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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · MAY 2023
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-2023-report
Monthly Traffic Safety Analysis
8,796 CRASHES IN
CONNECTICUT, CT
MAY 2023
In May 2023, Connecticut recorded 8,796 total vehicle crashes, a figure nearly identical to the 8,774 crashes documented in May 2022, representing a 0.25% year-over-year increase. Despite the stable crash volume, the state saw a significant positive development: total traffic fatalities fell by 21.6%, decreasing from 37 in the prior year's period to 29 in the current period. This reduction in fatalities occurred alongside a 5.5% drop in total injuries.
8,796
▲ 0.3%was 8,774
Total Crash Events
29
▼ -21.6%was 37
Persons Killed
2,964
▼ -5.5%was 3,135
Persons Injured
1,098
▼ -8.5%was 1,200
Hit-and-Run Crashes
Note: "Persons Killed" (29) 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 · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year, the total number of crashes in Connecticut remained stable, with an increase of just 22 incidents from 8,774 in May 2022 to 8,796 in May 2023. However, metrics of crash severity showed a notable improvement. Fatalities declined from 37 to 29, and total injuries decreased from 3,135 to 2,964, indicating a downward trend in the most severe outcomes despite a consistent overall crash frequency.
1,098
Hit-and-Run Crashes — May 2023
▼ -8.5% vs prior (1,200)
Hit-and-run incidents decreased in both volume and as a proportion of total crashes. In May 2023, there were 1,098 hit-and-run crashes, down from 1,200 in May 2022, representing an 8.5% reduction. The hit-and-run rate also fell, dropping from 13.7% of all crashes in the prior period to 12.5% in the current period, indicating a downward trend for this crash type.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
28
Motorists Killed
89
Pedestrians Injured
36
Cyclists Injured
2,839
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted slightly between the two periods. In May 2023, the peak day for crashes was Wednesday with 1,411 incidents, and the peak hour was 4 p.m. with 795 incidents. This contrasts with May 2022, when the peak day was Tuesday (1,431 crashes) and the peak hour was 3 p.m. (804 crashes). While weekday afternoons remain the highest-risk time, the specific peak day and hour both shifted from the prior year.
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Compared to the previous year, the severity of crashes in May 2023 trended downward. The number of fatal crashes decreased from 29 to 24, and the proportion of crashes resulting in possible injuries fell from 12.8% to 11.1%. Conversely, the share of non-injury crashes increased from 73.9% to 75.7%. However, the count of crashes involving serious injuries rose from 107 in May 2022 to 130 in May 2023, an increase from 1.2% to 1.5% of all crashes.
Severity is per crash event (most severe injury). 24 fatal crash events resulted in 29 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions appeared more favorable in May 2023 compared to the same month in 2022. The proportion of crashes occurring on dry roads increased from 85.1% to 92.4%, while collisions on wet roads decreased from 14.0% to 7.1% of the total. Similarly, crashes in the rain fell from 916 incidents to 475. The distribution of crashes by lighting conditions remained relatively stable, with daylight crashes accounting for 80.4% of incidents, up slightly from 78.3% the previous year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes—Honda, Toyota, Ford, Nissan, and Chevrolet—remained the same in both periods, indicating stable vehicle make demographics. However, the age distribution of persons involved in crashes shifted. The number of individuals aged 55-64 and 65+ involved in collisions increased from 2,317 to 2,493 and from 2,021 to 2,317, respectively. In contrast, involvement decreased among younger age groups, including the 16-20 and 35-44 brackets.
Top Vehicle Makes (16,801 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records
1,416 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,911 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones was mixed year-over-year. Collisions increased in 25 mph zones (from 2,556 to 2,619) and 40 mph zones (from 493 to 513), while decreasing in 45 mph zones (from 342 to 307). Notably, the location of fatal crashes shifted; fatal crashes in 40 mph zones doubled from 3 to 6, while those in 45 mph zones fell from 7 to 3. Fatal crashes in 25 mph zones also decreased from 6 to 3.
Fatal crashes by zone: 1 mph: 1 of 1,055 (0.095%) · 25 mph: 3 of 2,619 (0.115%) · 30 mph: 4 of 695 (0.576%) · 40 mph: 6 of 513 (1.17%) · 45 mph: 3 of 307 (0.977%) · 50 mph: 2 of 181 (1.105%) · 55 mph: 2 of 831 (0.241%) · 65 mph: 3 of 501 (0.599%)
Source: Connecticut Crash Data · Csv Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2023-05-01 through 2023-05-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,796
- Total persons involved: 21,399
- Total vehicles involved: 16,801
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 2023." Published August 20, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/may-2023-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: 2023-05-01 – 2023-05-31
Generated: August 20, 2026 · All rights reserved
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