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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · APRIL 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/april-2016-report
Monthly Traffic Safety Analysis
9,279 CRASHES IN
CONNECTICUT, CT
APRIL 2016
In April 2016, Connecticut recorded 9,279 traffic crashes, a 20.9% increase from the 7,674 crashes documented in April 2015. This year-over-year comparison shows a significant rise in overall crash volume. This increase was accompanied by a 24.9% rise in injuries (from 2,476 to 3,094) and an increase in fatalities from 19 to 21.
9,279
▲ 20.9%was 7,674
Total Crash Events
21
▲ 10.5%was 19
Persons Killed
3,094
▲ 25.0%was 2,476
Persons Injured
1,027
▲ 18.0%was 870
Hit-and-Run Crashes
Note: "Persons Killed" (21) counts individual fatalities across all crash events. "Fatal" in the severity table below (20) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend shows a significant increase in traffic incidents compared to the previous year. Total crashes rose by 20.9% from 7,674 in April 2015 to 9,279 in April 2016. Correspondingly, the number of injuries increased by 24.9% and total fatalities rose from 19 to 21.
1,027
Hit-and-Run Crashes — April 2016
▲ 18.0% vs prior (870)
The absolute number of hit-and-run crashes increased from 870 in April 2015 to 1,027 in April 2016, an 18.0% rise. However, the hit-and-run rate as a proportion of all crashes saw a slight decrease, moving from 11.3% in the prior year to 11.1% in the current period. This indicates that while more hit-and-run incidents occurred, they did not grow at a faster pace than other crash types.
Vulnerable Road User Casualties
5
Pedestrians Killed
0
Cyclists Killed
16
Motorists Killed
88
Pedestrians Injured
27
Cyclists Injured
2,979
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
While the peak hour for crashes remained the 4 p.m. hour in both April 2015 (720 crashes) and April 2016 (873 crashes), the peak day of the week shifted. In April 2016, Monday was the day with the most crashes (1,735), a change from the prior year when Wednesday saw the highest volume (1,359 crashes). Overall crash counts increased across most days and hours compared to the previous year.
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate per 100 crashes decreased slightly from 0.25 in April 2015 to 0.22 in April 2016, despite an increase in the absolute number of fatal crashes from 19 to 20. The proportion of crashes resulting in serious injuries increased from 1.0% to 1.2% year-over-year. Concurrently, the share of crashes with no reported injuries decreased from 76.4% to 75.6%, indicating a slight shift toward more severe outcomes.
Severity is per crash event (most severe injury). 20 fatal crash events resulted in 21 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Most severe injury per crash record
Road & Environmental Conditions
The proportion of crashes occurring in daylight remained stable at approximately 78% for both periods. However, a notable shift occurred in weather conditions, with April 2016 seeing 640 crashes in snow, a condition that accounted for only 2 crashes in April 2015. Consequently, the percentage of crashes on dry road surfaces decreased from 82.6% in 2015 to 75.9% in 2016.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Road surface condition field
Vehicles & Demographics
The ranking of the most common vehicle makes involved in crashes remained consistent, with Honda, Toyota, and Ford being the top three in both April 2015 and April 2016. The absolute number of vehicles from these makes involved in collisions increased in line with the overall rise in crashes. An analysis of persons involved shows that the 16-20 age group represented a slightly larger share of individuals in crashes, increasing from 8.9% of total persons in 2015 to 9.9% in 2016.
Top Vehicle Makes (17,264 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Vehicle unit records
1,352 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (21,413 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · Person-level records linked to crash events
Speed Limit Zones
The year-over-year increase in crashes was most pronounced in zones with posted speed limits of 35 mph or less, which saw an additional 1,475 crashes in April 2016 compared to April 2015. In contrast, zones with speed limits of 40 mph or higher recorded a much smaller increase of 60 crashes. In April 2016, the 25 mph and 30 mph zones accounted for the most fatal crashes, with 5 and 4, respectively, a shift from April 2015 when the 55 mph zone also saw 4 fatal crashes.
Fatal crashes by zone: 25 mph: 5 of 2,908 (0.172%) · 30 mph: 4 of 867 (0.461%) · 35 mph: 2 of 1,061 (0.189%) · 40 mph: 1 of 548 (0.182%) · 45 mph: 2 of 369 (0.542%) · 55 mph: 3 of 769 (0.39%) · 65 mph: 1 of 498 (0.201%) · 88 mph: 2 of 586 (0.341%)
Source: Connecticut Crash Data · Csv Open Data · 2016-04-01 to 2016-04-30 · 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: 2016-04-01 through 2016-04-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2016-04-01 through 2016-04-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,279
- Total persons involved: 22,632
- Total vehicles involved: 17,264
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: April 2016." Published August 20, 2026. Reporting period: 2016-04-01 to 2016-04-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/april-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: 2016-04-01 – 2016-04-30
Generated: August 20, 2026 · All rights reserved
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