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Yearly Traffic Safety Analysis

28,906 CRASHES IN
CONNECTICUT, CT
2023

All metrics benchmarked against2022

In 2023, New Haven County recorded 28,906 total crashes, a 2.2% decrease from the 29,549 crashes documented in 2022. While overall collisions and injuries saw a slight decline, the most significant year-over-year change was a 34.5% reduction in total fatalities, which fell from 113 to 74.

28,906

▼ -2.2%was 29,549

Total Crash Events

▼ -34.5%was 113

Persons Killed

10,123

▼ -2.5%was 10,378

Persons Injured

4,095

▼ -2.3%was 4,190

Hit-and-Run Crashes

Note: "Persons Killed" (74) counts individual fatalities across all crash events. "Fatal" in the severity table below (72) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in New Haven County were downward from 2022 to 2023. Total crashes decreased by 2.2%, from 29,549 to 28,906. This trend extended to crash outcomes, with total injuries declining by 2.5% and total fatalities seeing a substantial 34.5% decrease.

4,095

Hit-and-Run Crashes — 2023

▼ -2.3% vs prior (4,190)

The trend for hit-and-run crashes in New Haven County remained stable year-over-year. The total number of hit-and-run incidents saw a minor decrease from 4,190 in 2022 to 4,095 in 2023. Despite this small drop in absolute numbers, the hit-and-run rate as a percentage of total crashes was unchanged at 14.2% for both periods.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 23↓-34.8%

Cyclists Killed

Prior: 2↓-50.0%

Motorists Killed

Prior: 87↓-33.3%

374

Pedestrians Injured

Prior: 398↓-6.0%

111

Cyclists Injured

Prior: 96↑15.6%

9,638

Motorists Injured

Prior: 9,882↓-2.5%

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · 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 Haven County remained largely consistent year-over-year. Friday was the peak day for crashes in both 2023 (4,800 crashes) and 2022 (4,871 crashes). The peak hour for collisions shifted slightly earlier, moving from 5 p.m. in 2022 (2,415 crashes) to 4 p.m. in 2023 (2,404 crashes).

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes in New Haven County decreased from 2022 to 2023. The fatal crash rate fell from 0.35% to 0.25%, with 30 fewer fatal crashes recorded. Crashes resulting in serious injuries also decreased proportionally from 1.4% to 1.2% of all incidents, while the share of non-injury crashes rose from 74.3% to 75.1%.

Severity is per crash event (most severe injury). 72 fatal crash events resulted in 74 persons killed.

Outcome by Severity (Crash Events)

Fatal72fatal crashes0.2%

↓-29.4%prior 102

Serious Injury350serious injury crashes1.2%

↓-16.1%prior 417

Minor Injury2,928minor injury crashes10.1%

↑1.5%prior 2,884

Possible Injury3,852possible injury crashes13.3%

↓-8.1%prior 4,192

No Injury21,704no injury crashes75.1%

↓-1.1%prior 21,954

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in 'Clear' weather (23,814 in 2023 vs. 24,121 in 2022) and on 'Dry' road surfaces (23,851 vs. 23,949). A notable shift occurred in winter-related conditions; crashes on snowy roads decreased from 524 to 234, and incidents on icy or frosty surfaces fell from 732 to 218. Conversely, crashes during rainfall increased from 2,818 in 2023 to 3,148.

Weather

Clear23,814 (82.8%)

↓-1.3%prior 24,121

Rain3,148 (10.9%)

↑11.7%prior 2,818

Cloudy1,243 (4.3%)

↑1.5%prior 1,225

Snow234 (0.8%)

↓-55.3%prior 524

Fog, Smog, Smoke171 (0.6%)

↑51.3%prior 113

Freezing Rain or Freezing Drizzle83 (0.3%)

↓-80.2%prior 419

Blowing Snow36 (0.1%)

↓-56.6%prior 83

Sleet or Hail15 (0.1%)

↓-70.6%prior 51

Other13 (0.0%)

