Monthly Traffic Safety Analysis

1,742 CRASHES IN
CONNECTICUT, CT
MARCH 2026

All metrics benchmarked againstMarch 2025

In March 2026, there were 1,742 total crashes, a 76.6% decrease from the 7,435 crashes recorded in March 2025. This substantial drop in overall crash volume was the most notable year-over-year shift. Despite the reduction in total incidents, the proportion of crashes resulting in an injury increased dramatically, and the fatal crash rate more than doubled from 0.24% to 0.63%.

1,742

▼ -76.6%was 7,435

Total Crash Events

11

▼ -42.1%was 19

Persons Killed

2,189

▼ -5.0%was 2,303

Persons Injured

171

▼ -82.8%was 997

Hit-and-Run Crashes

Note: "Persons Killed" (11) counts individual fatalities across all crash events. "Fatal" in the severity table below (11) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a significant year-over-year decrease in traffic incidents. Total crashes fell by 76.6%, from 7,435 to 1,742. Similarly, fatalities decreased by 42.1% (from 19 to 11), and total injuries saw a modest 5.0% decline (from 2,303 to 2,189).

171

Hit-and-Run Crashes — March 2026

▼ -82.8% vs prior (997)

Both the count and rate of hit-and-run incidents decreased significantly in March 2026 compared to the previous year. The number of hit-and-run crashes fell from 997 to 171. The hit-and-run rate also trended downward, dropping from 13.4% of all crashes in March 2025 to 9.8% in March 2026.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 4↓-75.0%

0

Cyclists Killed

Prior: 1↓-100.0%

10

Motorists Killed

Prior: 14↓-28.6%

60

Pedestrians Injured

Prior: 76↓-21.1%

17

Cyclists Injured

Prior: 19↓-10.5%

2,112

Motorists Injured

Prior: 2,208↓-4.3%

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Monday (1,216 crashes) in the prior year to Tuesday (349 crashes) in the current period. The peak hour also shifted two hours earlier, from 4 p.m. (660 crashes) in March 2025 to 2 p.m. (147 crashes) in March 2026.

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total fatalities decreased from 19 to 11, the crashes that occurred in March 2026 were substantially more severe on average. The fatal crash rate more than doubled, rising from 0.24% in the prior year to 0.63% in the current period. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) increased dramatically from 22.9% of all crashes in March 2025 to 93.9% in March 2026.

Outcome by Severity (Crash Events)

Fatal11fatal crashes0.6%
↓-38.9%prior 18
Serious Injury116serious injury crashes6.7%
↑50.6%prior 77
Minor Injury776minor injury crashes44.5%
↓-5.6%prior 822
Possible Injury743possible injury crashes42.7%
↓-8.0%prior 808
No Injury96no injury crashes5.5%
↓-98.3%prior 5,710

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record

Road & Environmental Conditions

Year-over-year, a greater proportion of crashes occurred in adverse conditions. Crashes on wet road surfaces accounted for 18.8% of incidents in March 2026, up from 13.2% in the prior year. Similarly, crashes during rainfall made up 12.2% of the total, compared to 8.3% in March 2025. Consequently, the share of crashes occurring on dry roads and in clear weather decreased, from 85.7% to 75.6% and 84.6% to 78.0%, respectively.

Weather

Clear1,359 (78.1%)
↓-78.4%prior 6,288
Rain213 (12.2%)
↓-65.6%prior 620
Cloudy85 (4.9%)
↓-76.6%prior 363
Freezing Rain or Freezing Drizzle41 (2.4%)
↑28.1%prior 32
Fog, Smog, Smoke15 (0.9%)
↓-80.8%prior 78
Snow15 (0.9%)
Sleet or Hail8 (0.5%)
Other2 (0.1%)
↓-66.7%prior 6
Blowing Snow1 (0.1%)

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash

Lighting

Daylight1,178 (67.8%)
↓-78.3%prior 5,420
Dark-Lighted394 (22.7%)
↓-72.1%prior 1,412
Dark-Not Lighted126 (7.2%)
↓-66.8%prior 379
Dusk19 (1.1%)
↓-80.0%prior 95
Dark-Unknown Lighting11 (0.6%)
↓-76.1%prior 46
Dawn9 (0.5%)
↓-57.1%prior 21
Other1 (0.1%)
↓-91.7%prior 12

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field

Road Surface

Dry1,317 (75.7%)
↓-79.3%prior 6,374
Wet327 (18.8%)
↓-66.8%prior 984
Ice / Frost62 (3.6%)
↑313.3%prior 15
Slush21 (1.2%)
Snow8 (0.5%)
Sand2 (0.1%)
Other2 (0.1%)
Mud, Dirt, Gravel1 (0.1%)
↓-83.3%prior 6

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent year-over-year, with Honda, Toyota, and Ford leading in both periods. In March 2026, Honda (382 vehicles) narrowly surpassed Toyota (372 vehicles) for the most-involved make, reversing the order from March 2025 when Toyota led with 1,561 vehicles to Honda's 1,553. The proportion of crashes involving a 'Vehicle in Operation' slightly increased from 91.6% to 94.7%, while incidents involving parked vehicles decreased from 7.4% to 4.4% of all vehicles involved.

Top Vehicle Makes (3,326 vehicles)

1
HONDA382 (11.5%)
↓-75.4%prior 1,553
2
TOYOTA372 (11.2%)
↓-76.2%prior 1,561
3
FORD256 (7.7%)
↓-78.5%prior 1,193
4
NISSAN215 (6.5%)
↓-77.5%prior 954
5
CHEVROLET184 (5.5%)
↓-79.4%prior 895
6
SUBARU161 (4.8%)
↓-77.3%prior 709
7
JEEP149 (4.5%)
↓-75.9%prior 617
8
HYUNDAI146 (4.4%)
↓-75.0%prior 583
9
KIA100 (3%)
↓-74.6%prior 394
10
BMW81 (2.4%)
↓-76.9%prior 351

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records

188 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (4,302 persons with recorded sex)

Male2,388 (55.5%)
↓-74.2%prior 9,266
Female1,914 (44.5%)
↓-72.9%prior 7,073

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes decreased in all speed zones compared to the prior year, but the fatality rate within several zones increased. For instance, in 25 mph zones, the fatal crash rate rose from 0.37% (8 fatalities in 2,182 crashes) to 0.63% (3 fatalities in 473 crashes). A more significant increase occurred in 35 mph zones, where the fatal crash rate jumped from 0.24% to 1.33% year-over-year. The proportion of crashes occurring in lower speed zones (35 mph or less) saw a slight decrease from 65.7% to 62.1% of all speed-recorded incidents.

Fatal crashes by zone: 25 mph: 3 of 473 (0.634%) · 30 mph: 1 of 139 (0.719%) · 35 mph: 3 of 226 (1.327%) · 45 mph: 2 of 74 (2.703%) · 55 mph: 2 of 167 (1.198%)

Source: Connecticut Crash Data · Csv Open Data · 2026-03-01 to 2026-03-31 · 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: 2026-03-01 through 2026-03-31
  • Report generated: August 3, 2026

Data Coverage

  • Reporting period: 2026-03-01 through 2026-03-31 (31 days)
  • Geographic scope: connecticut, CT
  • Total crash records analyzed: 1,742
  • Total persons involved: 4,570
  • Total vehicles involved: 3,326

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: March 2026." Published August 3, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/march-2026-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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Connecticut (Statewide) Crash Report — March 2026 | ThatCarHitMe.com