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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · MAY 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/may-2022-report
Monthly Traffic Safety Analysis
8,774 CRASHES IN
CONNECTICUT, CT
MAY 2022
In May 2022, Connecticut recorded 8,774 vehicle crashes, a 3.4% increase from the 8,482 crashes reported in May 2021. While overall crash volume saw a modest rise, the most notable year-over-year change was a significant 37.0% increase in traffic fatalities, which grew from 27 to 37.
8,774
▲ 3.4%was 8,482
Total Crash Events
37
▲ 37.0%was 27
Persons Killed
3,135
▲ 1.9%was 3,076
Persons Injured
1,200
▲ 2.3%was 1,173
Hit-and-Run Crashes
Note: "Persons Killed" (37) counts individual fatalities across all crash events. "Fatal" in the severity table below (29) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Connecticut for May 2022 were higher compared to the same month in the previous year. Total crashes increased by 3.4% from 8,482 to 8,774. This upward trend was also reflected in total injuries, which rose by 1.9% from 3,076 to 3,135, and total fatalities, which increased by 37.0% from 27 to 37.
1,200
Hit-and-Run Crashes — May 2022
▲ 2.3% vs prior (1,173)
The absolute number of hit-and-run crashes saw a small increase from 1,173 in May 2021 to 1,200 in May 2022. However, due to the overall increase in total crashes during the same period, the hit-and-run rate as a proportion of all crashes remained stable. The rate decreased marginally from 13.8% to 13.7% year-over-year.
Vulnerable Road User Casualties
3
Pedestrians Killed
1
Cyclists Killed
33
Motorists Killed
78
Pedestrians Injured
26
Cyclists Injured
3,031
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak hour for crashes remained consistent year-over-year at 3 PM, with the number of incidents during this hour increasing from 752 to 804. However, the peak day for crashes shifted. In May 2021, Saturday was the busiest day with 1,384 crashes, whereas in May 2022, the peak shifted to Tuesday, which saw 1,431 crashes.
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The proportion of fatal crashes remained stable at 0.3% of all incidents in both periods, although the absolute count of fatal crashes rose from 26 to 29. The share of crashes resulting in serious injuries decreased, falling from 1.6% of all crashes in May 2021 to 1.2% in May 2022. Correspondingly, the percentage of crashes with no reported injuries increased slightly from 73.3% to 73.9% year-over-year.
Severity is per crash event (most severe injury). 29 fatal crash events resulted in 37 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes across different environmental conditions showed little change between May 2021 and May 2022. In both periods, approximately 83% of crashes occurred in clear weather, and about 85% took place on dry road surfaces. Crashes in daylight accounted for 78.3% of the total in May 2022, a marginal increase from 77.3% in the prior year, with no significant shifts observed in crashes under adverse lighting or weather conditions.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles most frequently involved in crashes were consistent year-over-year, with Honda, Toyota, and Ford ranking as the top three in both May 2021 and May 2022. Analysis of the age of persons involved in crashes reveals a minor demographic shift. The proportion of individuals in the 26-34 age group decreased from 17.9% to 16.6%, while the share of those aged 65 and older increased from 8.8% to 9.5%.
Top Vehicle Makes (16,677 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
1,484 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,760 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events
Speed Limit Zones
The data indicates a slight shift in crashes toward higher speed zones, with an increase in incidents on roads with 55 mph and 65 mph limits. The most significant change occurred in the 45 mph zone, where the number of fatal crashes increased from 3 to 7, causing the fatality rate for that zone to more than double from 0.95% to 2.05%. In contrast, fatality rates in zones with posted limits of 25, 30, and 35 mph all decreased compared to the prior year.
Fatal crashes by zone: 1 mph: 1 of 1,088 (0.092%) · 25 mph: 6 of 2,556 (0.235%) · 30 mph: 3 of 719 (0.417%) · 35 mph: 3 of 924 (0.325%) · 40 mph: 3 of 493 (0.609%) · 45 mph: 7 of 342 (2.047%) · 50 mph: 1 of 223 (0.448%) · 55 mph: 1 of 845 (0.118%) · 65 mph: 4 of 469 (0.853%)
Source: Connecticut Crash Data · Csv Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2022-05-01 through 2022-05-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,774
- Total persons involved: 21,308
- Total vehicles involved: 16,677
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: May 2022." Published August 20, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/may-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: 2022-05-01 – 2022-05-31
Generated: August 20, 2026 · All rights reserved
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