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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
1,997 CRASHES IN
CONNECTICUT, CT
2022
In 2022, Windham County recorded 1,997 total crashes, a 3.8% increase from the 1,923 crashes reported in 2021. The most significant year-over-year change was a substantial increase in fatalities, which rose from 16 in 2021 to 31 in 2022.
1,997
▲ 3.8%was 1,923
Total Crash Events
31
▲ 93.8%was 16
Persons Killed
731
▼ -2.4%was 749
Persons Injured
208
▼ -6.7%was 223
Hit-and-Run Crashes
Note: "Persons Killed" (31) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) 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 traffic crashes in Windham County trended upward, increasing by 3.8% from 1,923 in 2021 to 1,997 in 2022. While total injuries saw a slight decrease of 2.4% to 731, the number of fatalities nearly doubled, rising from 16 to 31 year-over-year.
208
Hit-and-Run Crashes — 2022
▼ -6.7% vs prior (223)
Hit-and-run incidents decreased in both count and as a proportion of total crashes in 2022 compared to the previous year. There were 208 hit-and-run crashes recorded in 2022, down from 223 in 2021. This corresponds to a drop in the hit-and-run rate from 11.6% of all crashes in 2021 to 10.4% in 2022.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
29
Motorists Killed
22
Pedestrians Injured
5
Cyclists Injured
704
Motorists 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 (329 crashes) and 2021 (336 crashes). Similarly, the 3 p.m. hour was the peak time for collisions in both periods, with 184 crashes in 2022 and 171 in 2021. No significant shifts in daily or hourly crash distribution were observed between the two years.
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 worsened in 2022 compared to the prior year. The fatal crash rate increased from 0.8% of all crashes in 2021 to 1.3% in 2022, corresponding to a rise from 15 to 26 fatal incidents. While the proportion of serious and minor injury crashes remained stable, crashes categorized as 'Possible Injury' decreased from 10.2% to 8.4% of the total. Crashes resulting in no injury made up 72.1% of all incidents in 2022 versus 70.9% in 2021.
Severity is per crash event (most severe injury). 26 fatal crash events resulted in 31 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 crashes across different lighting and road surface conditions remained consistent between 2021 and 2022. In both years, approximately 67% of crashes occurred in daylight, and about 77% happened on dry road surfaces. Crashes in adverse weather, such as rain or snow, also constituted a similar proportion of total incidents in both periods, indicating no significant year-over-year shift in how environmental conditions related to crashes.
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
The top five vehicle makes involved in crashes remained consistent, with Ford leading in both 2022 (426 vehicles) and 2021 (438 vehicles). Toyota-made vehicles saw a notable increase in crash involvement, rising from 230 in 2021 to 317 in 2022. An analysis of persons involved in crashes shows a slight increase in the representation of the 65+ age group, which accounted for 11.1% of individuals in 2022, up from 9.8% in the prior year. The 26-34 age group saw a slight decrease in its share of involved persons, from 17.7% to 16.3%.
Top Vehicle Makes (3,322 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
200 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,037 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
Crashes in 2022 showed a shift toward higher speed zones compared to 2021, with increases in zones posted at 45 mph (from 237 to 267 crashes), 50 mph (from 45 to 58), and 65 mph (from 194 to 230). The fatal crash rate within the 50 mph speed zone increased significantly, with 7 of the 58 crashes (12.1%) in 2022 being fatal, compared to 2 of 45 crashes (4.4%) in 2021. Additionally, the 65 mph zone, which had no fatal crashes in 2021, recorded 4 fatal incidents in 2022.
Fatal crashes by zone: 25 mph: 1 of 572 (0.175%) · 30 mph: 3 of 222 (1.351%) · 35 mph: 5 of 287 (1.742%) · 40 mph: 1 of 196 (0.51%) · 45 mph: 5 of 267 (1.873%) · 50 mph: 7 of 58 (12.069%) · 65 mph: 4 of 230 (1.739%)
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 20, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 1,997
- Total persons involved: 4,339
- Total vehicles involved: 3,322
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 20, 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 20, 2026 · All rights reserved
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