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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · 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/2022-annual-report
Yearly Traffic Safety Analysis
24,657 CRASHES IN
CONNECTICUT, CT
2022
In Hartford County, total traffic crashes remained relatively stable, with 24,657 incidents in 2022 compared to 24,486 in 2021, an increase of 0.7%. While overall crash and injury numbers saw little change, the most notable year-over-year shift was a 25% increase in pedestrian fatalities, which rose from 20 to 25. Total fatalities also increased from 89 in 2021 to 95 in 2022.
24,657
▲ 0.7%was 24,486
Total Crash Events
95
▲ 6.7%was 89
Persons Killed
9,105
▼ -1.3%was 9,225
Persons Injured
3,221
▼ -6.5%was 3,446
Hit-and-Run Crashes
Note: "Persons Killed" (95) counts individual fatalities across all crash events. "Fatal" in the severity table below (84) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for crashes in Hartford County was relatively stable, with total collisions increasing by just 0.7% from 24,486 in 2021 to 24,657 in 2022. While total injuries decreased by 1.3% from 9,225 to 9,105, the number of fatalities rose by 6.7%, from 89 to 95, indicating a slight increase in the lethality of crashes.
3,221
Hit-and-Run Crashes — 2022
▼ -6.5% vs prior (3,446)
The frequency of hit-and-run crashes in Hartford County showed a downward trend between the two periods. The total number of hit-and-run incidents fell from 3,446 in 2021 to 3,221 in 2022. This corresponds to a decrease in the hit-and-run rate, which dropped from 14.1% of all crashes in 2021 to 13.1% in 2022.
Vulnerable Road User Casualties
25
Pedestrians Killed
1
Cyclists Killed
69
Motorists Killed
260
Pedestrians Injured
53
Cyclists Injured
8,792
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed minor changes between the two periods. Friday remained the day with the highest number of crashes in both 2021 (4,036 crashes) and 2022 (4,175 crashes). However, the peak hour for collisions shifted slightly later in the day, from the 3 p.m. hour in 2021 (2,092 crashes) to the 4 p.m. hour in 2022 (2,135 crashes).
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity distribution of crashes remained similar year-over-year, with the fatal crash rate increasing marginally from 0.33% to 0.34%. The proportion of crashes involving serious injuries decreased slightly from 1.4% in 2021 to 1.3% in 2022. Concurrently, the share of crashes resulting in minor injuries increased from 12.3% to 13.3%, while possible injury crashes fell from 12.8% to 11.9% of the total.
Severity is per crash event (most severe injury). 84 fatal crash events resulted in 95 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions were largely consistent between 2022 and 2021, with no significant shifts in environmental factors. The vast majority of crashes in both periods occurred in clear weather (81.9% in 2022 vs. 80.5% in 2021) and on dry road surfaces (80.9% vs. 79.4%). Crashes in daylight accounted for 69.0% of incidents in 2022, nearly identical to the 68.7% reported in 2021, indicating stable patterns for lighting conditions.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Honda, Toyota, and Ford—remained the same in 2022 as in 2021, although the counts for all three decreased. An analysis of the age of persons involved in crashes shows that while the 26-34 age group was the largest in both years, there was a decrease in crash involvement for younger drivers aged 16-25. Conversely, the number of persons aged 65 and older involved in crashes increased from 5,600 in 2021 to 5,897 in 2022.
Top Vehicle Makes (46,623 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
3,873 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (57,185 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes remained most frequent in 25 mph, 35 mph, and 30 mph zones in both periods, with a slight decrease in total incidents within these zones in 2022. The distribution of fatal crashes, however, shifted; fatal crashes in the 65 mph zone decreased from 19 to 15 year-over-year. In contrast, fatal crashes in the 45 mph zone more than doubled from 3 to 7, and the 35 mph zone saw an increase from 11 to 14 fatal crashes.
Fatal crashes by zone: 1 mph: 1 of 1,392 (0.072%) · 25 mph: 6 of 3,955 (0.152%) · 30 mph: 18 of 2,611 (0.689%) · 35 mph: 14 of 3,862 (0.363%) · 40 mph: 10 of 2,079 (0.481%) · 45 mph: 7 of 764 (0.916%) · 50 mph: 8 of 1,850 (0.432%) · 55 mph: 3 of 1,027 (0.292%) · 65 mph: 15 of 2,219 (0.676%)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: August 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 24,657
- Total persons involved: 60,654
- Total vehicles involved: 46,623
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: 2022." Published August 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2022-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: 2022-01-01 – 2022-12-31
Generated: August 21, 2026 · All rights reserved
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