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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/connecticut/statewide/2022-annual-report
Yearly Traffic Safety Analysis
29,549 CRASHES IN
CONNECTICUT, CT
2022
In 2022, New Haven County recorded 29,549 traffic crashes, a 1.4% increase from the 29,155 crashes documented in 2021. While the overall crash volume remained relatively stable, the number of resulting fatalities saw a significant year-over-year increase, rising 25.6% from 90 deaths in 2021 to 113 in 2022.
29,549
▲ 1.4%was 29,155
Total Crash Events
113
▲ 25.6%was 90
Persons Killed
10,378
▲ 0.1%was 10,370
Persons Injured
4,190
▼ -5.0%was 4,411
Hit-and-Run Crashes
Note: "Persons Killed" (113) counts individual fatalities across all crash events. "Fatal" in the severity table below (102) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in New Haven County showed a slight increase between 2021 and 2022. Total crashes rose by 1.4% from 29,155 to 29,549, while the number of injuries remained nearly flat with an increase of just eight individuals. However, fatalities experienced a significant upward trend, increasing by 25.6% from 90 in the prior year to 113 in the current year.
4,190
Hit-and-Run Crashes — 2022
▼ -5.0% vs prior (4,411)
The number and rate of hit-and-run crashes decreased from 2021 to 2022. The total count of hit-and-run incidents fell from 4,411 to 4,190. This corresponds to a drop in the hit-and-run rate, which declined from 15.1% of all crashes in 2021 to 14.2% in 2022.
Vulnerable Road User Casualties
23
Pedestrians Killed
2
Cyclists Killed
87
Motorists Killed
1
Other Killed
398
Pedestrians Injured
96
Cyclists Injured
9,882
Motorists Injured
2
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both 2022 (4,871 crashes) and 2021 (4,908 crashes). The peak hour for collisions shifted slightly later in the afternoon, moving from the 4 p.m. hour in 2021 (2,391 crashes) to the 5 p.m. hour in 2022 (2,415 crashes).
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes increased from 2021 to 2022. The number of fatal crashes rose from 86 to 102, and the fatal crash rate increased from 0.29% to 0.35%. Crashes resulting in serious injuries also grew in both count (from 384 to 417) and proportion (from 1.3% to 1.4% of all incidents). Conversely, the share of crashes involving minor or possible injuries saw a marginal decrease.
Severity is per crash event (most severe injury). 102 fatal crash events resulted in 113 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of environmental conditions during crashes remained stable between 2021 and 2022. In both periods, the vast majority of incidents occurred in clear weather (81.6% in 2022 vs. 82.0% in 2021) and on dry road surfaces (81.1% vs. 82.2%). Crashes during daylight hours consistently accounted for approximately 68% of the total in both years, indicating no significant shift in collisions attributed to adverse conditions.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
Vehicle and person demographics showed high stability year-over-year. The top five vehicle makes involved in crashes were Honda, Toyota, Nissan, Ford, and Chevrolet in both periods, with only a minor reordering of Toyota and Nissan for the second and third ranks. The age distribution of persons involved in crashes also saw minimal change, with the 26-34 age group remaining the largest single cohort in both 2021 and 2022.
Top Vehicle Makes (56,258 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
5,384 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (66,330 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Analysis of crashes by posted speed limit shows a mixed pattern between the two periods. The number of crashes in 25 mph zones decreased from 11,110 to 10,800, but the number of fatalities in these same zones increased from 25 to 37. Conversely, crashes on roads with 65 mph speed limits increased from 1,291 to 1,435, with fatalities nearly doubling from 6 to 11.
Fatal crashes by zone: 25 mph: 37 of 10,800 (0.343%) · 30 mph: 7 of 1,728 (0.405%) · 35 mph: 12 of 2,467 (0.486%) · 40 mph: 12 of 1,354 (0.886%) · 45 mph: 6 of 1,066 (0.563%) · 50 mph: 2 of 392 (0.51%) · 55 mph: 12 of 3,402 (0.353%) · 65 mph: 11 of 1,435 (0.767%) · 88 mph: 1 of 655 (0.153%)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Connecticut Crash Data, accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Csv Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2022-01-01 through 2022-12-31
- Report generated: August 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 29,549
- Total persons involved: 72,051
- Total vehicles involved: 56,258
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "connecticut, CT Crash Intelligence Report: 2022." Published August 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2022-annual-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Connecticut Crash Data · Csv
Period: 2022-01-01 – 2022-12-31
Generated: August 21, 2026 · All rights reserved
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