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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
6,129 CRASHES IN
CONNECTICUT, CT
2022
In 2022, New London County recorded 6,129 total crashes, a 1.3% increase from the 6,052 crashes reported in 2021. While overall collisions saw a slight rise, the most significant year-over-year change was a 21.5% decrease in crashes where speeding was a factor, which fell from 632 in 2021 to 496 in 2022. Total injuries increased by 3.5% to 1,870, and fatalities rose from 28 to 29.
6,129
▲ 1.3%was 6,052
Total Crash Events
29
▲ 3.6%was 28
Persons Killed
1,870
▲ 3.5%was 1,806
Persons Injured
799
▼ -2.4%was 819
Hit-and-Run Crashes
Note: "Persons Killed" (29) counts individual fatalities across all crash events. "Fatal" in the severity table below (27) 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
Crash data for New London County indicates a slight upward trend year-over-year. Total crashes increased by 1.3%, from 6,052 in 2021 to 6,129 in 2022. Similarly, total injuries rose by 3.5% to 1,870, and fatalities increased by one, from 28 to 29.
799
Hit-and-Run Crashes — 2022
▼ -2.4% vs prior (819)
Hit-and-run incidents in New London County saw a slight decrease in 2022 compared to the prior year. The total number of hit-and-run crashes fell from 819 in 2021 to 799 in 2022. This corresponds to a decline in the hit-and-run rate, which dropped from 13.5% of all crashes in 2021 to 13.0% in 2022.
Vulnerable Road User Casualties
4
Pedestrians Killed
0
Cyclists Killed
25
Motorists Killed
0
Other Killed
61
Pedestrians Injured
16
Cyclists Injured
1,789
Motorists Injured
4
Other 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 in New London County remained consistent between 2021 and 2022. Friday was the peak day for crashes in both years, with 1,061 incidents in 2022 compared to 1,044 in 2021. The 3 PM hour was the single busiest hour in both periods, accounting for 606 crashes in 2022 and 559 in 2021, indicating no significant shift in the daily or hourly timing of collisions.
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 of crashes showed minimal change year-over-year. The fatal crash rate remained stable, moving from 0.43% of all crashes in 2021 to 0.44% in 2022. Crashes resulting in no injury decreased slightly as a proportion of the total, from 77.6% to 76.6%, while the share of crashes involving minor or possible injuries increased from a combined 20.5% to 21.7%.
Severity is per crash event (most severe injury). 27 fatal crash events resulted in 29 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
The environmental conditions at the time of crashes were largely consistent between 2021 and 2022. In both periods, approximately 81% of collisions occurred in clear weather and on dry road surfaces. Daylight crashes accounted for roughly 70% of the total in both years. There were no notable year-over-year shifts in the proportion of crashes occurring under adverse weather, lighting, or road surface 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 remained unchanged: Ford, Toyota, and Honda, though the number of Fords involved decreased from 1,330 in 2021 to 1,273 in 2022. An analysis of persons involved shows a shift in age demographics, with the proportion of individuals aged 16-20 decreasing from 10.7% to 9.5% of the total. Conversely, the 65+ age group saw their representation increase from 10.3% in 2021 to 11.6% in 2022.
Top Vehicle Makes (10,956 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
999 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (13,345 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
The distribution of crashes across speed zones showed some shifts between 2021 and 2022. While the number of crashes in 25 mph zones remained stable at over 2,200, there was a decrease in collisions in 35 mph zones (from 1,037 to 925) and 65 mph zones (from 729 to 670). The fatal crash rate increased in several key zones; for instance, the rate in 25 mph zones rose from 0.045% to 0.225%, and the rate in 65 mph zones increased from 0.549% to 0.896%.
Fatal crashes by zone: 1 mph: 1 of 256 (0.391%) · 25 mph: 5 of 2,222 (0.225%) · 30 mph: 3 of 426 (0.704%) · 35 mph: 4 of 925 (0.432%) · 40 mph: 1 of 268 (0.373%) · 45 mph: 7 of 669 (1.046%) · 65 mph: 6 of 670 (0.896%)
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: 6,129
- Total persons involved: 14,395
- Total vehicles involved: 10,956
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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