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Yearly Traffic Safety Analysis

83,791 CRASHES IN
CONNECTICUT, CT
2020

All metrics benchmarked against2019

In 2020, Connecticut recorded 83,791 total traffic crashes, a 25.6% decrease from the 112,611 crashes reported in 2019. Despite the significant reduction in overall collisions, the number of fatalities increased. The most notable year-over-year shift was a 16.8% rise in total fatalities, from 256 in 2019 to 299 in 2020.

83,791

▼ -25.6%was 112,611

Total Crash Events

299

▲ 16.8%was 256

Persons Killed

29,211

▼ -21.7%was 37,323

Persons Injured

11,833

▼ -6.6%was 12,668

Hit-and-Run Crashes

Note: "Persons Killed" (299) counts individual fatalities across all crash events. "Fatal" in the severity table below (287) 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 traffic incidents, with total crashes falling by 25.6% from 112,611 in 2019 to 83,791 in 2020. Similarly, total injuries declined by 21.7% from 37,323 to 29,211. However, this downward trend did not extend to the most severe outcomes, as total fatalities increased by 16.8% during the same period.

11,833

Hit-and-Run Crashes — 2020

▼ -6.6% vs prior (12,668)

The total number of hit-and-run crashes saw a slight decrease from 12,668 in 2019 to 11,833 in 2020. Despite this drop in raw numbers, the hit-and-run rate as a percentage of all crashes trended upwards. In 2020, hit-and-run incidents accounted for 14.1% of all crashes, an increase from the 11.2% rate recorded in the prior year.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 56↑10.7%

Cyclists Killed

Prior: 3↑100.0%

231

Motorists Killed

Prior: 197↑17.3%

Other Killed

Prior: 0→0.0%

971

Pedestrians Injured

Prior: 1,382↓-29.7%

350

Cyclists Injured

Prior: 413↓-15.3%

27,880

Motorists Injured

Prior: 35,517↓-21.5%

Other Injured

Prior: 11↓-9.1%

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 day for crashes remained Friday in both 2020 (14,240 crashes) and 2019 (18,856 crashes). However, the peak hour for collisions shifted two hours earlier, moving from 5 p.m. in 2019 to 3 p.m. in 2020. The number of crashes during the new 3 p.m. peak was 7,005, down from the 9,852 crashes seen at the 5 p.m. peak in 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 severity of those crashes increased from 2019 to 2020. The fatal crash rate rose from 0.21% to 0.34% of all crashes. The proportion of crashes resulting in serious injuries also increased from 1.0% to 1.3%, and minor injury crashes grew from 9.5% to 11.1% of the total. Consequently, the share of crashes with no injuries decreased from 75.7% in 2019 to 74.3% in 2020.

Severity is per crash event (most severe injury). 287 fatal crash events resulted in 299 persons killed.

Outcome by Severity (Crash Events)

Fatal287fatal crashes0.3%

↑20.6%prior 238

Serious Injury1,108serious injury crashes1.3%

↓-4.5%prior 1,160

Minor Injury9,274minor injury crashes11.1%

↓-13.6%prior 10,731

Possible Injury10,882possible injury crashes13%

↓-28.6%prior 15,237

No Injury62,240no injury crashes74.3%

↓-27.0%prior 85,245

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 environmental conditions during crashes remained largely stable between 2019 and 2020. In 2020, 81.4% of crashes occurred in clear weather and 67.3% during daylight, compared to 78.9% and 70.1% respectively in the prior year. Crashes on dry road surfaces accounted for 80.9% of the total in 2020, a slight proportional increase from 78.5% in 2019. There were no significant shifts in the proportions of crashes occurring in adverse conditions.

