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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · MAY 2020
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-2020-report
Monthly Traffic Safety Analysis
5,222 CRASHES IN
CONNECTICUT, CT
MAY 2020
In May 2020, Connecticut recorded 5,222 traffic crashes, a 46.5% decrease from the 9,766 crashes reported in May 2019. Despite this substantial drop in collisions, the number of fatalities remained unchanged at 20 for both periods. The most notable year-over-year shift was the doubling of the fatal crash rate, which increased from 0.2% to 0.4% of all crashes.
5,222
▼ -46.5%was 9,766
Total Crash Events
20
Persons Killed
1,940
▼ -43.0%was 3,401
Persons Injured
852
▼ -21.8%was 1,090
Hit-and-Run Crashes
Note: "Persons Killed" (20) counts individual fatalities across all crash events. "Fatal" in the severity table below (21) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends showed a significant year-over-year improvement in the volume of incidents, but not in their severity. Total crashes fell by 4,544 (a 46.5% reduction) and total injuries decreased by 1,461 (a 43.0% reduction). However, the number of traffic fatalities held steady at 20, indicating that the crashes that did occur were more likely to be deadly.
852
Hit-and-Run Crashes — May 2020
▼ -21.8% vs prior (1,090)
While the total number of hit-and-run crashes decreased from 1,090 in May 2019 to 852 in May 2020, the hit-and-run rate trended upward significantly. Hit-and-run incidents accounted for 16.3% of all crashes in May 2020, a notable increase from the 11.2% rate recorded in the same month of the previous year. This indicates that a larger proportion of crashes involved a driver leaving the scene.
Vulnerable Road User Casualties
2
Pedestrians Killed
2
Cyclists Killed
16
Motorists Killed
0
Other Killed
59
Pedestrians Injured
35
Cyclists Injured
1,845
Motorists Injured
1
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained consistent despite a large decrease in overall volume. Friday was the peak day for crashes in both May 2020 (1,022 crashes) and May 2019 (1,814 crashes). Similarly, the 4 p.m. hour was the peak time for collisions in both periods, accounting for 477 crashes in the current period and 884 in the prior year. The timing of when crashes were most frequent did not shift year-over-year.
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes worsened in May 2020 compared to the previous year. The fatal crash rate doubled from 0.2% to 0.4%, as the number of fatal incidents rose from 20 to 21 despite far fewer total crashes. The proportion of crashes involving serious injuries also increased from 1.3% to 1.7%, and minor injury crashes grew from 9.9% to 12.1% of all incidents. Consequently, the share of non-injury crashes decreased from 74.5% to 73.0%.
Severity is per crash event (most severe injury). 21 fatal crash events resulted in 20 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Most severe injury per crash record
Road & Environmental Conditions
The vast majority of crashes in both periods occurred in clear weather and daylight on dry roads. Year-over-year, there was a slight shift toward a higher proportion of crashes happening in clear weather, which accounted for 85.7% of incidents in May 2020 versus 76.6% in May 2019. Crashes on wet roads became less frequent, making up 11.3% of the total compared to 18.0% in the prior year. The proportion of crashes in daylight conditions saw a small decrease from 80.6% to 77.1%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained largely the same, with Honda, Ford, and Toyota leading in both periods, although the total number of vehicles involved fell from 18,808 to 9,635. The age distribution of persons involved in crashes also showed little change. The 26-34 age group was the largest cohort in both years, representing a slightly increased share of 18.2% of all individuals in May 2020 compared to 16.8% in May 2019.
Top Vehicle Makes (9,635 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Vehicle unit records
1,064 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (11,225 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes decreased across all speed zones, with the 25 mph zone remaining the most common location for collisions in both periods (1,836 in May 2020 vs. 3,074 in May 2019). However, the distribution of fatal crashes shifted, with the fatal crash rate increasing in higher speed zones. The fatal crash rate in the 35 mph zone increased from 0.28% to 1.22%, and the rate in the 65 mph zone rose from 0.40% to 1.34% year-over-year.
Fatal crashes by zone: 25 mph: 3 of 1,836 (0.163%) · 30 mph: 3 of 421 (0.713%) · 35 mph: 7 of 572 (1.224%) · 45 mph: 1 of 205 (0.488%) · 55 mph: 2 of 263 (0.76%) · 65 mph: 3 of 224 (1.339%) · 88 mph: 1 of 357 (0.28%)
Source: Connecticut Crash Data · Csv Open Data · 2020-05-01 to 2020-05-31 · 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: 2020-05-01 through 2020-05-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2020-05-01 through 2020-05-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 5,222
- Total persons involved: 12,167
- Total vehicles involved: 9,635
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 2020." Published August 20, 2026. Reporting period: 2020-05-01 to 2020-05-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/may-2020-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: 2020-05-01 – 2020-05-31
Generated: August 20, 2026 · All rights reserved
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