↓-35.0%prior 20

Severe Crosswinds4 (0.0%)

↓-42.9%prior 7

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight19,781 (68.9%)

↓-1.6%prior 20,097

Dark-Lighted6,366 (22.2%)

↓-4.6%prior 6,674

Dark-Not Lighted1,680 (5.9%)

↓-3.4%prior 1,740

Dusk422 (1.5%)

↑19.9%prior 352

Dark-Unknown Lighting228 (0.8%)

↑19.4%prior 191

Dawn194 (0.7%)

↓-16.7%prior 233

Other25 (0.1%)

↑8.7%prior 23

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry23,851 (82.9%)

↓-0.4%prior 23,949

Wet4,459 (15.5%)

↑9.2%prior 4,085

Ice / Frost218 (0.8%)

↓-70.2%prior 732

Snow140 (0.5%)

↓-67.1%prior 425

Slush40 (0.1%)

↓-63.3%prior 109

Moving Water17 (0.1%)

↑112.5%prior 8

Mud, Dirt, Gravel15 (0.1%)

↓-21.1%prior 19

Standing Water13 (0.0%)

↑18.2%prior 11

Other10 (0.0%)

↓-16.7%prior 12

Sand7 (0.0%)

↓-79.4%prior 34

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes remained consistent between 2022 and 2023: Honda, Toyota, Nissan, Ford, and Chevrolet. Honda was the most common make in both years, though its involvement decreased from 6,969 vehicles to 6,559. The distribution of persons involved in crashes by age group also showed little change, with the 26-34 age bracket representing the largest cohort in both periods, accounting for 12,313 individuals in 2023 compared to 12,828 in 2022.

Top Vehicle Makes (55,269 vehicles)

HONDA6,559 (11.9%)

↓-5.9%prior 6,969

TOYOTA6,106 (11%)

↑3.5%prior 5,900

NISSAN4,726 (8.6%)

↓-1.1%prior 4,778

FORD4,670 (8.4%)

→0.0%prior 4,670

CHEVROLET3,881 (7%)

↓-2.9%prior 3,995

HYUNDAI2,742 (5%)

↓-0.7%prior 2,760

SUBARU2,535 (4.6%)

↑3.3%prior 2,455

JEEP2,342 (4.2%)

↓-1.7%prior 2,382

KIA1,456 (2.6%)

↑0.5%prior 1,449

DODGE1,225 (2.2%)

↓-5.6%prior 1,298

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

5,522 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (64,544 persons with recorded sex)

Male36,454 (56.5%)

↓-2.4%prior 37,368

Female28,090 (43.5%)

↓-3.0%prior 28,962

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones was largely unchanged from 2022 to 2023, with 25 mph zones accounting for the highest volume of incidents in both years (10,409 in 2023 vs. 10,800 in 2022). However, there was a significant reduction in fatalities within these zones. Fatalities in 25 mph zones fell from 37 to 25, while fatalities in 55 mph zones dropped from 12 to 3, and those in 65 mph zones decreased from 11 to 5.

Fatal crashes by zone: 1 mph: 1 of 4,571 (0.022%) · 25 mph: 25 of 10,409 (0.24%) · 30 mph: 7 of 1,557 (0.45%) · 35 mph: 8 of 2,482 (0.322%) · 40 mph: 9 of 1,178 (0.764%) · 45 mph: 4 of 933 (0.429%) · 50 mph: 6 of 340 (1.765%) · 55 mph: 3 of 3,327 (0.09%) · 65 mph: 5 of 1,339 (0.373%) · 88 mph: 1 of 723 (0.138%) · 99 mph: 2 of 36 (5.556%)

Source: Connecticut Crash Data · Csv Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
Report generated: August 21, 2026

Data Coverage

Reporting period: 2023-01-01 through 2023-12-31 (365 days)
Geographic scope: connecticut, CT
Total crash records analyzed: 28,906
Total persons involved: 70,536
Total vehicles involved: 55,269

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: 2023." Published August 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2023-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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