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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · SEPTEMBER 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/september-2016-report
Monthly Traffic Safety Analysis
9,214 CRASHES IN
CONNECTICUT, CT
SEPTEMBER 2016
In September 2016, there were 9,214 total crashes, a marginal increase of 0.05% from the 9,209 crashes recorded in September 2015. While the overall crash volume remained stable, the number of fatalities increased by 7.4% from 27 to 29 year-over-year. The most notable shift was the increase in fatalities despite a 1.8% decrease in total injuries.
9,214
▲ 0.1%was 9,209
Total Crash Events
29
▲ 7.4%was 27
Persons Killed
3,207
▼ -1.8%was 3,267
Persons Injured
1,075
▲ 5.0%was 1,024
Hit-and-Run Crashes
Note: "Persons Killed" (29) counts individual fatalities across all crash events. "Fatal" in the severity table below (27) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends remained stable between September 2015 and September 2016, with total crashes increasing by only 5 incidents to 9,214. Despite this stability in crash volume, the outcomes shifted; total injuries decreased by 1.8% to 3,207, while fatalities rose by 7.4% from 27 to 29.
1,075
Hit-and-Run Crashes — September 2016
▲ 5.0% vs prior (1,024)
Hit-and-run incidents trended upward in September 2016 compared to the previous year. The total number of hit-and-run crashes increased from 1,024 to 1,075. This represents an increase in the hit-and-run rate, which rose from 11.1% of all crashes in September 2015 to 11.7% in September 2016.
Vulnerable Road User Casualties
5
Pedestrians Killed
0
Cyclists Killed
24
Motorists Killed
0
Other Killed
123
Pedestrians Injured
59
Cyclists Injured
3,023
Motorists Injured
2
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a shift year-over-year. In September 2016, the peak day for crashes was Friday with 1,934 incidents, a change from the prior year when Wednesday was the peak day with 1,666 crashes. The peak hour for crashes also shifted later in the day, from the 2 p.m. hour in 2015 (773 crashes) to the 4 p.m. hour in 2016 (882 crashes).
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes saw minor shifts between the two periods. The fatal crash rate increased from 0.27% in September 2015 to 0.29% in September 2016, corresponding to a rise from 25 to 27 fatal crashes. The proportion of crashes resulting in serious injuries remained constant at 1.6%, while the share of minor injury crashes decreased from 10.2% to 9.0% of all incidents.
Severity is per crash event (most severe injury). 27 fatal crash events resulted in 29 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Most severe injury per crash record
Road & Environmental Conditions
The vast majority of crashes in both periods occurred in clear weather and during daylight. However, there was a noticeable increase in the proportion of crashes on wet road surfaces, which rose from 9.7% of all crashes in September 2015 to 11.6% in September 2016. Correspondingly, crashes reported during rain increased from 7.7% to 8.2% of the total. The distribution of crashes by lighting conditions remained nearly identical year-over-year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes, including Ford, Honda, and Toyota, were consistent across both periods. An analysis of persons involved shows a demographic shift, with the proportion of individuals in the 16-20 age group increasing from 8.3% of all persons in September 2015 to 9.3% in September 2016. Conversely, the share of persons in the 0-15 age group decreased from 8.0% to 7.3%.
Top Vehicle Makes (17,665 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Vehicle unit records
1,546 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (21,718 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · Person-level records linked to crash events
Speed Limit Zones
Year-over-year, there was a slight shift in crashes toward lower speed zones. The number of crashes in zones posted at 35 mph or less increased from 5,654 to 5,816, while incidents in zones 40 mph or higher decreased from 2,515 to 2,406. Despite fewer crashes in high-speed zones, the fatal crash rate within these zones increased from 0.48% to 0.54%. The fatal crash rate in lower speed zones remained stable at approximately 0.2% for both periods.
Fatal crashes by zone: 1 mph: 2 of 950 (0.211%) · 25 mph: 6 of 2,865 (0.209%) · 30 mph: 2 of 778 (0.257%) · 35 mph: 3 of 1,096 (0.274%) · 40 mph: 5 of 587 (0.852%) · 45 mph: 2 of 368 (0.543%) · 50 mph: 1 of 279 (0.358%) · 55 mph: 2 of 794 (0.252%) · 65 mph: 3 of 378 (0.794%) · 99 mph: 1 of 176 (0.568%)
Source: Connecticut Crash Data · Csv Open Data · 2016-09-01 to 2016-09-30 · 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: 2016-09-01 through 2016-09-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2016-09-01 through 2016-09-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,214
- Total persons involved: 23,038
- Total vehicles involved: 17,665
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: September 2016." Published August 20, 2026. Reporting period: 2016-09-01 to 2016-09-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/september-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: 2016-09-01 – 2016-09-30
Generated: August 20, 2026 · All rights reserved
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