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Monthly Traffic Safety Analysis

9,955 CRASHES IN
CONNECTICUT, CT
JUNE 2016

All metrics benchmarked againstJune 2015

In June 2016, Connecticut recorded 9,955 traffic crashes, an 8.8% increase from the 9,154 crashes reported in June 2015. This year-over-year rise was accompanied by a 15.9% increase in total injuries and a 23.8% increase in fatalities. Notably, crashes involving motorcycles saw a significant surge, increasing by 47% from 164 in the prior year to 241 in the current period.

9,955

8.8%was 9,154

Total Crash Events

26

23.8%was 21

Persons Killed

3,719

15.9%was 3,208

Persons Injured

1,060

8.5%was 977

Hit-and-Run Crashes

Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (25) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for June indicates a rising trend year-over-year. Total crashes increased by 8.8%, from 9,154 in June 2015 to 9,955 in June 2016. This upward trend extended to crash outcomes, with total injuries rising by 15.9% and fatalities increasing from 21 to 26.

1,060

Hit-and-Run Crashes — June 2016

8.5% vs prior (977)

The number of hit-and-run crashes increased from 977 in June 2015 to 1,060 in June 2016, reflecting the overall rise in total collisions. However, the rate of hit-and-run incidents as a proportion of all crashes remained stable. The hit-and-run rate was 10.6% in the current period, a slight decrease from 10.7% in the prior year, indicating that the frequency of these events grew proportionally with the total number of crashes.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 20.0%

1

Cyclists Killed

Prior: 0%

23

Motorists Killed

Prior: 1921.1%

0

Other Killed

Prior: 00.0%

110

Pedestrians Injured

Prior: 8627.9%

73

Cyclists Injured

Prior: 6119.7%

3,534

Motorists Injured

Prior: 3,05915.5%

2

Other Injured

Prior: 20.0%

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · 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 shifts between June 2015 and June 2016. The peak day for crashes moved from Tuesday (1,560 crashes) in the prior year to Wednesday (1,767 crashes) in the current period. While the 5 p.m. hour remained the most frequent time for collisions in both years, the number of crashes during this peak hour increased from 847 to 925.

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes increased in June 2016 compared to the previous year. Fatal crashes rose from 21 to 25, and their share of all crashes increased from 0.2% to 0.3%. Similarly, the proportion of crashes resulting in serious injuries grew from 1.4% to 1.7%. Conversely, the percentage of crashes with no reported injuries decreased from 74.8% to 73.5%, indicating a shift toward more severe outcomes.

Severity is per crash event (most severe injury). 25 fatal crash events resulted in 26 persons killed.

Outcome by Severity (Crash Events)

Fatal25fatal crashes0.3%
19.0%prior 21
Serious Injury168serious injury crashes1.7%
28.2%prior 131
Minor Injury1,063minor injury crashes10.7%
18.9%prior 894
Possible Injury1,379possible injury crashes13.9%
9.6%prior 1,258
No Injury7,320no injury crashes73.5%
6.9%prior 6,850

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Most severe injury per crash record

Road & Environmental Conditions

A notable shift occurred in the reported environmental conditions for crashes year-over-year. In June 2016, a significantly higher proportion of crashes occurred in clear weather (91.6%) and on dry roads (93.4%), compared to 79.4% and 81.8% respectively in June 2015. Crashes during rainy conditions decreased from 1,297 to 414, and those on wet surfaces fell from 1,576 to 578. Despite the prevalence of more favorable conditions, the total number of crashes still increased by 8.8%.

Weather

Clear9,115 (92.0%)
25.5%prior 7,265
Rain414 (4.2%)
-68.1%prior 1,297
Cloudy355 (3.6%)
-29.4%prior 503
Other13 (0.1%)
-13.3%prior 15
Fog, Smog, Smoke7 (0.1%)
-12.5%prior 8
Severe Crosswinds2 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Weather condition at time of crash

Lighting

Daylight8,153 (82.5%)
10.1%prior 7,407
Dark-Lighted1,104 (11.2%)
4.7%prior 1,054
Dark-Not Lighted379 (3.8%)
-8.5%prior 414
Dusk142 (1.4%)
18.3%prior 120
Dawn62 (0.6%)
44.2%prior 43
Dark-Unknown Lighting36 (0.4%)
-12.2%prior 41
Other11 (0.1%)
-15.4%prior 13

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Lighting condition field

Road Surface

Dry9,302 (93.8%)
24.2%prior 7,492
Wet578 (5.8%)
-63.3%prior 1,576
Mud, Dirt, Gravel17 (0.2%)
41.7%prior 12
Standing Water7 (0.1%)
-30.0%prior 10
Other7 (0.1%)
-46.2%prior 13
Sand3 (0.0%)
Moving Water1 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Road surface condition field

Vehicles & Demographics

The demographics of persons involved in crashes remained consistent year-over-year, with the 26-34 age group representing the largest cohort in both June 2015 (3,761 persons) and June 2016 (4,176 persons). The distribution of crash-involved individuals across all age groups showed no significant proportional changes. Similarly, the most common vehicle makes involved in collisions, such as Ford, Honda, and Toyota, retained their top rankings in both periods, with their counts increasing in line with the overall rise in crashes.

Top Vehicle Makes (19,169 vehicles)

1
FORD1,860 (9.7%)
6.1%prior 1,753
2
HOND1,126 (5.9%)
19.2%prior 945
3
HONDA1,053 (5.5%)
9.8%prior 959
4
TOYOTA903 (4.7%)
12.3%prior 804
5
TOYO873 (4.6%)
621.5%prior 121
6
NISSAN854 (4.5%)
20.5%prior 709
7
NISS796 (4.2%)
12.6%prior 707
8
CHEV723 (3.8%)
-4.4%prior 756
9
JEEP699 (3.6%)
19.3%prior 586
10
CHEVROLET550 (2.9%)
25.3%prior 439

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Vehicle unit records

1,447 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (24,025 persons with recorded sex)

Male13,161 (54.8%)
10.7%prior 11,889
Female10,864 (45.2%)
9.1%prior 9,959

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes remained most frequent in 25 mph zones, with incidents in this zone increasing from 2,491 to 3,001 year-over-year, and associated fatalities rising from four to six. A notable shift occurred in fatal crash locations; while the 30 mph zone accounted for the most fatalities (6) in June 2015, the 45 mph zone saw the highest number of fatalities (8) in June 2016. This shift also corresponded with the 45 mph zone having the highest fatal crash rate (1.8%) in the current period.

Fatal crashes by zone: 1 mph: 2 of 1,018 (0.196%) · 25 mph: 6 of 3,001 (0.2%) · 35 mph: 2 of 1,163 (0.172%) · 40 mph: 3 of 638 (0.47%) · 45 mph: 8 of 443 (1.806%) · 50 mph: 1 of 269 (0.372%) · 55 mph: 2 of 914 (0.219%) · 65 mph: 1 of 446 (0.224%)

Source: Connecticut Crash Data · Csv Open Data · 2016-06-01 to 2016-06-30 · 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: 2016-06-01 through 2016-06-30
  • Report generated: August 20, 2026

Data Coverage

  • Reporting period: 2016-06-01 through 2016-06-30 (30 days)
  • Geographic scope: connecticut, CT
  • Total crash records analyzed: 9,955
  • Total persons involved: 25,411
  • Total vehicles involved: 19,169

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: June 2016." Published August 20, 2026. Reporting period: 2016-06-01 to 2016-06-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/june-2016-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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