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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · AUGUST 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/august-2016-report
Monthly Traffic Safety Analysis
9,446 CRASHES IN
CONNECTICUT, CT
AUGUST 2016
In August 2016, Connecticut recorded 9,446 total vehicle crashes, a 7.0% increase from the 8,827 crashes in August 2015. Despite the rise in total collisions and a 3.8% increase in injuries, the most notable year-over-year shift was a 25% decrease in fatalities, which fell from 32 to 24.
9,446
▲ 7.0%was 8,827
Total Crash Events
24
▼ -25.0%was 32
Persons Killed
3,356
▲ 3.8%was 3,232
Persons Injured
1,086
▲ 9.4%was 993
Hit-and-Run Crashes
Note: "Persons Killed" (24) counts individual fatalities across all crash events. "Fatal" in the severity table below (24) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic collisions in Connecticut trended upward in August 2016 compared to the same month in the prior year, with total crashes increasing by 7.0% from 8,827 to 9,446. While total injuries also rose by 3.8% (from 3,232 to 3,356), the number of fatalities decreased by 25% (from 32 to 24).
1,086
Hit-and-Run Crashes — August 2016
▲ 9.4% vs prior (993)
The number of hit-and-run crashes increased from 993 in August 2015 to 1,086 in August 2016. This change also reflects a slight increase in the hit-and-run rate, which rose from 11.2% to 11.5% of all crashes. The data indicates an upward trend in both the absolute count and the proportion of hit-and-run incidents.
Vulnerable Road User Casualties
2
Pedestrians Killed
1
Cyclists Killed
21
Motorists Killed
100
Pedestrians Injured
64
Cyclists Injured
3,192
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes remained consistent year-over-year. The peak day for crashes in both August 2016 and August 2015 was Monday, and the peak hour for collisions was 4 p.m. in both periods. Crash volumes during these peak times increased, with Monday crashes rising from 1,422 to 1,541 and incidents during the 4 p.m. hour increasing from 750 to 872.
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the fatal crash rate decreased from 0.33% in August 2015 to 0.25% in August 2016. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) remained stable, moving from 25.9% of all crashes in the prior year to 25.6% in the current year. Correspondingly, the share of crashes with no reported injuries slightly increased from 73.7% to 74.2%.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Most severe injury per crash record
Road & Environmental Conditions
The majority of crashes in both periods occurred in clear weather on dry roads. In August 2016, 91.5% of crashes were in clear weather, compared to 93.7% in August 2015. There was a slight proportional increase in crashes on wet roads, which accounted for 6.6% of incidents in August 2016 versus 5.4% in the prior year. The distribution of crashes by lighting condition remained consistent, with daylight crashes making up approximately 78% of the total in both periods.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Road surface condition field
Vehicles & Demographics
The leading vehicle makes involved in crashes, including Honda, Toyota, and Ford, were consistent across both periods, with collision counts for each make increasing in line with the overall trend. The demographic profile of persons involved in crashes also showed little year-over-year change. The 26-34 age group was the largest single cohort of individuals involved in collisions in both August 2015 and August 2016.
Top Vehicle Makes (18,234 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Vehicle unit records
1,487 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (22,749 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes were most frequent in 25 mph zones in both periods, with the count in this zone rising from 2,519 to 2,890 year-over-year. In contrast, the number of crashes in speed zones of 55 mph or higher saw a decrease from 2,294 to 2,122. This shift was accompanied by a reduction in high-speed fatalities; crashes in 55 mph and 65 mph zones resulted in 9 deaths in August 2015 but only 2 in August 2016.
Fatal crashes by zone: 1 mph: 1 of 1,033 (0.097%) · 20 mph: 1 of 43 (2.326%) · 25 mph: 8 of 2,890 (0.277%) · 30 mph: 5 of 818 (0.611%) · 35 mph: 3 of 1,026 (0.292%) · 40 mph: 1 of 550 (0.182%) · 45 mph: 1 of 361 (0.277%) · 50 mph: 2 of 269 (0.743%) · 65 mph: 2 of 429 (0.466%)
Source: Connecticut Crash Data · Csv Open Data · 2016-08-01 to 2016-08-31 · 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: 2016-08-01 through 2016-08-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2016-08-01 through 2016-08-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,446
- Total persons involved: 24,090
- Total vehicles involved: 18,234
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: August 2016." Published August 20, 2026. Reporting period: 2016-08-01 to 2016-08-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/august-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: 2016-08-01 – 2016-08-31
Generated: August 20, 2026 · All rights reserved
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