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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · MAY 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/may-2024-report
Monthly Traffic Safety Analysis
9,200 CRASHES IN
CONNECTICUT, CT
MAY 2024
In May 2024, Connecticut recorded 9,200 total traffic crashes, a 4.6% increase from the 8,796 crashes in May 2023. While total fatalities decreased from 29 to 27, the number of pedestrian fatalities increased from one to six year-over-year. The most notable shift was the increase in crashes occurring during rainy conditions, which more than doubled compared to the same period in the prior year.
9,200
▲ 4.6%was 8,796
Total Crash Events
27
▼ -6.9%was 29
Persons Killed
3,097
▲ 4.5%was 2,964
Persons Injured
1,195
▲ 8.8%was 1,098
Hit-and-Run Crashes
Note: "Persons Killed" (27) counts individual fatalities across all crash events. "Fatal" in the severity table below (23) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crashes in Connecticut trended upward in May 2024 compared to the previous year, increasing by 4.6% from 8,796 to 9,200 incidents. The number of injuries also rose by 4.5%, from 2,964 to 3,097. In contrast, total fatalities saw a slight decline of 6.9%, from 29 to 27.
1,195
Hit-and-Run Crashes — May 2024
▲ 8.8% vs prior (1,098)
Hit-and-run incidents increased in both volume and rate from the prior year. In May 2024, there were 1,195 hit-and-run crashes, up from 1,098 in May 2023. This represents an increase in the hit-and-run rate from 12.5% to 13.0% of all crashes.
Vulnerable Road User Casualties
6
Pedestrians Killed
1
Cyclists Killed
20
Motorists Killed
99
Pedestrians Injured
40
Cyclists Injured
2,958
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal pattern of crashes shifted slightly year-over-year. While the peak hour for collisions remained the 4 p.m. hour in both May 2023 (795 crashes) and May 2024 (838 crashes), the peak day for crashes moved from Wednesday (1,411 crashes) in the prior year to Friday (1,687 crashes) in the current period.
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity remained largely consistent between the two periods. Fatal crashes accounted for 0.3% of all incidents in both May 2023 and May 2024. The proportion of crashes resulting in serious injuries saw a minor decrease from 1.5% (130 crashes) to 1.3% (122 crashes) year-over-year, while no-injury crashes made up the vast majority in both periods (75.7% and 75.5%, respectively).
Severity is per crash event (most severe injury). 23 fatal crash events resulted in 27 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record
Road & Environmental Conditions
There was a marked increase in crashes occurring under adverse weather conditions in May 2024 compared to May 2023. The number of crashes in the rain more than doubled from 475 to 991, and collisions on wet road surfaces increased from 624 to 1,247. Consequently, the proportion of crashes on wet roads rose from 7.1% to 13.6% of the monthly total.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Honda, Toyota, and Ford—remained the same in both May 2023 and May 2024, with each seeing an increase in total incidents consistent with the overall trend. The distribution of persons involved in crashes by age group also showed no significant proportional changes year-over-year. The 26-34 age group consistently represented the largest cohort in both periods.
Top Vehicle Makes (17,577 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records
1,493 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (20,654 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed zone were the most frequent in both periods, with 2,618 incidents in May 2024 compared to 2,619 in May 2023. A notable increase occurred in the 1 mph zone (often representing parking lots), which saw crashes rise from 1,055 to 1,253. The highest fatal crash rate shifted from the 40 mph zone (1.17%) in the prior year to the 50 mph zone (0.8%) in the current year.
Fatal crashes by zone: 1 mph: 1 of 1,253 (0.08%) · 25 mph: 9 of 2,618 (0.344%) · 30 mph: 2 of 758 (0.264%) · 35 mph: 2 of 999 (0.2%) · 40 mph: 1 of 499 (0.2%) · 45 mph: 1 of 302 (0.331%) · 50 mph: 2 of 250 (0.8%) · 55 mph: 3 of 864 (0.347%) · 65 mph: 2 of 611 (0.327%)
Source: Connecticut Crash Data · Csv Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2024-05-01 through 2024-05-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,200
- Total persons involved: 22,416
- Total vehicles involved: 17,577
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: May 2024." Published August 20, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/may-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: 2024-05-01 – 2024-05-31
Generated: August 20, 2026 · All rights reserved
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