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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · 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/2024-annual-report
Yearly Traffic Safety Analysis
2,236 CRASHES IN
CONNECTICUT, CT
2024
In Windham County, total traffic crashes increased from 2,046 in 2023 to 2,236 in 2024, representing a 9.3% rise. Despite the increase in overall collisions, the number of fatalities decreased from 13 to 8 over the same period. The most notable shift was the reduction in the fatal crash rate, which fell from 0.64% to 0.36% year-over-year.
2,236
▲ 9.3%was 2,046
Total Crash Events
8
▼ -38.5%was 13
Persons Killed
721
▲ 2.9%was 701
Persons Injured
258
▲ 20.0%was 215
Hit-and-Run Crashes
Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crash trends in Windham County show a notable increase year-over-year, with total collisions rising by 9.3% from 2,046 to 2,236. While the overall number of crashes grew, fatalities saw a significant decline of 38.5%, dropping from 13 in 2023 to 8 in 2024. The total number of injuries remained relatively stable, increasing by just 2.9%.
258
Hit-and-Run Crashes — 2024
▲ 20.0% vs prior (215)
Hit-and-run incidents increased in Windham County from 2023 to 2024, both in absolute numbers and as a proportion of total crashes. The total count of hit-and-run crashes rose from 215 to 258. The hit-and-run rate also trended upward, increasing from 10.5% in the prior year to 11.5% in the current year.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
5
Motorists Killed
14
Pedestrians Injured
8
Cyclists Injured
699
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Windham County remained consistent year-over-year. In both 2023 and 2024, Friday was the day with the highest number of crashes, with 343 and 360 incidents respectively. Similarly, the 3 p.m. hour was the peak time for collisions in both periods, recording 202 crashes in 2023 and 200 in 2024, indicating no significant shift in when crashes occurred.
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes in Windham County decreased from 2023 to 2024, even as total crashes rose. The fatal crash rate fell from 0.64% to 0.36%, and the proportion of crashes resulting in a serious injury dropped from 1.8% to 1.2%. This shift was accompanied by a corresponding increase in the share of 'No Injury' crashes, which grew from 73.5% to 75.3% of all collisions.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes by lighting conditions remained stable year-over-year, with daylight crashes accounting for 68.3% of the total in 2024 versus 66.8% in 2023. However, there was a notable shift in weather and road surface conditions, with crashes in snow more than doubling from 39 to 105. Conversely, the number of crashes in rain decreased from 245 to 203, and those on wet roads fell from 349 to 274.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes showed consistency between the two periods, with Ford, Toyota, Chevrolet, Nissan, and Honda remaining the top five most common makes in both years. Ford-made vehicles were the most frequently involved, with their count rising from 452 in 2023 to 516 in 2024. The age distribution of all persons involved in crashes also remained stable, with no significant shifts in the proportional representation of any age group year-over-year.
Top Vehicle Makes (3,761 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
200 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,409 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones saw a slight shift toward lower-speed roads, with collisions in zones of 35 mph or less accounting for 64.6% of incidents in 2024, up from 62.7% in 2023. In 2024, 6 of the 8 fatal crashes occurred in zones posted between 35 and 45 mph. This is a change from 2023, when the 13 fatal crashes were more broadly distributed across speed zones ranging from 20 mph to 65 mph.
Fatal crashes by zone: 25 mph: 1 of 619 (0.162%) · 35 mph: 2 of 309 (0.647%) · 40 mph: 3 of 203 (1.478%) · 45 mph: 1 of 264 (0.379%) · 50 mph: 1 of 41 (2.439%)
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 2,236
- Total persons involved: 4,828
- Total vehicles involved: 3,761
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: 2024." Published August 20, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: August 20, 2026 · All rights reserved
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