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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
30,557 CRASHES IN
CONNECTICUT, CT
2016
In New Haven County, total reported traffic crashes increased by 6.1%, rising from 28,807 in 2015 to 30,557 in 2016. This rise in collisions was accompanied by a significant increase in crash severity. The most notable year-over-year shift was a 32.3% increase in total fatalities, which grew from 62 in 2015 to 82 in 2016.
30,557
▲ 6.1%was 28,807
Total Crash Events
82
▲ 32.3%was 62
Persons Killed
11,263
▲ 13.4%was 9,929
Persons Injured
3,933
▲ 2.4%was 3,839
Hit-and-Run Crashes
Note: "Persons Killed" (82) counts individual fatalities across all crash events. "Fatal" in the severity table below (78) 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 New Haven County worsened from 2015 to 2016. The total number of crashes rose by 1,750 incidents, a 6.1% increase. Concurrently, the number of people injured increased by 13.4% from 9,929 to 11,263, and total fatalities saw a substantial 32.3% jump from 62 to 82.
3,933
Hit-and-Run Crashes — 2016
▲ 2.4% vs prior (3,839)
The total number of hit-and-run crashes increased slightly from 3,839 in 2015 to 3,933 in 2016. However, because the overall number of crashes grew at a faster pace, the hit-and-run rate as a percentage of all crashes trended downward. The rate decreased from 13.3% in 2015 to 12.9% in 2016.
Vulnerable Road User Casualties
15
Pedestrians Killed
1
Cyclists Killed
65
Motorists Killed
1
Other Killed
385
Pedestrians Injured
121
Cyclists Injured
10,757
Motorists Injured
0
Other 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 year-over-year, with no change in the highest-risk times. In both 2015 and 2016, Friday was the peak day for crashes and the 4 p.m. hour was the peak time. However, the volume of crashes during these peaks intensified in 2016, with Friday crashes increasing from 4,977 to 5,453 and collisions during the 4 p.m. hour rising from 2,483 to 2,610.
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 59 to 78, causing the fatal crash rate to increase from 0.2% to 0.3% of all collisions. While the proportion of serious injury crashes held steady at 1.4%, the share of crashes resulting in no injuries decreased from 75.4% in 2015 to 73.8% in 2016, indicating a general shift toward more crashes involving some level of injury.
Severity is per crash event (most severe injury). 78 fatal crash events resulted in 82 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
Comparing the two periods, a larger proportion of crashes in 2016 occurred under ideal driving conditions. Collisions on dry road surfaces increased from 76.8% of the total in 2015 to 82.3% in 2016. Similarly, crashes in clear weather rose from 78.0% to 81.7% of all incidents. The distribution of crashes by lighting conditions remained stable, with approximately 70% of collisions in both years occurring during daylight hours.
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 makes of vehicles involved in crashes remained consistent between 2015 and 2016. In both periods, the most frequently involved makes were Honda, Ford, Toyota, and Nissan. The age demographics of persons involved in crashes also showed little change, with the proportional representation of all age groups, from young drivers (16-20) to older individuals (65+), remaining stable year-over-year.
Top Vehicle Makes (58,420 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Vehicle unit records
4,422 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (73,147 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
Crash distribution shifted toward lower speed zones in 2016 compared to the prior year. The number of crashes in zones posted at 35 mph or less increased from 18,128 to 20,217, while collisions in zones 65 mph or higher decreased from 2,674 to 2,115. Despite this shift, fatalities increased in lower speed zones, rising from 32 to 46 in areas posted at 35 mph or less. The largest single increase was in 25 mph zones, where fatal crashes rose from 17 to 27.
Fatal crashes by zone: 1 mph: 4 of 3,641 (0.11%) · 20 mph: 1 of 124 (0.806%) · 25 mph: 27 of 11,323 (0.238%) · 30 mph: 3 of 1,959 (0.153%) · 35 mph: 11 of 2,812 (0.391%) · 40 mph: 7 of 1,717 (0.408%) · 45 mph: 5 of 1,412 (0.354%) · 50 mph: 3 of 427 (0.703%) · 55 mph: 8 of 2,975 (0.269%) · 65 mph: 7 of 1,110 (0.631%) · 88 mph: 1 of 855 (0.117%) · 99 mph: 1 of 150 (0.667%)
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 21, 2026
Data Coverage
- Reporting period: 2016-01-01 through 2016-12-31 (366 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 30,557
- Total persons involved: 77,513
- Total vehicles involved: 58,420
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 21, 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 21, 2026 · All rights reserved
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