
fetched_at	string	Trailing complete UTC day of the sweep. (unit: date)
row_hash	string	Deterministic 16-hex row hash.

10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.

model_year	make	make_slug	model	model_slug	vehicle_label	nhtsa_url	complaint_count	crash_count	fire_count	injury_total	death_total	severity_raw	severity_rate	severity_score	top_component	top_component_share_pct	n_distinct_components	complaints_yoy_pct	burden_score	burden_rank	fetched_at	row_hash
2 021	JEEP	jeep	Wrangler	wrangler	2021 Jeep Wrangler	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=JEEP&model=Wrangler&modelYear=2021	933	20	27	14	0	223	0,239	3,14	ELECTRICAL SYSTEM	32,48	30	—	51,57	1	2026-09-24	d58a8d82aec8ebdd
2 022	HONDA	honda	Civic	civic	2022 Honda Civic	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=HONDA&model=Civic&modelYear=2022	881	34	3	19	0	155	0,176	2,31	STEERING	82,97	21	511,81	50,59	2	2026-09-24	b9c07a9252c01e97
2 022	TESLA	tesla	Model 3	model-3	2022 Tesla Model 3	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=TESLA&model=Model+3&modelYear=2022	765	53	4	45	1	279	0,365	4,8	FORWARD COLLISION AVOIDANCE	69,54	24	15,38	50,44	3	2026-09-24	429364a0dfce17fd
2 021	MERCEDES-BENZ	mercedes-benz	G-Class	g-class	2021 Mercedes-Benz G-Class	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=MERCEDES-BENZ&model=G-Class&modelYear=2021	5	1	1	15	0	38	7,6	100	ENGINE	60	7	—	50	4	2026-09-24	716f77265da38d20
2 021	TESLA	tesla	Model 3	model-3	2021 Tesla Model 3	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=TESLA&model=Model+3&modelYear=2021	663	46	5	19	8	281	0,424	5,58	FORWARD COLLISION AVOIDANCE	61,39	24	—	49,41	5	2026-09-24	2951b948b107ec44
2 021	FORD	ford	Bronco Sport	bronco-sport	2021 Ford Bronco Sport	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=FORD&model=Bronco+Sport&modelYear=2021	691	18	17	12	0	163	0,236	3,1	ELECTRICAL SYSTEM	30,25	30	—	48,58	6	2026-09-24	8b6714a544d8c106
2 023	NISSAN	nissan	Rogue	rogue	2023 Nissan Rogue	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=NISSAN&model=Rogue&modelYear=2023	716	22	3	15	0	111	0,155	2,04	ENGINE	39,25	26	173,28	48,4	7	2026-09-24	9d3870d6e62fc252
2 021	RAM	ram	1500	1500	2021 Ram 1500	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=RAM&model=1500&modelYear=2021	678	27	4	23	0	147	0,217	2,85	ENGINE	40,71	30	—	48,27	8	2026-09-24	53f416d917cd321e
2 023	TESLA	tesla	Model 3	model-3	2023 Tesla Model 3	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=TESLA&model=Model+3&modelYear=2023	424	72	1	49	1	329	0,776	10,21	FORWARD COLLISION AVOIDANCE	41,75	24	-44,58	47,31	9	2026-09-24	e21a81d3edb60fad
2 023	HONDA	honda	HR-V	hr-v	2023 Honda HR-V	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=HONDA&model=HR-V&modelYear=2023	686	7	0	4	0	29	0,042	0,56	VISIBILITY	57,87	20	679,55	47,24	10	2026-09-24	8d720cbbee454e77

