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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · AUGUST 2022
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-2022-report
Monthly Traffic Safety Analysis
8,251 CRASHES IN
CONNECTICUT, CT
AUGUST 2022
In August 2022, Connecticut recorded 8,251 traffic crashes, a 6.3% decrease from the 8,802 crashes documented in August 2021. While overall collisions, injuries (2,904 vs. 3,145), and fatalities (26 vs. 33) all declined year-over-year, one of the most notable shifts was a significant increase in crashes involving vulnerable road users. Collisions involving bicyclists rose by 41.7% and pedestrian-involved crashes increased by 17.2%.
8,251
▼ -6.3%was 8,802
Total Crash Events
26
▼ -21.2%was 33
Persons Killed
2,904
▼ -7.7%was 3,145
Persons Injured
1,069
▼ -4.1%was 1,115
Hit-and-Run Crashes
Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety metrics showed a general improvement in August 2022 compared to the previous year. Total crashes fell by 6.3%, from 8,802 to 8,251. This downward trend was also reflected in crash outcomes, with total injuries decreasing by 7.7% and fatalities dropping by 21.2%.
1,069
Hit-and-Run Crashes — August 2022
▼ -4.1% vs prior (1,115)
The absolute number of hit-and-run crashes decreased from 1,115 in August 2021 to 1,069 in August 2022. However, as a percentage of all crashes, the hit-and-run rate trended slightly upward. These incidents constituted 13.0% of all crashes in the current period, an increase from the 12.7% rate observed in the prior year.
Vulnerable Road User Casualties
6
Pedestrians Killed
1
Cyclists Killed
19
Motorists Killed
91
Pedestrians Injured
29
Cyclists Injured
2,784
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak time for crashes remained consistent, with the 4 p.m. hour having the most incidents in both August 2022 (753 crashes) and August 2021 (789 crashes). The peak day of the week shifted from Tuesday (1,411 crashes) in the prior year to Wednesday (1,384 crashes) in the current period. Crashes on Sundays saw a notable year-over-year decrease from 1,117 to 847.
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity of crashes lessened slightly between August 2021 and August 2022. The fatal crash rate decreased from 0.35% to 0.32%, with 26 fatal crashes recorded in the current period compared to 31 in the prior. The proportion of crashes resulting in a serious injury saw a slight increase from 1.3% to 1.7%, while the share of no-injury crashes remained stable at approximately 74% for both periods.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Most severe injury per crash record
Road & Environmental Conditions
In both periods, the vast majority of crashes occurred in daylight on dry roads with clear weather. However, the proportion of crashes in adverse conditions was lower in August 2022 compared to the prior year. Crashes on wet roads accounted for 6.0% of the total, down from 10.4% in August 2021. Similarly, collisions during rain fell from 8.0% of all crashes to 4.0% year-over-year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes were consistent across both periods, led by Honda, Toyota, and Ford. In August 2022, Toyota (1,615 vehicles) surpassed Ford (1,312 vehicles) to become the second-most frequent make, swapping places from August 2021 when Ford ranked second. The number of vehicles involved in crashes from each of the top makes generally decreased, in line with the overall reduction in collisions.
Top Vehicle Makes (15,622 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Vehicle unit records
1,336 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (18,404 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · Person-level records linked to crash events
Speed Limit Zones
The 25 mph speed zone was the site of the most crashes in both periods, though the count dropped from 2,508 in August 2021 to 2,395 in August 2022. Despite this drop, fatal crashes in the 25 mph zone increased from 5 to 7. Crashes in 55 mph zones also decreased from 1,023 to 825, with fatalities in that zone falling from 4 to 2. Conversely, the 35 mph zone saw fatalities increase from 2 to 5, even as total crashes in the zone decreased.
Fatal crashes by zone: 25 mph: 7 of 2,395 (0.292%) · 30 mph: 3 of 632 (0.475%) · 35 mph: 5 of 867 (0.577%) · 40 mph: 4 of 447 (0.895%) · 45 mph: 2 of 309 (0.647%) · 50 mph: 2 of 197 (1.015%) · 55 mph: 2 of 825 (0.242%) · 65 mph: 1 of 522 (0.192%)
Source: Connecticut Crash Data · Csv Open Data · 2022-08-01 to 2022-08-31 · 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: 2022-08-01 through 2022-08-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2022-08-01 through 2022-08-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,251
- Total persons involved: 19,945
- Total vehicles involved: 15,622
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 2022." Published August 20, 2026. Reporting period: 2022-08-01 to 2022-08-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/august-2022-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: 2022-08-01 – 2022-08-31
Generated: August 20, 2026 · All rights reserved
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