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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JUNE 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/june-2022-report
Monthly Traffic Safety Analysis
8,615 CRASHES IN
CONNECTICUT, CT
JUNE 2022
In June 2022, Connecticut recorded 8,615 total vehicle crashes, a 1.9% decrease from the 8,777 crashes reported in June 2021. Despite the overall decline in collisions, the number of fatalities increased significantly, rising from 33 in the prior year to 40 in the current period, representing a 21.2% year-over-year increase.
8,615
▼ -1.8%was 8,777
Total Crash Events
40
▲ 21.2%was 33
Persons Killed
3,031
▼ -5.7%was 3,215
Persons Injured
1,082
▼ -5.2%was 1,141
Hit-and-Run Crashes
Note: "Persons Killed" (40) counts individual fatalities across all crash events. "Fatal" in the severity table below (37) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash totals in Connecticut saw a slight year-over-year decline, falling by 162 incidents from 8,777 in June 2021 to 8,615 in June 2022. However, this decrease in total crashes was accompanied by a concerning rise in severity. The number of people killed increased by 21.2% (from 33 to 40), while total injuries reported saw a modest decrease of 5.7% (from 3,215 to 3,031).
1,082
Hit-and-Run Crashes — June 2022
▼ -5.2% vs prior (1,141)
Hit-and-run incidents showed a downward trend compared to the previous year. The total number of hit-and-run crashes decreased from 1,141 in June 2021 to 1,082 in June 2022. The hit-and-run rate, as a percentage of all crashes, also declined slightly from 13.0% to 12.6%.
Vulnerable Road User Casualties
6
Pedestrians Killed
0
Cyclists Killed
34
Motorists Killed
114
Pedestrians Injured
31
Cyclists Injured
2,886
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes remained largely consistent year-over-year. The peak hour for collisions in both June 2022 and June 2021 was the 3 p.m. hour, with 757 and 756 crashes respectively. The peak day of the week shifted slightly, from Tuesday (1,483 crashes) in the prior year to Wednesday (1,505 crashes) in the current period.
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, the severity of those crashes increased year-over-year. The number of fatal crashes rose from 33 to 37, and the total number of fatalities increased from 33 to 40. The proportion of crashes involving a serious injury also grew, accounting for 1.7% of all crashes (145 incidents) in June 2022, up from 1.3% (118 incidents) in June 2021.
Severity is per crash event (most severe injury). 37 fatal crash events resulted in 40 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions were very similar between the two periods, with the vast majority of incidents in both years occurring in clear weather on dry roads during daylight hours. In June 2022, 87.8% of crashes happened in clear weather, compared to 88.4% in the prior year. There was a slight corresponding increase in the proportion of crashes on wet roads, rising from 8.8% in June 2021 to 9.9% in June 2022.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, with Honda, Toyota, and Ford leading in both June 2022 and June 2021 with very similar involvement counts. The age distribution of persons involved in crashes also showed little change. The 26-34 age group was the most represented demographic in both periods, accounting for 3,566 individuals in the current year and 3,753 in the prior year.
Top Vehicle Makes (16,335 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records
1,345 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,637 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events
Speed Limit Zones
Year-over-year data shows a slight decrease in crashes in 25 mph zones (from 2,634 to 2,463) and a slight increase in 65 mph zones (from 471 to 514). More significantly, the number of fatalities in 65 mph zones doubled, increasing from 3 in June 2021 to 6 in June 2022. Fatalities in 25 mph zones also saw a small increase from 6 to 7.
Fatal crashes by zone: 1 mph: 1 of 1,028 (0.097%) · 25 mph: 7 of 2,463 (0.284%) · 30 mph: 4 of 669 (0.598%) · 35 mph: 3 of 981 (0.306%) · 40 mph: 6 of 464 (1.293%) · 45 mph: 4 of 322 (1.242%) · 50 mph: 3 of 233 (1.288%) · 55 mph: 1 of 889 (0.112%) · 65 mph: 6 of 514 (1.167%)
Source: Connecticut Crash Data · Csv Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2022-06-01 through 2022-06-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,615
- Total persons involved: 21,085
- Total vehicles involved: 16,335
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: June 2022." Published August 20, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/june-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: 2022-06-01 – 2022-06-30
Generated: August 20, 2026 · All rights reserved
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