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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · OCTOBER 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/october-2024-report
Monthly Traffic Safety Analysis
9,449 CRASHES IN
CONNECTICUT, CT
OCTOBER 2024
In October 2024, Connecticut recorded 9,449 total crashes, a 1.0% increase from the 9,351 crashes reported in October 2023. While overall crash volume remained relatively stable, the number of fatalities rose significantly, increasing by 22.6% from 31 to 38 deaths year-over-year.
9,449
▲ 1.0%was 9,351
Total Crash Events
38
▲ 22.6%was 31
Persons Killed
3,121
▼ -2.4%was 3,198
Persons Injured
1,142
▲ 4.6%was 1,092
Hit-and-Run Crashes
Note: "Persons Killed" (38) counts individual fatalities across all crash events. "Fatal" in the severity table below (36) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year crash data for October indicates a relatively stable trend in total crash volume, with a slight 1.0% increase from 9,351 incidents in 2023 to 9,449 in 2024. However, the severity of these crashes worsened, as total fatalities increased by 22.6% to 38, while total injuries saw a minor decrease of 2.4% to 3,121.
1,142
Hit-and-Run Crashes — October 2024
▲ 4.6% vs prior (1,092)
Hit-and-run incidents increased in both absolute numbers and as a percentage of total crashes. In October 2024, there were 1,142 hit-and-run crashes, up from 1,092 in October 2023. This represents a 4.6% increase in count. The hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, also trended upward, rising from 11.7% to 12.1% year-over-year.
Vulnerable Road User Casualties
7
Pedestrians Killed
2
Cyclists Killed
29
Motorists Killed
146
Pedestrians Injured
53
Cyclists Injured
2,922
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted slightly between October 2023 and October 2024. The peak day for crashes moved from Tuesday (1,471 crashes) in the prior year to Thursday (1,634 crashes) in the current period. The peak hour also shifted one hour earlier, from the 4 p.m. hour in 2023 to the 3 p.m. hour in 2024, which saw 850 crashes. Notably, crashes on Sundays decreased from 1,319 to 947 year-over-year, while mid-week crashes on Wednesday and Thursday saw increases.
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased in October 2024 compared to the same month in 2023. The number of fatal crashes rose from 28 to 36, and the fatal crash rate per 100 crashes increased from 0.30 to 0.38. Similarly, crashes resulting in serious injuries grew from 113 (1.2% of total) to 131 (1.4% of total). The proportion of crashes involving minor or possible injuries slightly decreased from 23.4% to 22.7%, while no-injury crashes remained proportionally stable at approximately 75% of all incidents.
Severity is per crash event (most severe injury). 36 fatal crash events resulted in 38 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record
Road & Environmental Conditions
Environmental conditions were markedly different between the two periods. In October 2024, crashes overwhelmingly occurred in clear weather (96.2%) and on dry roads (97.1%). This contrasts sharply with October 2023, where a much higher proportion of crashes occurred during rain (12.9%) and on wet roads (16.5%). Despite the overall increase in total crashes and fatalities in the current period, they occurred under more favorable weather and road surface conditions. Lighting conditions remained proportionally similar year-over-year, with approximately 70% of crashes in both periods occurring during daylight.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Road surface condition field
Vehicles & Demographics
The composition of vehicles involved in crashes remained consistent year-over-year. In both October 2023 and October 2024, the most frequently involved vehicle makes were Honda, Toyota, and Ford, with their rankings and total counts showing minimal change. For instance, Hondas involved in crashes increased from 1,986 to 2,012, while Toyotas increased from 1,903 to 2,000. Analysis of persons involved shows a slight shift in age demographics, with the proportion of individuals in the 35-44 age group increasing from 15.5% to 16.3% of all persons involved.
Top Vehicle Makes (18,115 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records
1,395 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (21,635 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events
Speed Limit Zones
Analysis of crashes by posted speed limit reveals a shift towards higher speed zones in October 2024 compared to the prior year. Crashes in 55 mph zones increased from 860 to 1,017, and those in 65 mph zones rose from 560 to 658. Conversely, crashes in the 35 mph zone decreased from 1,093 to 989. Despite the drop in total crashes in the 35 mph zone, fatalities within it more than doubled from 3 to 7, indicating a higher severity for incidents in that specific speed zone this year.
Fatal crashes by zone: 25 mph: 9 of 2,649 (0.34%) · 30 mph: 3 of 741 (0.405%) · 35 mph: 7 of 989 (0.708%) · 40 mph: 1 of 602 (0.166%) · 45 mph: 5 of 379 (1.319%) · 55 mph: 3 of 1,017 (0.295%) · 65 mph: 5 of 658 (0.76%) · 88 mph: 2 of 368 (0.543%) · 99 mph: 1 of 24 (4.167%)
Source: Connecticut Crash Data · Csv Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2024-10-01 through 2024-10-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,449
- Total persons involved: 23,402
- Total vehicles involved: 18,115
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: October 2024." Published August 20, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/october-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: 2024-10-01 – 2024-10-31
Generated: August 20, 2026 · All rights reserved
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