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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · FEBRUARY 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/february-2022-report
Monthly Traffic Safety Analysis
7,695 CRASHES IN
CONNECTICUT, CT
FEBRUARY 2022
In February 2022, Connecticut recorded 7,695 motor vehicle crashes, a 4.9% increase from the 7,338 crashes documented in February 2021. While total crashes saw a modest rise, the most notable year-over-year shift was a doubling in traffic fatalities, which increased from 14 to 28.
7,695
▲ 4.9%was 7,338
Total Crash Events
28
▲ 100.0%was 14
Persons Killed
2,366
▲ 24.1%was 1,906
Persons Injured
966
▼ -4.5%was 1,011
Hit-and-Run Crashes
Note: "Persons Killed" (28) counts individual fatalities across all crash events. "Fatal" in the severity table below (22) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends worsened in February 2022 compared to the previous year. Total crashes increased by 4.9% from 7,338 to 7,695. More significantly, the number of injuries rose by 24.1% from 1,906 to 2,366, and fatalities doubled from 14 to 28.
966
Hit-and-Run Crashes — February 2022
▼ -4.5% vs prior (1,011)
The total number of hit-and-run crashes decreased from 1,011 in February 2021 to 966 in February 2022. This decline is reflected in the hit-and-run rate, which fell from 13.8% of all crashes in the prior period to 12.6% in the current period.
Vulnerable Road User Casualties
5
Pedestrians Killed
0
Cyclists Killed
23
Motorists Killed
0
Other Killed
102
Pedestrians Injured
4
Cyclists Injured
2,259
Motorists Injured
1
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal pattern of crashes showed a slight shift year-over-year. In February 2022, Friday was the peak day for crashes with 1,244 incidents, changing from Thursday (1,195 crashes) in the prior year. The peak hour for collisions remained consistent at 3 p.m. in both periods, with a slight increase in crash volume from 591 to 623.
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased notably in February 2022 compared to the prior year. The fatal crash rate rose from 0.19 to 0.29 per 100 crashes. The number of crashes resulting in serious injuries more than doubled from 45 to 98. Consequently, the proportion of crashes with no reported injuries decreased from 80.2% in February 2021 to 76.8% in February 2022.
Severity is per crash event (most severe injury). 22 fatal crash events resulted in 28 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record
Road & Environmental Conditions
A significant difference in environmental conditions was observed between the two periods. In February 2022, 70.8% of crashes occurred on dry roads, compared to only 48.3% in February 2021. This corresponds with a major decrease in the share of crashes happening in snow conditions, which fell from 22.2% of all crashes in the prior year to just 5.1% in the current period. Lighting conditions remained broadly similar across both years, with daylight crashes accounting for 62.8% in 2022 and 64.6% in 2021.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes—Honda, Toyota, Ford, Nissan, and Chevrolet—remained the same across both periods with minimal change in their rank order. An analysis of persons involved in crashes indicates a shift in age demographics, with the 65+ age group accounting for 9.2% of individuals in February 2022, an increase from 7.8% in the prior year. Proportions for other age groups remained relatively stable.
Top Vehicle Makes (14,202 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records
1,232 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (16,715 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events
Speed Limit Zones
Year-over-year, crashes shifted proportionally toward higher speed zones. Collisions in zones posted at 55 mph or higher represented 21.5% of incidents in February 2022, up from 17.5% in the prior year. Conversely, the share of crashes in zones of 35 mph or less decreased from 71.0% to 61.9%. The number of fatal crashes in 40 mph zones increased from one to four, while the fatal crash rate in 65 mph zones decreased from 0.89% to 0.61%.
Fatal crashes by zone: 1 mph: 1 of 938 (0.107%) · 25 mph: 5 of 2,212 (0.226%) · 30 mph: 1 of 598 (0.167%) · 35 mph: 3 of 884 (0.339%) · 40 mph: 4 of 474 (0.844%) · 45 mph: 1 of 286 (0.35%) · 50 mph: 2 of 213 (0.939%) · 55 mph: 2 of 760 (0.263%) · 65 mph: 3 of 495 (0.606%)
Source: Connecticut Crash Data · Csv Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2022-02-01 through 2022-02-28 (28 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 7,695
- Total persons involved: 17,956
- Total vehicles involved: 14,202
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: February 2022." Published August 20, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/february-2022-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: 2022-02-01 – 2022-02-28
Generated: August 20, 2026 · All rights reserved
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