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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · MAY 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/may-2019-report
Monthly Traffic Safety Analysis
9,766 CRASHES IN
CONNECTICUT, CT
MAY 2019
In May 2019, Connecticut recorded 9,766 total crashes, a slight decrease of 0.2% from the 9,785 crashes in May 2018. While overall crash volume remained stable, the number of fatalities saw a notable year-over-year decline. There were 20 fatalities in May 2019, a 23.1% reduction from the 26 fatalities recorded in the same month of the prior year.
9,766
▼ -0.2%was 9,785
Total Crash Events
20
▼ -23.1%was 26
Persons Killed
3,401
▲ 0.6%was 3,382
Persons Injured
1,090
▲ 4.8%was 1,040
Hit-and-Run Crashes
Note: "Persons Killed" (20) counts individual fatalities across all crash events. "Fatal" in the severity table below (20) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends remained relatively stable year-over-year, with total crashes decreasing by a marginal 0.2% from 9,785 in May 2018 to 9,766 in May 2019. Despite the stable crash volume, fatalities decreased by 23.1% (from 26 to 20), while total injuries saw a slight increase of 0.6% (from 3,382 to 3,401).
1,090
Hit-and-Run Crashes — May 2019
▲ 4.8% vs prior (1,040)
Hit-and-run incidents increased in both count and as a proportion of total crashes. There were 1,090 hit-and-run crashes in May 2019, a 4.8% increase from the 1,040 recorded in May 2018. Consequently, the hit-and-run rate rose from 10.6% of all crashes in the prior period to 11.2% in the current period.
Vulnerable Road User Casualties
6
Pedestrians Killed
1
Cyclists Killed
13
Motorists Killed
113
Pedestrians Injured
40
Cyclists Injured
3,248
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a shift between May 2018 and May 2019. The peak day for crashes moved from Thursday (1,701 crashes) in the prior year to Friday (1,814 crashes) in the current period. Similarly, the peak hour for collisions shifted an hour earlier, from 5 p.m. in 2018 (942 crashes) to 4 p.m. in 2019 (884 crashes).
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes shifted slightly year-over-year, with the proportion of fatal crashes decreasing from 0.3% to 0.2% of all incidents. Crashes resulting in serious injuries increased from 1.1% (108 incidents) of the total in May 2018 to 1.3% (124 incidents) in May 2019. Similarly, minor injury crashes grew from 9.5% to 9.9% of all collisions.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions remained broadly consistent year-over-year, with the majority of incidents in both periods occurring in clear weather and daylight. Daylight conditions were present in 80.6% of crashes in May 2019, compared to 81.1% in May 2018. There was a minor shift toward more crashes on wet roads, which accounted for 18.0% of incidents in May 2019 compared to 16.0% in the prior year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes remained consistent between May 2018 and May 2019, though their order shifted. Honda continued to be the most common make, with its involvement increasing from 1,853 to 2,007 vehicles. Toyota (1,834 vehicles) surpassed Ford (1,675 vehicles) to become the second-most frequent make involved in collisions. The age distribution of persons involved in crashes showed no significant changes year-over-year.
Top Vehicle Makes (18,808 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Vehicle unit records
1,556 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (23,577 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones saw some changes year-over-year. Crashes in 25 mph zones increased from 2,906 to 3,074, while incidents in 30 mph and 35 mph zones decreased. Notably, there were no fatal crashes reported in 55 mph zones in May 2019, compared to 4 in the same month of 2018. Conversely, crashes in 40 mph zones accounted for 4 fatalities in 2019, up from zero in the prior year.
Fatal crashes by zone: 1 mph: 1 of 1,191 (0.084%) · 25 mph: 2 of 3,074 (0.065%) · 30 mph: 4 of 795 (0.503%) · 35 mph: 3 of 1,075 (0.279%) · 40 mph: 4 of 532 (0.752%) · 45 mph: 2 of 339 (0.59%) · 50 mph: 1 of 279 (0.358%) · 65 mph: 2 of 499 (0.401%)
Source: Connecticut Crash Data · Csv Open Data · 2019-05-01 to 2019-05-31 · 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: 2019-05-01 through 2019-05-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2019-05-01 through 2019-05-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,766
- Total persons involved: 24,906
- Total vehicles involved: 18,808
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 2019." Published August 20, 2026. Reporting period: 2019-05-01 to 2019-05-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/may-2019-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: 2019-05-01 – 2019-05-31
Generated: August 20, 2026 · All rights reserved
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