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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · 2016
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/2016-annual-report
Yearly Traffic Safety Analysis
33,684 CRASHES IN
CONNECTICUT, CT
2016
In 2016, Fairfield County recorded 33,684 traffic crashes, a 3.7% increase from the 32,469 crashes reported in 2015. While total crashes saw a modest rise, the most significant year-over-year change was a sharp increase in roadway fatalities, which grew from 38 in 2015 to 72 in 2016, an 89.5% increase.
33,684
▲ 3.7%was 32,469
Total Crash Events
72
▲ 89.5%was 38
Persons Killed
9,860
▲ 7.8%was 9,145
Persons Injured
3,474
▲ 15.3%was 3,013
Hit-and-Run Crashes
Note: "Persons Killed" (72) counts individual fatalities across all crash events. "Fatal" in the severity table below (67) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Fairfield County worsened from 2015 to 2016. The total number of crashes rose by 3.7%, from 32,469 to 33,684. This increase was accompanied by a more pronounced rise in negative outcomes, with total injuries increasing by 7.8% and total fatalities increasing by 89.5% year-over-year.
3,474
Hit-and-Run Crashes — 2016
▲ 15.3% vs prior (3,013)
Hit-and-run incidents increased in both absolute numbers and as a proportion of total crashes. The count of hit-and-run crashes rose by 15.3% from 3,013 in 2015 to 3,474 in 2016. This pushed the hit-and-run rate up from 9.3% to 10.3% of all crashes, indicating a worsening trend.
Vulnerable Road User Casualties
21
Pedestrians Killed
2
Cyclists Killed
49
Motorists Killed
456
Pedestrians Injured
114
Cyclists Injured
9,290
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained consistent between 2015 and 2016. Friday continued to be the peak day for crashes, with incidents increasing from 5,415 to 5,800. Similarly, the 5 p.m. hour remained the peak time for collisions, with counts rising from 2,751 in 2015 to 2,889 in 2016, indicating a stable but intensifying pattern of crashes during the weekday evening commute.
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes increased from 2015 to 2016. The number of fatal crashes rose from 37 to 67, and the fatal crash rate as a percentage of all crashes increased from 0.1% to 0.2%. Crashes resulting in serious injuries also grew proportionally, from 0.9% to 1.2% of all incidents. Consequently, the share of crashes with no reported injuries decreased from 79.4% in 2015 to 78.5% in 2016.
Severity is per crash event (most severe injury). 67 fatal crash events resulted in 72 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Most severe injury per crash record
Road & Environmental Conditions
The proportion of crashes occurring under different environmental conditions shifted between 2015 and 2016. Crashes during adverse weather, such as rain or snow, decreased as a share of the total, with snow-related incidents falling from 3.9% to 2.2% of all crashes. Correspondingly, collisions on clear days with dry road surfaces made up a larger percentage of the total, increasing from 79.6% to 83.3% of all crashes. Lighting conditions at the time of crashes remained proportionally stable year-over-year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Road surface condition field
Vehicles & Demographics
The demographic profile of persons involved in crashes and the most common vehicle makes remained largely consistent year-over-year. The distribution of involved persons across age groups saw minimal changes, with most groups maintaining a similar proportional representation. In terms of vehicles, Ford, Honda, and Toyota continued to be the most frequently involved makes in both 2015 and 2016, with no significant shifts in their rankings.
Top Vehicle Makes (65,204 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Vehicle unit records
5,123 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (78,118 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a notable shift in crashes toward lower posted speed limit zones between 2015 and 2016. Crashes in zones of 25 mph or less increased from 9,324 to 12,137. The number of fatal crashes in the 25 mph zone also increased significantly, rising from 6 in 2015 to 22 in 2016. Conversely, collisions in some higher speed zones, such as the 55 mph zone, saw a smaller increase in crash counts from 5,049 to 5,162.
Fatal crashes by zone: 1 mph: 2 of 5,367 (0.037%) · 20 mph: 1 of 178 (0.562%) · 25 mph: 22 of 12,137 (0.181%) · 30 mph: 12 of 2,579 (0.465%) · 35 mph: 5 of 2,380 (0.21%) · 40 mph: 5 of 1,297 (0.386%) · 45 mph: 3 of 418 (0.718%) · 55 mph: 13 of 5,162 (0.252%) · 88 mph: 3 of 2,837 (0.106%) · 99 mph: 1 of 177 (0.565%)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · 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: 2016-01-01 through 2016-12-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2016-01-01 through 2016-12-31 (366 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 33,684
- Total persons involved: 82,808
- Total vehicles involved: 65,204
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: 2016." Published August 20, 2026. Reporting period: 2016-01-01 to 2016-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2016-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: 2016-01-01 – 2016-12-31
Generated: August 20, 2026 · All rights reserved
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