Weather

Clear68,180 (81.9%)

↓-23.3%prior 88,865

Rain8,265 (9.9%)

↓-32.1%prior 12,167

Cloudy4,345 (5.2%)

↓-31.3%prior 6,323

Snow1,459 (1.8%)

↓-41.0%prior 2,473

Freezing Rain or Freezing Drizzle337 (0.4%)

↓-68.7%prior 1,078

Fog, Smog, Smoke307 (0.4%)

↑17.6%prior 261

Blowing Snow217 (0.3%)

↓-35.4%prior 336

Other74 (0.1%)

↓-28.8%prior 104

Severe Crosswinds69 (0.1%)

↑16.9%prior 59

Sleet or Hail28 (0.0%)

↓-90.6%prior 297

Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight56,380 (67.9%)

↓-28.6%prior 78,949

Dark-Lighted18,426 (22.2%)

↓-18.1%prior 22,508

Dark-Not Lighted5,562 (6.7%)

↓-19.6%prior 6,921

Dusk1,356 (1.6%)

↓-20.3%prior 1,702

Dawn609 (0.7%)

↓-27.8%prior 843

Dark-Unknown Lighting554 (0.7%)

↓-9.3%prior 611

Other178 (0.2%)

↑4.1%prior 171

Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry67,807 (81.4%)

↓-23.3%prior 88,366

Wet12,760 (15.3%)

↓-28.5%prior 17,855

Snow1,385 (1.7%)

↓-42.4%prior 2,404

Ice / Frost724 (0.9%)

↓-60.3%prior 1,822

Slush382 (0.5%)

↓-66.8%prior 1,152

Mud, Dirt, Gravel91 (0.1%)

↓-24.8%prior 121

Other56 (0.1%)

↓-26.3%prior 76

Standing Water47 (0.1%)

↓-21.7%prior 60

Moving Water45 (0.1%)

↑18.4%prior 38

Sand18 (0.0%)

↓-81.4%prior 97

Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

The composition of vehicles and persons involved in crashes showed little change year-over-year. The top five vehicle makes involved in collisions were identical in both periods: Honda, Toyota, Ford, Nissan, and Chevrolet, maintaining their respective ranks. Similarly, the age distribution of all persons involved in crashes remained consistent, with no single age group showing a significant proportional increase or decrease from 2019 to 2020.

Top Vehicle Makes (156,447 vehicles)

HONDA16,839 (10.8%)

↓-25.2%prior 22,512

TOYOTA14,955 (9.6%)

↓-29.0%prior 21,069

FORD13,949 (8.9%)

↓-28.2%prior 19,434

NISSAN12,946 (8.3%)

↓-24.7%prior 17,197

CHEVROLET9,312 (6%)

↓-24.7%prior 12,360

JEEP6,328 (4%)

↓-26.4%prior 8,598

SUBARU6,058 (3.9%)

↓-29.9%prior 8,636

HYUNDAI5,764 (3.7%)

↓-23.5%prior 7,531

DODGE3,679 (2.4%)

↓-26.6%prior 5,011

BMW3,220 (2.1%)

↓-25.1%prior 4,300

Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

15,403 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (184,079 persons with recorded sex)

Male106,002 (57.6%)

↓-26.5%prior 144,160

Female78,075 (42.4%)

↓-33.5%prior 117,439

02 (0.0%)

→0.0%prior 2

Source: Connecticut Crash Data · Csv Open Data · 2020-01-01 to 2020-12-31 · Person-level records linked to crash events

Speed Limit Zones

While the total number of crashes decreased across most speed zones from 2019 to 2020, the fatal crash rate within these zones generally increased. In 25 mph zones, crashes fell from 34,785 to 27,068, but the fatal crash percentage rose from 0.132% to 0.229%. This trend was more pronounced in higher speed zones; the fatal rate in 55 mph zones more than tripled from 0.159% to 0.533%, and nearly doubled in 65 mph zones from 0.422% to 0.811%.

Fatal crashes by zone: 1 mph: 10 of 10,003 (0.1%) · 15 mph: 1 of 625 (0.16%) · 25 mph: 62 of 27,068 (0.229%) · 30 mph: 37 of 6,951 (0.532%) · 35 mph: 44 of 9,949 (0.442%) · 40 mph: 27 of 4,776 (0.565%) · 45 mph: 26 of 3,180 (0.818%) · 50 mph: 9 of 2,024 (0.445%) · 55 mph: 33 of 6,188 (0.533%) · 65 mph: 32 of 3,948 (0.811%) · 88 mph: 2 of 5,514 (0.036%) · 99 mph: 1 of 465 (0.215%)

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 20, 2026

Data Coverage

Reporting period: 2020-01-01 through 2020-12-31 (366 days)
Geographic scope: connecticut, CT
Total crash records analyzed: 83,791
Total persons involved: 198,626
Total vehicles involved: 156,447

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 20, 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

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