Profilé le 25 sept. 2026 à partir de l’instantané 20260925T185649Z-7025e10028b3

Mesuré

Complétude: 98,5 %
Lignes: 833
Colonnes: 23
Colonnes incomplètes: 1

Colonne	Manquant	Distinctes	Plage	Distribution
model_yearbigint	0 %	5	2 021 → 2 025médiane 2 023
makevarchar	0 %	43	—	TOYOTA61 KIA57 CHEVROLET56
make_slugvarchar	0 %	30	—	toyota61 kia57 chevrolet56
modelvarchar	0 %	282	—	35005 4Runner5 Acadia5
model_slugvarchar	0 %	259	—	35005 4runner5 acadia5
vehicle_labelvarchar	0 %	767	—	2021 Acura ILX1 2021 Acura RDX1 2021 Acura TLX1
nhtsa_urlvarchar	0 %	765	—	https://api.nhtsa.gov/complaints/complaintsByVehicle?make=ACURA&model=ADX&modelYear=20251 https://api.nhtsa.gov/complaints/complaintsByVehicle?make=ACURA&model=ILX&modelYear=20211 https://api.nhtsa.gov/complaints/complaintsByVehicle?make=ACURA&model=Integra&modelYear=20231
complaint_countbigint	0 %	271	5 → 933médiane 35	9 hors du 1er–99e centile
crash_countbigint	0 %	34	0 → 72médiane 2	9 hors du 1er–99e centile
fire_countbigint	0 %	17	0 → 27médiane 0	8 hors du 1er–99e centile
injury_totalbigint	0 %	30	0 → 54médiane 1	8 hors du 1er–99e centile
death_totalbigint	0 %	6	0 → 8médiane 0	3 hors du 1er–99e centile
severity_rawdouble	0 %	137	0 → 329médiane 12	9 hors du 1er–99e centile
severity_ratedouble	0 %	412	0 → 7,6médiane 0,2857	7 hors du 1er–99e centile
severity_scoredouble	0 %	379	0 → 100médiane 3,76	7 hors du 1er–99e centile
top_componentvarchar	0 %	21	—	ELECTRICAL SYSTEM224 UNKNOWN OR OTHER134 ENGINE112
top_component_share_pctdouble	0 %	392	14,29 → 100médiane 36,15	18 hors du 1er–99e centile
n_distinct_componentsbigint	0 %	32	2 → 36médiane 15	8 hors du 1er–99e centile
complaints_yoy_pctdouble	35,4 %	379	-96,12 → 1 683médiane -28,37	12 hors du 1er–99e centile
burden_scoredouble	0 %	516	0 → 51,57médiane 20,97	9 hors du 1er–99e centile
burden_rankbigint	0 %	1 001	1 → 833médiane 417	18 hors du 1er–99e centile
fetched_atvarchar	0 %	1	—	2026-09-24833
row_hashvarchar	0 %	964	—	004feb9b8dcb48131 006dcbd434dbf9e81 007f3bd7b45ce0031

Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/nhtsa_vehicle_signals/nhtsa_vehicle_complaint_monthly" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/nhtsa_vehicle_signals/nhtsa_vehicle_complaint_monthly").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

Point d’accès API : https://datazimuts.com/v1/datasets/nhtsa_vehicle_signals/nhtsa_vehicle_complaint_monthly

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.

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APA

NHTSA vehicle complaint intelligence (agent-curated). (2026). NHTSA vehicle complaint intelligence (monthly) [Data set, snapshot 20260925T185649Z-7025e10028b3, sha256 7025e10028b3]. Datazimuts. Retrieved 2026-09-25, from https://datazimuts.com/fr/datasets/nhtsa_vehicle_signals/nhtsa_vehicle_complaint_monthly?snapshot=20260925T185649Z-7025e10028b3

BibTeX

@misc{dz_nhtsa_vehicle_signals_nhtsa_vehicle_comp_7025e100,
  title        = {{NHTSA vehicle complaint intelligence (monthly)}},
  author       = {{NHTSA vehicle complaint intelligence (agent-curated)}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/fr/datasets/nhtsa_vehicle_signals/nhtsa_vehicle_complaint_monthly?snapshot=20260925T185649Z-7025e10028b3}},
  note         = {Snapshot 20260925T185649Z-7025e10028b3, sha256 7025e10028b3a762eaf83f3acdfc4104c5e1a0b92be12a8a20e3b76d56f61592; accessed 2026-09-25}
}

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HTML

<iframe src="https://datazimuts.com/embed/chart?dataset=nhtsa_vehicle_signals%2Fnhtsa_vehicle_complaint_monthly&lang=fr&theme=auto&snapshot=20260925T185649Z-7025e10028b3&x=model_year&y=model_year&agg=avg" title="NHTSA vehicle complaint intelligence (monthly)" width="100%" height="380" style="border:0" loading="lazy"></iframe>

NHTSA vehicle complaint intelligence (monthly)

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