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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · MAY 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/may-2016-report
Monthly Traffic Safety Analysis
9,966 CRASHES IN
CONNECTICUT, CT
MAY 2016
In May 2016, there were 9,966 total crashes statewide, an increase of 9.2% from the 9,125 crashes recorded in May 2015. While total fatalities decreased from 30 to 27 year-over-year, the number of pedestrians killed rose from 3 in the prior period to 8 in the current period. Total injuries also increased by 3.5%, from 3,261 to 3,374.
9,966
▲ 9.2%was 9,125
Total Crash Events
27
▼ -10.0%was 30
Persons Killed
3,374
▲ 3.5%was 3,261
Persons Injured
1,101
▲ 14.2%was 964
Hit-and-Run Crashes
Note: "Persons Killed" (27) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic crashes in Connecticut trended upward in May 2016 compared to the same month in the prior year. The total number of crashes increased by 9.2%, rising from 9,125 to 9,966. While fatalities saw a decrease of 10% (from 30 to 27), the number of injuries increased by 3.5% to 3,374.
1,101
Hit-and-Run Crashes — May 2016
▲ 14.2% vs prior (964)
Hit-and-run crashes trended upward in May 2016 compared to the previous year. The total count of hit-and-run incidents increased by 14.2%, from 964 in May 2015 to 1,101 in May 2016. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also saw a slight increase, rising from 10.6% to 11.0% year-over-year.
Vulnerable Road User Casualties
8
Pedestrians Killed
1
Cyclists Killed
18
Motorists Killed
115
Pedestrians Injured
44
Cyclists Injured
3,215
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day of the week for crashes shifted from Friday (1,787 crashes) in May 2015 to Tuesday (1,614 crashes) in May 2016. The peak hour for collisions, however, remained consistent year-over-year, with the 4 p.m. hour seeing the highest volume in both periods (863 crashes in 2015 and 940 in 2016). Crashes during the morning commute hours of 7 a.m. and 8 a.m. also saw increases, rising from 430 to 474 and 508 to 599, respectively.
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate decreased from 0.32 per 100 crashes in May 2015 to 0.26 in May 2016, with 26 fatal crashes recorded compared to 29 in the prior year. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) saw a slight decrease, accounting for 24.3% of all crashes in May 2016 versus 25.1% in the prior period. Correspondingly, crashes resulting in no injury increased from 74.6% to 75.4% of the total.
Severity is per crash event (most severe injury). 26 fatal crash events resulted in 27 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Most severe injury per crash record
Road & Environmental Conditions
The most significant shift in crash conditions was related to weather and road surface. Crashes occurring in the rain increased from 320 in May 2015 to 1,347 in May 2016, representing a proportional increase from 3.5% to 13.5% of all crashes. Similarly, crashes on wet road surfaces rose from 442 to 1,847. The distribution of crashes by lighting conditions remained relatively stable, with approximately 80% of collisions in both periods occurring during daylight hours.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes remained consistent year-over-year, with Honda, Toyota, and Ford being the most common in both May 2016 and May 2015. Examining the age of persons involved, there was an increase in the representation of the 16-20 age group. This group accounted for 10.2% of all persons involved in crashes in May 2016 (2,576 individuals), up from 9.3% in the prior year (2,171 individuals).
Top Vehicle Makes (19,092 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Vehicle unit records
1,551 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (23,778 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · Person-level records linked to crash events
Speed Limit Zones
Year-over-year, there was a shift in crashes toward lower speed limit zones, with the number of crashes in 25 mph zones increasing from 2,678 to 3,105. Conversely, crashes in 65 mph zones decreased from 471 to 412. A notable change occurred in the 65 mph zone, which accounted for 8 fatalities in May 2015 but zero in May 2016. Meanwhile, fatal crashes increased in the 30 mph zone (from 0 to 4) and the 45 mph zone (from 2 to 5).
Fatal crashes by zone: 1 mph: 1 of 1,042 (0.096%) · 25 mph: 6 of 3,105 (0.193%) · 30 mph: 4 of 877 (0.456%) · 35 mph: 2 of 1,136 (0.176%) · 40 mph: 2 of 589 (0.34%) · 45 mph: 5 of 415 (1.205%) · 50 mph: 3 of 235 (1.277%) · 55 mph: 2 of 949 (0.211%) · 88 mph: 1 of 675 (0.148%)
Source: Connecticut Crash Data · Csv Open Data · 2016-05-01 to 2016-05-31 · 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: 2016-05-01 through 2016-05-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2016-05-01 through 2016-05-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,966
- Total persons involved: 25,206
- Total vehicles involved: 19,092
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: May 2016." Published August 20, 2026. Reporting period: 2016-05-01 to 2016-05-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/may-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: 2016-05-01 – 2016-05-31
Generated: August 20, 2026 · All rights reserved
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