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 · JUNE 2024
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-2024-report
Monthly Traffic Safety Analysis
8,964 CRASHES IN
CONNECTICUT, CT
JUNE 2024
In June 2024, Connecticut recorded 8,964 total vehicle crashes, a 9.0% increase from the 8,221 crashes documented in June 2023. The total number of injuries rose by 5.9% to 3,059. The most significant year-over-year change was a 44.4% rise in total fatalities, which increased from 27 in the prior period to 39 in the current period.
8,964
▲ 9.0%was 8,221
Total Crash Events
39
▲ 44.4%was 27
Persons Killed
3,059
▲ 5.9%was 2,889
Persons Injured
1,133
▲ 10.8%was 1,023
Hit-and-Run Crashes
Note: "Persons Killed" (39) counts individual fatalities across all crash events. "Fatal" in the severity table below (35) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for June 2024 indicates an upward trend across key metrics compared to the same month in the prior year. Total crashes rose by 9.0% from 8,221 to 8,964. Similarly, total injuries increased by 5.9% (from 2,889 to 3,059), and fatalities saw a substantial 44.4% increase (from 27 to 39).
1,133
Hit-and-Run Crashes — June 2024
▲ 10.8% vs prior (1,023)
Hit-and-run incidents increased in both absolute numbers and as a percentage of total crashes. In June 2024, there were 1,133 hit-and-run crashes, up from 1,023 in June 2023, representing a 10.7% increase in volume. The hit-and-run rate also trended upward, rising from 12.4% to 12.6% of all crashes year-over-year.
Vulnerable Road User Casualties
12
Pedestrians Killed
0
Cyclists Killed
27
Motorists Killed
82
Pedestrians Injured
38
Cyclists Injured
2,939
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · 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 a shift in the peak day of the week, moving from Friday (1,610 crashes) in June 2023 to Saturday (1,425 crashes) in June 2024. The peak hour for collisions remained consistent at 4 p.m. in both periods, though the number of crashes during this hour increased from 711 to 794 year-over-year.
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes increased in June 2024 compared to the previous year. The number of fatal crashes rose from 27 to 35, and their proportion of all crashes increased from 0.3% to 0.4%. Crashes involving serious injuries also saw an increase in both count (from 106 to 128) and proportion (from 1.3% to 1.4%). While crashes with minor injuries increased from 995 to 1,103, their share of total crashes remained stable at approximately 12%.
Severity is per crash event (most severe injury). 35 fatal crash events resulted in 39 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record
Road & Environmental Conditions
The majority of crashes in both periods occurred in clear weather and on dry roads. In June 2024, 90.9% of crashes happened in clear weather, up from 86.2% in June 2023. Crashes on dry road surfaces accounted for 91.8% of the total in the current period, a slight increase from 90.0% in the prior period. The proportion of crashes occurring during daylight hours remained stable, at 79.7% in June 2024 compared to 80.5% in June 2023.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent year-over-year: Honda, Toyota, and Ford, with all three seeing an increase in total counts in June 2024. The age distribution of persons involved in crashes also showed general stability. The 26-34 age group continued to represent the largest share of individuals in both periods, accounting for 16.5% in June 2024 and 16.3% in June 2023. The representation of persons aged 65 and older saw a slight proportional increase, from 10.8% to 11.2% of all persons involved.
Top Vehicle Makes (16,977 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records
1,351 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (20,260 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crash counts increased across most speed zones in June 2024 compared to the prior year, with no major shift in the overall distribution of crashes by speed limit. The 25 mph zone continued to have the highest volume of crashes, rising from 2,364 to 2,520. The number of fatal crashes in the 25 mph zone increased from 9 to 13, and the fatality rate for that zone rose from 0.38% to 0.52%. In contrast, the 45 mph zone saw a decrease in fatal crashes from 5 to 3 year-over-year.
Fatal crashes by zone: 10 mph: 1 of 19 (5.263%) · 25 mph: 13 of 2,520 (0.516%) · 30 mph: 4 of 724 (0.552%) · 35 mph: 4 of 1,022 (0.391%) · 40 mph: 4 of 489 (0.818%) · 45 mph: 3 of 311 (0.965%) · 65 mph: 4 of 590 (0.678%) · 88 mph: 2 of 393 (0.509%)
Source: Connecticut Crash Data · Csv Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2024-06-01 through 2024-06-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,964
- Total persons involved: 21,882
- Total vehicles involved: 16,977
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 2024." Published August 20, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/june-2024-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: 2024-06-01 – 2024-06-30
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.