If you're a data point in this report, call us.
We'll evaluate whether you have a case. Free, and no pressure.
ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · APRIL 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/april-2022-report
Monthly Traffic Safety Analysis
7,901 CRASHES IN
CONNECTICUT, CT
APRIL 2022
In April 2022, there were 7,901 total crashes, an increase of 9.9% from the 7,188 crashes recorded in April 2021. While total crashes and injuries rose, the most notable year-over-year shift was a decrease in traffic fatalities, which fell from 31 to 23.
7,901
▲ 9.9%was 7,188
Total Crash Events
23
▼ -25.8%was 31
Persons Killed
2,744
▲ 9.5%was 2,507
Persons Injured
1,013
▼ -3.1%was 1,045
Hit-and-Run Crashes
Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crashes in April 2022 increased by 9.9% compared to the same month in the prior year, rising from 7,188 to 7,901. This upward trend was also reflected in the number of injuries, which grew from 2,507 to 2,744. In contrast, the number of fatalities decreased from 31 in April 2021 to 23 in April 2022.
1,013
Hit-and-Run Crashes — April 2022
▼ -3.1% vs prior (1,045)
Both the total count and the rate of hit-and-run crashes decreased in April 2022 compared to the previous year. The number of hit-and-run incidents fell from 1,045 to 1,013. The hit-and-run rate, which measures the proportion of all crashes classified as hit-and-runs, also trended downward from 14.5% in April 2021 to 12.8% in April 2022.
Vulnerable Road User Casualties
2
Pedestrians Killed
1
Cyclists Killed
20
Motorists Killed
72
Pedestrians Injured
27
Cyclists Injured
2,645
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · 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 consistent year-over-year. In both April 2022 and April 2021, Friday was the peak day for crashes (1,580 and 1,422, respectively) and the 3 p.m. hour was the peak time for collisions (684 and 664, respectively). The overall increase in crashes was distributed across the week, with most days showing higher volumes in the current period.
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes decreased from the prior year. The fatal crash rate fell from 0.39% in April 2021 to 0.24% in April 2022, with the number of fatal crashes dropping from 28 to 19. The proportion of crashes involving serious injuries also declined from 1.8% to 1.1%. The overall percentage of crashes resulting in any type of injury remained stable at approximately 25% for both periods.
Severity is per crash event (most severe injury). 19 fatal crash events resulted in 23 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes across different environmental conditions was largely similar between the two periods. In both years, the majority of collisions occurred in daylight (76.3% in 2022 vs. 75.9% in 2021) and on dry road surfaces (84.3% vs. 86.1%). There was a slight proportional increase in crashes occurring during rain, which accounted for 11.2% of crashes in April 2022 compared to 9.6% in April 2021.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes and the age demographics of persons involved remained consistent year-over-year. Honda, Toyota, and Ford were the top three makes in both April 2022 and April 2021, with their involvement counts increasing in line with the overall rise in crashes. The 26-34 age group consistently represented the largest share of individuals involved in collisions in both periods.
Top Vehicle Makes (15,145 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records
1,290 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (17,909 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events
Speed Limit Zones
Year-over-year, there was a shift in crashes toward higher speed zones. The number of crashes in zones posted at 40 mph or higher increased from 2,249 in April 2021 to 2,630 in April 2022. While total fatalities decreased, the prior year saw fatal crashes concentrated in zones of 35 mph (6 fatalities) and 40 mph (5 fatalities), a pattern that was less pronounced in the current period.
Fatal crashes by zone: 1 mph: 1 of 1,042 (0.096%) · 25 mph: 3 of 2,182 (0.137%) · 30 mph: 5 of 592 (0.845%) · 35 mph: 3 of 880 (0.341%) · 40 mph: 2 of 444 (0.45%) · 45 mph: 2 of 299 (0.669%) · 50 mph: 2 of 245 (0.816%) · 55 mph: 1 of 799 (0.125%)
Source: Connecticut Crash Data · Csv Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2022-04-01 through 2022-04-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 7,901
- Total persons involved: 19,265
- Total vehicles involved: 15,145
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: April 2022." Published August 20, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/april-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: 2022-04-01 – 2022-04-30
Generated: August 20, 2026 · All rights reserved
The data is step one. Get a Connecticut attorney on the line.
Call our intake team. We connect you to a vetted Connecticut personal injury attorney who calls you back within minutes. No phone tag. No voicemails.
Always free for accident victims.