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ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · NOVEMBER 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/november-2016-report
Monthly Traffic Safety Analysis
10,178 CRASHES IN
CONNECTICUT, CT
NOVEMBER 2016
In November 2016, Connecticut recorded 10,178 traffic crashes, a 6.0% increase from the 9,599 crashes that occurred in November 2015. Despite the overall rise in collisions, the number of fatalities decreased by 20%, from 25 to 20, over the same period. The most notable shift was this divergence, where an increase in total crashes was accompanied by a decrease in their lethality, with the fatal crash rate dropping from 0.25% to 0.19%.
10,178
▲ 6.0%was 9,599
Total Crash Events
20
▼ -20.0%was 25
Persons Killed
3,271
▲ 1.2%was 3,233
Persons Injured
1,109
▲ 10.1%was 1,007
Hit-and-Run Crashes
Note: "Persons Killed" (20) 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 · 2016-11-01 to 2016-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Connecticut showed an upward trend in November 2016 compared to the previous year, increasing by 579 incidents, or 6.0%. While total collisions rose, the number of people injured remained relatively stable, increasing by just 1.2% from 3,233 to 3,271. However, fatalities saw a notable 20% decrease, falling from 25 in November 2015 to 20 in November 2016.
1,109
Hit-and-Run Crashes — November 2016
▲ 10.1% vs prior (1,007)
Hit-and-run incidents increased in both absolute numbers and as a percentage of total crashes. In November 2016, there were 1,109 hit-and-run crashes, up from 1,007 in November 2015, marking a 10.1% increase. The hit-and-run rate also climbed, rising from 10.5% of all crashes in the prior year to 10.9% in the current period.
Vulnerable Road User Casualties
4
Pedestrians Killed
1
Cyclists Killed
15
Motorists Killed
160
Pedestrians Injured
24
Cyclists Injured
3,087
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes saw some shifts year-over-year. The peak hour for collisions remained the 5 p.m. slot in both periods, but the volume of crashes during this hour increased by 13.6% in November 2016, from 960 to 1,091. The most significant change was the peak day of the week, which moved from Monday (1,566 crashes) in 2015 to Tuesday (2,012 crashes) in 2016.
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the overall severity of collisions decreased in November 2016 compared to the prior year. The fatal crash rate fell from 0.25% to 0.19%, with 19 fatal crashes in the current period compared to 24 in the prior. The proportion of crashes resulting in any level of injury also saw a slight decline, from 24.0% of all crashes in November 2015 to 23.2% in November 2016. Crashes resulting in no injury increased from 7,270 to 7,795.
Severity is per crash event (most severe injury). 19 fatal crash events resulted in 20 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes across different environmental conditions remained largely consistent between November 2015 and November 2016. In both periods, approximately 81% of crashes occurred on dry road surfaces and roughly 80-82% happened in clear weather. There was a minor shift in lighting conditions, with the proportion of crashes occurring in daylight increasing from 55.9% to 58.1%, while crashes in dark but lighted conditions decreased proportionally from 31.4% to 28.5%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Road surface condition field
Vehicles & Demographics
An analysis of the vehicles and persons involved shows consistency across both periods. The most common vehicle makes involved in crashes remained Ford, Honda, and Toyota, with no significant shifts in their top-tier rankings. The age distribution of all persons involved in crashes was also stable, with each age demographic representing a nearly identical percentage of the total in November 2016 as in November 2015. For instance, the 26-34 age group accounted for 16.7% of persons in the current period, compared to 16.6% in the prior period.
Top Vehicle Makes (19,394 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Vehicle unit records
1,514 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (23,796 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained consistent year-over-year, with the 25 mph zone accounting for the largest share of incidents in both periods (30.1% in 2016 vs. 30.3% in 2015). However, there was a notable shift in where fatal crashes occurred. In November 2016, the 35 mph zone saw a significant increase in fatalities, with 5 deaths compared to 1 in the prior year. Conversely, fatalities in higher speed zones decreased; the 65 mph zone dropped from 4 fatalities to 1, and the 50 mph zone dropped from 3 fatalities to zero.
Fatal crashes by zone: 25 mph: 4 of 3,065 (0.131%) · 30 mph: 2 of 913 (0.219%) · 35 mph: 5 of 1,208 (0.414%) · 40 mph: 4 of 668 (0.599%) · 45 mph: 1 of 418 (0.239%) · 55 mph: 2 of 958 (0.209%) · 65 mph: 1 of 509 (0.196%)
Source: Connecticut Crash Data · Csv Open Data · 2016-11-01 to 2016-11-30 · 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: 2016-11-01 through 2016-11-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2016-11-01 through 2016-11-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 10,178
- Total persons involved: 25,227
- Total vehicles involved: 19,394
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: November 2016." Published August 20, 2026. Reporting period: 2016-11-01 to 2016-11-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/november-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: 2016-11-01 – 2016-11-30
Generated: August 20, 2026 · All rights reserved
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