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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
24,505 CRASHES IN
CONNECTICUT, CT
2020
In New Haven County, total traffic crashes decreased by 22.4% from 31,594 in 2019 to 24,505 in 2020. Despite this significant drop in overall collisions, the most notable year-over-year change was a 25.8% increase in total fatalities, which rose from 66 to 83.
24,505
▼ -22.4%was 31,594
Total Crash Events
83
▲ 25.8%was 66
Persons Killed
8,948
▼ -21.1%was 11,346
Persons Injured
3,812
▼ -2.4%was 3,907
Hit-and-Run Crashes
Note: "Persons Killed" (83) counts individual fatalities across all crash events. "Fatal" in the severity table below (79) 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
The overall trend shows a substantial year-over-year decrease in the volume of crashes and injuries, which fell by 22.4% and 21.1% respectively. However, this was contrasted by a significant 25.8% increase in fatalities. This suggests that while fewer crashes occurred, the incidents that did happen were more severe on average.
3,812
Hit-and-Run Crashes — 2020
▼ -2.4% vs prior (3,907)
While the absolute number of hit-and-run crashes decreased slightly from 3,907 in 2019 to 3,812 in 2020, the hit-and-run rate trended upward. As a percentage of all crashes, hit-and-run incidents increased from 12.4% to 15.6% year-over-year. This indicates that a larger proportion of collisions involved a driver leaving the scene in 2020 compared to the prior year.
Vulnerable Road User Casualties
25
Pedestrians Killed
3
Cyclists Killed
55
Motorists Killed
300
Pedestrians Injured
130
Cyclists Injured
8,518
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 temporal patterns of crashes showed some consistency and some change year-over-year. Friday remained the peak day for crashes in both 2020 and 2019, though the volume on that day decreased from 5,419 to 4,188. The peak hour for collisions shifted two hours earlier, from 5 p.m. in 2019 (2,755 crashes) to 3 p.m. in 2020 (2,045 crashes).
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
Although total crashes declined, the severity of crashes increased from 2019 to 2020. The fatal crash rate rose from 0.2% to 0.32% of all crashes. The proportion of crashes resulting in serious injuries also grew from 1.1% to 1.3%, and minor injury crashes increased from 8.8% to 10.2% of the total. Consequently, the share of crashes with no reported injuries fell from 74.0% to 73.1%.
Severity is per crash event (most severe injury). 79 fatal crash events resulted in 83 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
Crash conditions remained largely consistent between the two periods, with the majority of incidents in both years occurring in clear weather on dry roads. There was a minor shift in lighting conditions; the proportion of crashes occurring in daylight decreased from 69.3% in 2019 to 66.4% in 2020. Correspondingly, the share of crashes in dark, lighted conditions increased from 21.4% to 23.5%.
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 five vehicle makes involved in crashes—Honda, Nissan, Toyota, Ford, and Chevrolet—were the same in both 2020 and 2019, with all seeing fewer total incidents. The demographic profile of persons involved in crashes also remained stable. The 26-34 age group was the largest single cohort in both years, accounting for approximately 18.1% of all individuals involved in collisions.
Top Vehicle Makes (46,243 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records
4,573 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (54,567 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
Year-over-year, a slightly larger proportion of crashes shifted to zones with posted speed limits of 35 mph or less. However, the fatal crash rate increased across several key speed zones. For example, in 35 mph zones, the fatal crash rate more than doubled from 0.357% in 2019 to 0.762% in 2020, and in 55 mph zones, it increased from 0.093% to 0.448%.
Fatal crashes by zone: 1 mph: 2 of 3,390 (0.059%) · 25 mph: 24 of 9,812 (0.245%) · 30 mph: 5 of 1,511 (0.331%) · 35 mph: 17 of 2,232 (0.762%) · 40 mph: 8 of 1,069 (0.748%) · 45 mph: 3 of 873 (0.344%) · 50 mph: 3 of 327 (0.917%) · 55 mph: 9 of 2,011 (0.448%) · 65 mph: 6 of 905 (0.663%)
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: 24,505
- Total persons involved: 58,746
- Total vehicles involved: 46,243
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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