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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JUNE 2023
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-2023-report
Monthly Traffic Safety Analysis
8,221 CRASHES IN
CONNECTICUT, CT
JUNE 2023
In June 2023, Connecticut recorded 8,221 traffic crashes, a 4.6% decrease from the 8,615 crashes reported in June 2022. The most significant year-over-year change was a 32.5% reduction in total fatalities, which fell from 40 to 27. Total injuries also saw a slight decline of 4.7%, from 3,031 to 2,889.
8,221
▼ -4.6%was 8,615
Total Crash Events
27
▼ -32.5%was 40
Persons Killed
2,889
▼ -4.7%was 3,031
Persons Injured
1,023
▼ -5.5%was 1,082
Hit-and-Run Crashes
Note: "Persons Killed" (27) counts individual fatalities across all crash events. "Fatal" in the severity table below (27) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety metrics showed a downward trend in June 2023 compared to the same month in the previous year. Total crashes decreased by 4.6% from 8,615 to 8,221. Similarly, total fatalities dropped by 32.5% (from 40 to 27), and total injuries fell by 4.7% (from 3,031 to 2,889).
1,023
Hit-and-Run Crashes — June 2023
▼ -5.5% vs prior (1,082)
Hit-and-run incidents showed a slight decrease in both count and rate in June 2023 compared to the prior year. The total number of hit-and-run crashes fell from 1,082 to 1,023. The corresponding rate, which measures hit-and-runs as a percentage of all crashes, also saw a minor decline from 12.6% in June 2022 to 12.4% in June 2023.
Vulnerable Road User Casualties
2
Pedestrians Killed
1
Cyclists Killed
24
Motorists Killed
69
Pedestrians Injured
36
Cyclists Injured
2,784
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between June 2022 and June 2023. The day with the most crashes changed from Wednesday (1,505 crashes) in the prior period to Friday (1,610 crashes) in the current period. The peak hour for collisions also shifted slightly, moving from 3 p.m. (757 crashes) in 2022 to 4 p.m. (711 crashes) in 2023.
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity decreased in June 2023 compared to the previous year. The number of fatal crashes fell from 37 to 27, and the fatal crash rate per 100 crashes dropped from 0.43 to 0.33. The proportion of crashes resulting in serious injuries also declined, from 1.7% to 1.3% of all incidents. Meanwhile, the share of crashes with no injuries increased slightly from 74.3% to 74.8%.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes by environmental conditions remained largely consistent year-over-year. In both June 2023 and June 2022, the vast majority of crashes occurred in daylight (around 80.5%) and on dry roads (around 90%). There was a slight decrease in the proportion of crashes happening during adverse weather, with incidents in the rain accounting for 5.5% of crashes in 2023, down from 7.6% in 2022. Similarly, crashes on wet road surfaces represented 9.2% of the total in the current period, compared to 9.9% in the prior period.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field
Vehicles & Demographics
The characteristics of vehicles and persons involved in crashes were very similar between June 2022 and June 2023. The top five vehicle makes remained unchanged, with Honda, Toyota, and Ford being the most frequently involved in both periods, though their total counts decreased slightly in 2023. The age distribution of individuals involved in crashes also showed a consistent pattern, with the 26-34 age group being the most represented in both years, decreasing from 3,566 individuals to 3,263.
Top Vehicle Makes (15,689 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records
1,281 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (18,598 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained consistent year-over-year, with the 25 mph zone accounting for the highest number of incidents in both June 2023 (2,364 crashes) and June 2022 (2,463 crashes). However, the number of fatal crashes in this zone increased from 7 to 9. In 2023, the 45 mph speed zone had the highest fatal crash rate at 1.64%, with 5 fatalities from 305 crashes. There was a notable decrease in fatalities in zones with speed limits of 55 mph or higher, falling from a total of 7 in 2022 to 3 in 2023.
Fatal crashes by zone: 1 mph: 1 of 1,079 (0.093%) · 25 mph: 9 of 2,364 (0.381%) · 30 mph: 3 of 627 (0.478%) · 35 mph: 1 of 953 (0.105%) · 40 mph: 3 of 454 (0.661%) · 45 mph: 5 of 305 (1.639%) · 50 mph: 2 of 174 (1.149%) · 55 mph: 1 of 801 (0.125%) · 65 mph: 2 of 532 (0.376%)
Source: Connecticut Crash Data · Csv Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2023-06-01 through 2023-06-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,221
- Total persons involved: 20,065
- Total vehicles involved: 15,689
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 2023." Published August 20, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/june-2023-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: 2023-06-01 – 2023-06-30
Generated: August 20, 2026 · All rights reserved
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