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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JANUARY 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/january-2016-report
Monthly Traffic Safety Analysis
9,094 CRASHES IN
CONNECTICUT, CT
JANUARY 2016
In January 2016, there were 9,094 total crashes, a 1.8% increase from the 8,938 crashes recorded in January 2015. While overall crashes rose slightly, the number of fatalities increased by 50% from 16 to 24. The most significant change was a 52.8% decrease in crashes identified as speeding-related, which fell from 2,024 to 955 year-over-year.
9,094
▲ 1.7%was 8,938
Total Crash Events
24
▲ 50.0%was 16
Persons Killed
2,844
▲ 15.4%was 2,465
Persons Injured
1,158
▲ 38.8%was 834
Hit-and-Run Crashes
Note: "Persons Killed" (24) counts individual fatalities across all crash events. "Fatal" in the severity table below (23) 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 2016-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends show a slight increase in volume but a more substantial rise in severity compared to the same month last year. Total crashes increased by 1.8% from 8,938 to 9,094. However, total injuries rose by 15.4% (from 2,465 to 2,844), and fatalities increased by 50% (from 16 to 24).
1,158
Hit-and-Run Crashes — January 2016
▲ 38.8% vs prior (834)
Hit-and-run incidents increased notably in January 2016 compared to the same month in 2015. The absolute number of hit-and-run crashes rose by 38.8%, from 834 to 1,158. The hit-and-run rate, representing the portion of all crashes that were hit-and-runs, also trended upward, increasing from 9.3% to 12.7% year-over-year.
Vulnerable Road User Casualties
5
Pedestrians Killed
0
Cyclists Killed
19
Motorists Killed
0
Other Killed
129
Pedestrians Injured
14
Cyclists Injured
2,699
Motorists Injured
2
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · 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 broadly consistent year-over-year, with Friday being the peak day and 3 p.m. the peak hour in both January 2016 and January 2015. However, there was a notable redistribution of crashes throughout the week. Crashes on Monday through Thursday saw a marked increase in January 2016, while collisions on Sunday decreased by 242 incidents compared to the prior year.
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes increased in January 2016 compared to the previous year. The proportion of crashes resulting in a fatality rose from 0.2% to 0.3%, and the overall fatal crash rate increased from 0.18 to 0.25 per 100 crashes. The share of all injury-related crashes (serious, minor, or possible) also grew from 20.3% to 22.3% of total incidents. Consequently, the proportion of crashes with no reported injuries declined from 79.5% to 77.4%.
Severity is per crash event (most severe injury). 23 fatal crash events resulted in 24 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions shifted significantly, indicating better weather in January 2016 compared to January 2015. The proportion of crashes occurring on dry road surfaces increased from 53.8% to 79.4% year-over-year. Correspondingly, crashes on snowy or icy roads fell from a combined 29.8% in the prior year to just 7.3% in the current period. Similarly, crashes in clear weather accounted for 84.5% of the total, up from 62.7% the year before.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes, including Ford, Honda, and Toyota, remained consistent across both periods with no significant changes in ranking. Analysis of person demographics shows a stable distribution across most age groups. However, the proportion of individuals aged 65 and older involved in crashes increased slightly, from 7.7% of all persons in January 2015 to 8.3% in January 2016.
Top Vehicle Makes (17,008 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · Vehicle unit records
1,484 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (20,991 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · Person-level records linked to crash events
Speed Limit Zones
There was a shift in where crashes occurred relative to posted speed limits. In January 2016, a higher volume of crashes was recorded in zones with speed limits of 35 mph or less (5,849 crashes) compared to the prior year (5,143 crashes). Conversely, crashes in zones of 55 mph or higher decreased from 2,461 to 1,835. Despite more crashes occurring in lower speed zones, the number of fatal crashes increased in both lower (from 8 to 12) and higher (from 4 to 6) speed limit areas.
Fatal crashes by zone: 1 mph: 2 of 831 (0.241%) · 20 mph: 1 of 39 (2.564%) · 25 mph: 6 of 3,022 (0.199%) · 30 mph: 1 of 823 (0.122%) · 35 mph: 2 of 1,035 (0.193%) · 40 mph: 2 of 602 (0.332%) · 45 mph: 2 of 346 (0.578%) · 50 mph: 1 of 261 (0.383%) · 55 mph: 2 of 705 (0.284%) · 65 mph: 2 of 418 (0.478%) · 88 mph: 1 of 571 (0.175%) · 99 mph: 1 of 139 (0.719%)
Source: Connecticut Crash Data · Csv Open Data · 2016-01-01 to 2016-01-31 · 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 2016-01-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2016-01-01 through 2016-01-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,094
- Total persons involved: 22,319
- Total vehicles involved: 17,008
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: January 2016." Published August 20, 2026. Reporting period: 2016-01-01 to 2016-01-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/january-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: 2016-01-01 – 2016-01-31
Generated: August 20, 2026 · All rights reserved
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