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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · 2019
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/2019-annual-report
Yearly Traffic Safety Analysis
3,710 CRASHES IN
CONNECTICUT, CT
2019
Total crashes in Middlesex County decreased from 3,908 in 2018 to 3,710 in 2019, a 5.1% reduction. While overall crashes, fatalities, and injuries declined, the most notable year-over-year shift was an increase in crashes involving vulnerable road users. Collisions involving bicyclists rose from 13 to 19, and pedestrian-involved crashes increased from 33 to 39, with each category recording one fatality in 2019 compared to zero in the prior year.
3,710
▼ -5.1%was 3,908
Total Crash Events
13
▼ -13.3%was 15
Persons Killed
1,172
▼ -2.7%was 1,204
Persons Injured
277
▼ -5.8%was 294
Hit-and-Run Crashes
Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (11) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Middlesex County showed improvement from 2018 to 2019. Total crashes declined by 5.1%, from 3,908 to 3,710. This downward trend was also reflected in key safety metrics, with total fatalities decreasing from 15 to 13 and total injuries falling from 1,204 to 1,172.
277
Hit-and-Run Crashes — 2019
▼ -5.8% vs prior (294)
The incidence of hit-and-run crashes showed a slight decrease in absolute numbers, falling from 294 in 2018 to 277 in 2019. However, as a proportion of total crashes, the hit-and-run rate remained unchanged. In both 2019 and the prior year, hit-and-run incidents accounted for 7.5% of all reported collisions.
Vulnerable Road User Casualties
1
Pedestrians Killed
1
Cyclists Killed
11
Motorists Killed
0
Other Killed
31
Pedestrians Injured
17
Cyclists Injured
1,122
Motorists Injured
2
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · 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 largely consistent year-over-year. Friday was the peak day for crashes in both 2019 (676 crashes) and 2018 (628 crashes). The afternoon commute remains the most hazardous time, though the peak hour shifted slightly earlier from 4 p.m. in 2018 (353 crashes) to 3 p.m. in 2019 (347 crashes).
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed minor changes between the two periods. The fatal crash rate saw a slight improvement, decreasing from 0.33% of all crashes in 2018 to 0.30% in 2019. The proportion of crashes resulting in no injuries decreased from 77.1% to 76.3%, while minor injury crashes increased slightly from 10.6% to 11.2% of the total.
Severity is per crash event (most severe injury). 11 fatal crash events resulted in 13 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Most severe injury per crash record
Road & Environmental Conditions
The environmental conditions under which crashes occurred were very similar in both years. The vast majority of collisions in both 2019 and 2018 happened in clear weather (78.0% and 78.5%) and on dry roads (76.7% and 76.6%). A notable change was a reduction in crashes during snowy conditions, which fell from 122 incidents in 2018 to 64 in 2019.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes were consistent, with Toyota and Ford leading in both 2019 (696 and 681 vehicles, respectively) and 2018 (732 and 744 vehicles). A demographic analysis of persons involved in crashes reveals a slight shift in age distribution. The proportion of individuals aged 65 and older increased from 11.6% of all persons involved in 2018 to 12.7% in 2019.
Top Vehicle Makes (6,675 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Vehicle unit records
487 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (8,094 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a discernible shift in crashes toward higher speed zones in 2019 compared to the prior year. Crashes in zones posted at 45 mph or less decreased, while collisions in zones of 50 mph or higher increased from 614 to 655. The 65 mph speed zone, in particular, saw an increase from 560 crashes in 2018 to 594 in 2019, and it accounted for 4 of the 11 fatal crashes in the current period.
Fatal crashes by zone: 30 mph: 1 of 302 (0.331%) · 35 mph: 1 of 605 (0.165%) · 40 mph: 2 of 389 (0.514%) · 45 mph: 2 of 302 (0.662%) · 50 mph: 1 of 32 (3.125%) · 65 mph: 4 of 594 (0.673%)
Source: Connecticut Crash Data · Csv Open Data · 2019-01-01 to 2019-12-31 · 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: 2019-01-01 through 2019-12-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2019-01-01 through 2019-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 3,710
- Total persons involved: 8,540
- Total vehicles involved: 6,675
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: 2019." Published August 20, 2026. Reporting period: 2019-01-01 to 2019-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2019-annual-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: 2019-01-01 – 2019-12-31
Generated: August 20, 2026 · All rights reserved
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