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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · 2020
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/2020-annual-report
Yearly Traffic Safety Analysis
5,228 CRASHES IN
CONNECTICUT, CT
2020
In New London County, total vehicle crashes decreased by 20.9% from 6,606 in 2019 to 5,228 in 2020. This overall reduction in incidents was accompanied by a 37.1% drop in fatalities, from 35 to 22, and a 14.1% decrease in total injuries. The most notable shift was a significant increase in the hit-and-run rate, which rose from 11.9% to 14.9% of all crashes, even as the absolute number of such incidents remained stable.
5,228
▼ -20.9%was 6,606
Total Crash Events
22
▼ -37.1%was 35
Persons Killed
1,639
▼ -14.1%was 1,908
Persons Injured
780
▼ -0.5%was 784
Hit-and-Run Crashes
Note: "Persons Killed" (22) counts individual fatalities across all crash events. "Fatal" in the severity table below (21) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety data for New London County indicates a significant downward trend in collisions year-over-year. Total crashes fell from 6,606 in 2019 to 5,228 in 2020, representing a 20.9% reduction. This trend extended to crash outcomes, with total fatalities dropping from 35 to 22 and injuries decreasing from 1,908 to 1,639.
780
Hit-and-Run Crashes — 2020
▼ -0.5% vs prior (784)
While the absolute number of hit-and-run incidents was nearly identical year-over-year, with 780 in 2020 versus 784 in 2019, the rate saw a significant increase. Because total crashes declined, the proportion of hit-and-run crashes rose from 11.9% of all collisions in 2019 to 14.9% in 2020. This indicates a rising trend in the hit-and-run rate.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
19
Motorists Killed
48
Pedestrians Injured
28
Cyclists Injured
1,563
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak hour for crashes was consistent at 4 p.m. for both 2019 and 2020, although the number of crashes during that hour fell from 639 to 459. The peak day of the week for collisions shifted from Tuesday (1,051 crashes) in 2019 to Friday (853 crashes) in 2020. Overall, crash volumes were lower across all days of the week in 2020 compared to the prior year.
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, the proportion of crashes resulting in an injury increased year-over-year. The rate of fatal crashes saw a slight decline from 0.44% of all crashes in 2019 to 0.40% in 2020. However, the share of crashes involving serious injuries rose from 0.8% to 1.1%, and minor injury crashes increased their proportion from 10.6% to 12.0% of the total.
Severity is per crash event (most severe injury). 21 fatal crash events resulted in 22 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes across different environmental conditions remained largely consistent year-over-year, with most incidents in both periods occurring in clear weather on dry roads. There was a minor proportional shift in lighting conditions, as crashes during daylight hours decreased from 70.3% of the total in 2019 to 66.8% in 2020. Concurrently, the share of crashes occurring in dark, lighted conditions increased from 16.6% to 18.9%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in collisions, led by Ford, Toyota, and Honda, remained the same in 2020 as in 2019, though the counts for each decreased in line with the overall trend. An analysis of persons involved in crashes shows a stable age distribution, with one exception. The proportion of individuals in the 21-25 age group increased from 10.3% of all persons involved in 2019 to 11.5% in 2020.
Top Vehicle Makes (9,292 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records
986 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (11,225 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Person-level records linked to crash events
Speed Limit Zones
The overall distribution of crashes by speed zone was similar between the two periods. However, there was a notable shift in the severity of crashes in lower speed zones. In areas with a posted speed limit of 25 mph or less, the number of fatal crashes rose from 1 in 2019 to 7 in 2020. In contrast, fatal crashes in mid-range (30-50 mph) speed zones fell from 22 to 10, and fatalities in zones over 50 mph decreased from 6 to 4.
Fatal crashes by zone: 15 mph: 1 of 65 (1.538%) · 25 mph: 6 of 1,899 (0.316%) · 30 mph: 3 of 352 (0.852%) · 35 mph: 1 of 922 (0.108%) · 40 mph: 1 of 206 (0.485%) · 45 mph: 4 of 488 (0.82%) · 50 mph: 1 of 93 (1.075%) · 65 mph: 4 of 569 (0.703%)
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · 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: 2020-01-01 through 2020-12-31
- Report generated: August 22, 2026
Data Coverage
- Reporting period: 2020-01-01 through 2020-12-31 (366 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 5,228
- Total persons involved: 12,070
- Total vehicles involved: 9,292
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: 2020." Published August 22, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2020-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: 2020-01-01 – 2020-12-31
Generated: August 22, 2026 · All rights reserved
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