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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JANUARY 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/january-2022-report
Monthly Traffic Safety Analysis
9,087 CRASHES IN
CONNECTICUT, CT
JANUARY 2022
In January 2022, Connecticut recorded 9,087 vehicle crashes, a 34.7% increase from the 6,745 crashes reported in January 2021. This rise was accompanied by an increase in total fatalities from 19 to 27 year-over-year. The most notable shift was the substantial increase in crashes occurring on icy or freezing road surfaces, which rose from 126 incidents in 2021 to 1,495 in 2022.
9,087
▲ 34.7%was 6,745
Total Crash Events
27
▲ 42.1%was 19
Persons Killed
2,514
▲ 20.1%was 2,094
Persons Injured
1,042
▲ 2.8%was 1,014
Hit-and-Run Crashes
Note: "Persons Killed" (27) counts individual fatalities across all crash events. "Fatal" in the severity table below (24) 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 2022-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in Connecticut show a substantial year-over-year increase for January. Total crashes rose by 34.7%, from 6,745 in January 2021 to 9,087 in January 2022. Similarly, total injuries increased by 20.1% (from 2,094 to 2,514), and fatalities rose from 19 to 27.
1,042
Hit-and-Run Crashes — January 2022
▲ 2.8% vs prior (1,014)
While the absolute number of hit-and-run crashes saw a slight increase from 1,014 in January 2021 to 1,042 in January 2022, the hit-and-run rate decreased significantly. Hit-and-runs constituted 11.5% of all crashes in the current period, down from 15.0% in the prior year. This indicates that although total crashes rose, the proportion of those crashes that were hit-and-runs trended downward.
Vulnerable Road User Casualties
8
Pedestrians Killed
0
Cyclists Killed
19
Motorists Killed
104
Pedestrians Injured
7
Cyclists Injured
2,403
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between January 2021 and January 2022. The peak day for crashes moved from Tuesday (1,166 crashes) in the prior year to Wednesday (2,095 crashes) in the current period. More notably, the peak hour for collisions changed from the 5 p.m. hour in 2021 (631 crashes) to the 7 a.m. hour in 2022 (907 crashes), indicating a shift from evening to morning commute times.
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the absolute number of fatal crashes increased from 18 to 24 year-over-year, the fatal crash rate remained stable, slightly decreasing from 0.27% to 0.26%. The proportion of crashes resulting in any level of injury decreased across all categories (Serious, Minor, and Possible). Consequently, no-injury crashes made up a larger share of the total, rising from 76.9% in January 2021 to 78.9% in January 2022.
Severity is per crash event (most severe injury). 24 fatal crash events resulted in 27 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record
Road & Environmental Conditions
The proportion of crashes on adverse road surfaces increased significantly in January 2022 compared to the previous year. Crashes on 'Ice / Frost' surfaces rose from 126 to 1,495, and those on 'Wet' surfaces increased from 460 to 1,014. This corresponds with a major increase in crashes reported during 'Freezing Rain or Freezing Drizzle,' which jumped from 55 incidents in 2021 to 1,018 in 2022. Consequently, the share of crashes on 'Dry' roads fell from 80.6% to 60.3%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes remained consistent year-over-year, with Honda, Toyota, and Ford leading in both January 2021 and January 2022. The number of vehicles from each of these top makes involved in crashes increased, reflecting the overall rise in collisions. The age distribution of persons involved in crashes also showed little proportional change, with all age groups maintaining a similar share of the total compared to the prior year.
Top Vehicle Makes (16,626 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records
1,376 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,133 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes increased across all speed zones in January 2022 compared to the prior year, with the largest absolute increase occurring in zones posted at 25 mph or less (+979 crashes). The fatal crash rate saw notable increases in specific zones; in 35 mph zones, the rate more than doubled from 0.237% to 0.584%, and in 65 mph zones, it more than tripled from 0.313% to 1.035%. Conversely, the fatal crash rate in 30 mph zones remained relatively stable.
Fatal crashes by zone: 25 mph: 5 of 2,819 (0.177%) · 30 mph: 5 of 805 (0.621%) · 35 mph: 6 of 1,028 (0.584%) · 45 mph: 1 of 335 (0.299%) · 50 mph: 1 of 254 (0.394%) · 65 mph: 5 of 483 (1.035%)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-01-31 · 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 2022-01-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-01-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,087
- Total persons involved: 20,571
- Total vehicles involved: 16,626
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: January 2022." Published August 20, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/january-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: 2022-01-01 – 2022-01-31
Generated: August 20, 2026 · All rights reserved
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