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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · FEBRUARY 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/february-2016-report
Monthly Traffic Safety Analysis
9,394 CRASHES IN
CONNECTICUT, CT
FEBRUARY 2016
In February 2016, Connecticut recorded 9,394 traffic crashes, a 2.4% decrease from the 9,625 crashes in February 2015. Despite the overall reduction in collisions, the number of reported injuries rose by 16.2% year-over-year, from 2,352 to 2,733. The most significant change was a 76.1% increase in crashes resulting in a serious injury, which grew from 46 to 81 incidents.
9,394
▼ -2.4%was 9,625
Total Crash Events
19
▲ 5.6%was 18
Persons Killed
2,733
▲ 16.2%was 2,352
Persons Injured
1,082
▲ 4.4%was 1,036
Hit-and-Run Crashes
Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume in Connecticut showed a slight decline in February 2016 compared to the previous year, with total incidents decreasing by 2.4% from 9,625 to 9,394. However, the severity of these crashes worsened, as total injuries increased by 16.2% and fatalities edged up from 18 to 19. This suggests a trend toward fewer but more harmful collisions.
1,082
Hit-and-Run Crashes — February 2016
▲ 4.4% vs prior (1,036)
Hit-and-run incidents trended upward in February 2016 compared to the previous year. The total number of hit-and-run crashes increased from 1,036 to 1,082. As a proportion of all crashes, the hit-and-run rate also rose, climbing from 10.8% in February 2015 to 11.5% in February 2016.
Vulnerable Road User Casualties
7
Pedestrians Killed
0
Cyclists Killed
12
Motorists Killed
111
Pedestrians Injured
7
Cyclists Injured
2,615
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · 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. In February 2016, the peak day for crashes was Friday with 2,027 incidents, a change from Wednesday (1,633 crashes) in the prior year. The peak hour for collisions moved slightly earlier to the 3 PM hour in 2016, which saw 719 crashes, compared to the 4 PM hour in 2015.
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, the severity of outcomes worsened in February 2016. The proportion of crashes resulting in an injury rose from 18.0% in 2015 to 21.0% in 2016. This was driven by a notable increase in crashes causing serious injuries, which jumped from 46 (0.5% of total) to 81 (0.9% of total). The fatal crash count increased from 17 to 19, with the rate remaining stable at approximately 0.2% of all crashes.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions saw some shifts year-over-year, largely influenced by weather. The proportion of collisions occurring in clear weather decreased from 71.9% to 63.4%, while crashes during rain increased from just 22 incidents in February 2015 to 783 in February 2016. Correspondingly, crashes on wet road surfaces increased from 1,154 to 1,450. Crashes occurring in daylight remained the majority in both periods, accounting for over 65% of all incidents.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Road surface condition field
Vehicles & Demographics
The demographics of vehicles and persons involved in crashes remained largely consistent year-over-year. The top vehicle makes involved in collisions were consistent, with Honda, Ford, and Toyota being the most frequent in both February 2015 and 2016. Similarly, the age distribution of persons involved was stable, with the 26-34 age group consistently accounting for the largest share of individuals (16.8% in 2016 vs. 16.2% in 2015).
Top Vehicle Makes (17,116 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Vehicle unit records
1,317 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (20,875 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shows a shift toward lower-speed areas. Collisions in 25 mph zones increased from 2,808 to 3,008, with fatal crashes in this zone rising from 3 to 5. The 35 mph zone also saw a slight increase in total crashes and a rise in fatal crashes from 4 to 6. In contrast, the number of crashes in 65 mph zones decreased from 525 to 472.
Fatal crashes by zone: 25 mph: 5 of 3,008 (0.166%) · 30 mph: 2 of 893 (0.224%) · 35 mph: 6 of 1,121 (0.535%) · 45 mph: 2 of 373 (0.536%) · 50 mph: 1 of 242 (0.413%) · 55 mph: 1 of 687 (0.146%) · 65 mph: 1 of 472 (0.212%) · 88 mph: 1 of 568 (0.176%)
Source: Connecticut Crash Data · Csv Open Data · 2016-02-01 to 2016-02-29 · 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: 2016-02-01 through 2016-02-29
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2016-02-01 through 2016-02-29 (29 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,394
- Total persons involved: 22,176
- Total vehicles involved: 17,116
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: February 2016." Published August 20, 2026. Reporting period: 2016-02-01 to 2016-02-29. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/february-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Connecticut Crash Data · Csv
Period: 2016-02-01 – 2016-02-29
Generated: August 20, 2026 · All rights reserved
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