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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · AUGUST 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/august-2024-report
Monthly Traffic Safety Analysis
8,589 CRASHES IN
CONNECTICUT, CT
AUGUST 2024
In August 2024, there were 8,589 total crashes, a 5.8% increase from the 8,120 crashes recorded in August 2023. This rise in collisions was accompanied by a significant year-over-year increase in traffic fatalities, which rose from 22 to 31. Despite the increase in total and fatal crashes, the number of reported injuries decreased slightly from 2,961 to 2,870.
8,589
▲ 5.8%was 8,120
Total Crash Events
31
▲ 40.9%was 22
Persons Killed
2,870
▼ -3.1%was 2,961
Persons Injured
1,097
▲ 11.8%was 981
Hit-and-Run Crashes
Note: "Persons Killed" (31) counts individual fatalities across all crash events. "Fatal" in the severity table below (30) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends show an increase in August 2024 compared to the same month in the prior year. Total crashes rose by 5.8%, from 8,120 to 8,589. Concurrently, traffic fatalities increased by 40.9% from 22 to 31, while total injuries saw a slight decrease of 3.1%.
1,097
Hit-and-Run Crashes — August 2024
▲ 11.8% vs prior (981)
Hit-and-run incidents increased in both volume and as a percentage of total crashes. The number of hit-and-run crashes rose from 981 in August 2023 to 1,097 in August 2024. This represents an increase in the hit-and-run rate from 12.1% to 12.8% of all crashes, indicating a worsening trend for this type of incident.
Vulnerable Road User Casualties
4
Pedestrians Killed
0
Cyclists Killed
26
Motorists Killed
1
Other Killed
94
Pedestrians Injured
32
Cyclists Injured
2,744
Motorists Injured
0
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · 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 between August 2023 and August 2024. The day with the highest number of crashes moved from Tuesday (1,337 crashes) in the prior year to Friday (1,578 crashes) in the current period. The peak hour for collisions also shifted slightly, moving from 4 p.m. in 2023 (725 crashes) to 3 p.m. in 2024 (731 crashes).
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate increased from 0.27 per 100 crashes in August 2023 to 0.35 in August 2024, with the absolute number of fatal crashes rising from 22 to 30. The proportion of serious injury crashes also saw a slight increase from 1.3% to 1.4% of all incidents. Conversely, the combined share of minor and possible injury crashes decreased from 25.1% in the prior year to 22.5% in the current period.
Severity is per crash event (most severe injury). 30 fatal crash events resulted in 31 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes across different environmental conditions remained largely consistent year-over-year. In August 2024, 83.6% of crashes occurred on dry roads and 76.4% happened in daylight, compared to 84.7% and 77.9% respectively in August 2023. There was a minor increase in the proportion of crashes occurring on wet roads, which accounted for 15.7% of incidents in the current period versus 14.5% in the prior year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Road surface condition field
Vehicles & Demographics
The demographic profile of vehicles and persons involved in crashes showed little change year-over-year. The top five vehicle makes involved in collisions remained identical in both August 2024 and August 2023, with Honda, Toyota, and Ford leading in both periods. Similarly, the age distribution of persons involved in crashes was consistent, with the 26-34 and 35-44 age groups representing the largest shares in both years.
Top Vehicle Makes (16,301 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Vehicle unit records
1,227 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,208 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes increased across most speed zones, with a notable rise in incidents occurring in zones posted at 50 mph or higher. In August 2024, there were 1,839 crashes in these higher-speed zones, up from 1,589 in the prior year. A significant change in fatal crash distribution was observed in the 45 mph zone, which recorded 6 fatal crashes in the current period compared to zero in August 2023. The 25 mph and 35 mph zones also continued to account for a high number of fatal crashes, with 5 and 7 respectively.
Fatal crashes by zone: 25 mph: 5 of 2,397 (0.209%) · 30 mph: 5 of 628 (0.796%) · 35 mph: 7 of 976 (0.717%) · 40 mph: 2 of 454 (0.441%) · 45 mph: 6 of 311 (1.929%) · 50 mph: 1 of 232 (0.431%) · 55 mph: 1 of 971 (0.103%) · 65 mph: 3 of 636 (0.472%)
Source: Connecticut Crash Data · Csv Open Data · 2024-08-01 to 2024-08-31 · 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: 2024-08-01 through 2024-08-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2024-08-01 through 2024-08-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,589
- Total persons involved: 20,690
- Total vehicles involved: 16,301
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: August 2024." Published August 20, 2026. Reporting period: 2024-08-01 to 2024-08-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/august-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: 2024-08-01 – 2024-08-31
Generated: August 20, 2026 · All rights reserved
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