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 · 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
2,744 CRASHES IN
CONNECTICUT, CT
2024
In Tolland County, total traffic crashes increased by 8.3% from 2,533 in the prior period to 2,744 in the current period. Despite this rise in collisions, the number of resulting fatalities decreased from 16 to 13 year-over-year. The most significant proportional change was a 27.5% increase in crashes involving speeding, which rose from 338 to 431 incidents.
2,744
▲ 8.3%was 2,533
Total Crash Events
13
▼ -18.8%was 16
Persons Killed
887
▲ 7.4%was 826
Persons Injured
269
▲ 10.7%was 243
Hit-and-Run Crashes
Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) 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
Overall crash trends in Tolland County show an increase year-over-year. Total crashes rose by 8.3% (from 2,533 to 2,744), and the number of people injured increased by 7.4% (from 826 to 887). However, total fatalities saw a decline, dropping by 18.8% from 16 to 13.
269
Hit-and-Run Crashes — 2024
▲ 10.7% vs prior (243)
Hit-and-run crashes trended upward in both count and rate. The total number of hit-and-run incidents increased from 243 in the prior year to 269 in the current year. As a proportion of all crashes, the hit-and-run rate saw a slight increase from 9.6% to 9.8%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
12
Motorists Killed
23
Pedestrians Injured
3
Cyclists Injured
861
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 timing of crashes showed a slight shift between the two periods. The peak day for crashes moved from Friday (421 incidents) in the prior year to Thursday (436 incidents) in the current year. Similarly, the peak hour for collisions shifted later in the afternoon, from the 4 p.m. hour (251 crashes) in the prior period to the 5 p.m. hour (243 crashes) in the current period.
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
While total crashes increased, the severity of outcomes saw a slight improvement. The fatal crash rate decreased from 0.59% of all crashes in the prior period to 0.44% in the current period. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) remained stable, accounting for 24.5% of crashes in the current period compared to 24.7% in the prior period.
Severity is per crash event (most severe injury). 12 fatal crash events resulted in 13 persons killed.
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
Crash conditions varied slightly year-over-year, particularly concerning weather. The proportion of crashes occurring in snowy conditions more than doubled, rising from 2.7% of all crashes in the prior period to 5.9% in the current period, with absolute numbers increasing from 69 to 161. Conversely, the share of crashes on wet roads decreased from 17.7% to 13.9%. The distribution of crashes by lighting conditions remained largely unchanged, with daylight crashes accounting for approximately 68% in both periods.
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 top three vehicle makes involved in crashes remained consistent year-over-year: Toyota (541 current vs. 484 prior), Ford (532 vs. 475), and Honda (479 vs. 459). Subaru moved into the fourth position with 318 crashes, displacing Nissan (279 crashes). Analysis of persons involved shows the 26-34 age group was the largest in both periods, while the 16-20 age group saw a notable increase in involvement from 834 individuals to 986.
Top Vehicle Makes (4,770 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
222 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (5,845 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
Crash distribution across speed zones shifted toward lower-speed roads. Collisions in zones of 30 mph or less increased from 873 to 1,012 year-over-year. Fatal crashes in 40 mph and 50 mph zones, which accounted for 5 deaths in the prior period, dropped to zero in the current period. However, four new fatalities were recorded in 25 mph and 30 mph zones, where none had occurred previously.
Fatal crashes by zone: 25 mph: 2 of 388 (0.515%) · 30 mph: 2 of 394 (0.508%) · 35 mph: 4 of 614 (0.651%) · 45 mph: 2 of 353 (0.567%) · 65 mph: 2 of 312 (0.641%)
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 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 2,744
- Total persons involved: 6,246
- Total vehicles involved: 4,770
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 21, 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 21, 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.