If you're a data point in this report, call us.
We'll evaluate whether you have a case. Free, and no pressure.
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
28,341 CRASHES IN
CONNECTICUT, CT
2016
In 2016, Hartford County recorded 28,341 total crashes, an 8.1% increase from the 26,223 crashes reported in 2015. While total fatalities remained constant at 63, one of the most notable year-over-year changes was a 39.3% rise in crashes involving pedestrians, which increased from 313 to 436.
28,341
▲ 8.1%was 26,223
Total Crash Events
63
Persons Killed
10,522
▲ 10.5%was 9,526
Persons Injured
3,634
▲ 26.1%was 2,881
Hit-and-Run Crashes
Note: "Persons Killed" (63) counts individual fatalities across all crash events. "Fatal" in the severity table below (62) 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
Crash trends in Hartford County showed a notable increase from 2015 to 2016. Total crashes rose by 8.1%, from 26,223 to 28,341. This was accompanied by a 10.5% increase in total injuries, which grew from 9,526 to 10,522, while total fatalities remained unchanged at 63 for both years.
3,634
Hit-and-Run Crashes — 2016
▲ 26.1% vs prior (2,881)
Hit-and-run incidents increased substantially in Hartford County from 2015 to 2016. The total number of hit-and-run crashes rose by 26.1%, from 2,881 to 3,634. This outpaced the overall growth in crashes, causing the hit-and-run rate to climb from 11.0% of all crashes in 2015 to 12.8% in 2016.
Vulnerable Road User Casualties
16
Pedestrians Killed
1
Cyclists Killed
46
Motorists Killed
0
Other Killed
390
Pedestrians Injured
131
Cyclists Injured
9,993
Motorists Injured
8
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
Temporal crash patterns remained broadly consistent year-over-year, with Friday being the peak day for crashes in both 2016 (5,027 crashes) and 2015 (4,525 crashes). However, the peak hour for collisions shifted from the 3 p.m. hour in 2015 (2,341 crashes) to the 5 p.m. hour in 2016 (2,729 crashes). Weekday crashes consistently outnumbered weekend crashes across both periods.
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 overall severity of crashes saw minor shifts between 2015 and 2016. The fatal crash rate decreased slightly from 0.23% to 0.22%, even as the absolute number of fatal crashes rose from 60 to 62. The proportion of crashes resulting in serious injuries increased from 1.1% to 1.2%, and minor injury crashes rose from 9.9% to 10.5% of all incidents. Consequently, the share of no-injury crashes declined from 74.1% in 2015 to 73.6% in 2016.
Severity is per crash event (most severe injury). 62 fatal crash events resulted in 63 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 majority of crashes in both periods occurred in clear weather and on dry roads. In 2016, the proportion of crashes on dry road surfaces increased to 81.3% from 76.9% in the prior year. The share of crashes happening in clear weather also rose from 80.2% to 82.1%. The distribution of crashes by lighting conditions remained relatively stable, with approximately 70% occurring in daylight in both 2015 and 2016.
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, with Honda, Toyota, and Nissan being the most common in both 2016 and 2015. An analysis of persons involved in crashes shows a slight shift in age demographics. The proportion of individuals in the 16-20 age group increased from 9.0% in 2015 to 9.4% in 2016, while the share for the 21-25 age group decreased from 12.0% to 11.7%. The 26-34 age group continued to represent the largest share of persons involved, increasing its proportion from 16.8% to 17.1%.
Top Vehicle Makes (54,378 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-12-31 · Vehicle unit records
5,408 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (68,932 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
Crashes in lower speed zones saw an increase, with collisions in 25 mph zones rising from 5,195 to 5,955 year-over-year, while crashes in 65 mph zones decreased from 1,898 to 1,746. However, the rate of fatal crashes increased across several key speed zones. In 25 mph zones, the fatal crash rate rose from 0.154% to 0.252%, and in 35 mph zones, it increased from 0.098% to 0.199%. The fatal crash rate in 65 mph zones also increased significantly, from 0.211% in 2015 to 0.401% in 2016.
Fatal crashes by zone: 1 mph: 2 of 1,877 (0.107%) · 25 mph: 15 of 5,955 (0.252%) · 30 mph: 7 of 3,377 (0.207%) · 35 mph: 9 of 4,521 (0.199%) · 40 mph: 5 of 2,265 (0.221%) · 45 mph: 5 of 806 (0.62%) · 50 mph: 4 of 2,101 (0.19%) · 55 mph: 4 of 1,399 (0.286%) · 65 mph: 7 of 1,746 (0.401%) · 88 mph: 4 of 2,587 (0.155%)
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: 28,341
- Total persons involved: 73,331
- Total vehicles involved: 54,378
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
The data is step one. Get a Connecticut attorney on the line.
Call our intake team. We connect you to a vetted Connecticut personal injury attorney who calls you back within minutes. No phone tag. No voicemails.
Always free for accident victims.