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ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · OCTOBER 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/october-2023-report
Monthly Traffic Safety Analysis
9,351 CRASHES IN
CONNECTICUT, CT
OCTOBER 2023
In October 2023, Connecticut recorded 9,351 traffic crashes, a marginal 0.4% decrease from the 9,391 crashes in October 2022. While total crashes remained stable, the number of people injured rose by 3.0% and fatalities increased from 30 to 31. The most notable year-over-year shift was a significant increase in crashes involving vulnerable road users, with bicycle-involved crashes rising by 63.3% and motorcycle-involved crashes increasing by 21.5%.
9,351
▼ -0.4%was 9,391
Total Crash Events
31
▲ 3.3%was 30
Persons Killed
3,198
▲ 3.0%was 3,106
Persons Injured
1,092
▼ -2.7%was 1,122
Hit-and-Run Crashes
Note: "Persons Killed" (31) counts individual fatalities across all crash events. "Fatal" in the severity table below (28) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash volume in Connecticut was nearly stable, with a slight year-over-year decrease of 40 incidents, from 9,391 to 9,351. Despite this, the human cost of these crashes increased, as total injuries rose by 3.0% from 3,106 to 3,198, and fatalities ticked up from 30 to 31.
1,092
Hit-and-Run Crashes — October 2023
▼ -2.7% vs prior (1,122)
Hit-and-run crashes saw a minor decline in both count and rate. The number of hit-and-run incidents fell from 1,122 in October 2022 to 1,092 in October 2023. This resulted in a slight decrease in the overall hit-and-run rate, which dropped from 11.9% to 11.7% of all crashes.
Vulnerable Road User Casualties
8
Pedestrians Killed
1
Cyclists Killed
22
Motorists Killed
138
Pedestrians Injured
38
Cyclists Injured
3,022
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. The peak day for crashes moved from Saturday (1,548 crashes) in October 2022 to Tuesday (1,471 crashes) in October 2023. Concurrently, the peak hour for collisions moved slightly later in the afternoon, from the 3 p.m. hour in the prior period to the 4 p.m. hour in the current period. Saturday crashes saw a 21.6% decrease, while Sunday crashes increased by 22.2%.
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity of crashes remained consistent, with the fatal crash rate decreasing slightly from 0.32% to 0.30% of all incidents. There were 28 fatal crashes in October 2023, compared to 30 in the prior year, though the total number of people killed increased from 30 to 31. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) edged up slightly from 24.1% to 24.6% of all crashes.
Severity is per crash event (most severe injury). 28 fatal crash events resulted in 31 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record
Road & Environmental Conditions
A higher proportion of crashes in October 2023 occurred under favorable conditions compared to the previous year. Crashes on dry roads made up 82.6% of the total, an increase from 79.3% in October 2022, while crashes on wet surfaces decreased from 19.9% to 16.5% of the total. Similarly, the share of crashes happening in clear weather rose from 79.2% to 82.9%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field
Vehicles & Demographics
The top makes of vehicles involved in crashes were unchanged year-over-year, with Honda, Toyota, and Ford leading in both periods. The demographic profile of people involved in collisions also remained stable. The 26-34 age group was the most represented demographic in both October 2023 (3,737 people) and October 2022 (3,862 people), showing only a minor fluctuation.
Top Vehicle Makes (17,788 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records
1,451 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (21,177 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shifted slightly, with fewer incidents in 25 mph zones (2,645, down from 2,766) and 55 mph zones (860, down from 951). While total crashes in 65 mph zones increased from 540 to 560, the number of fatal crashes within these high-speed zones was halved, dropping from 6 to 3 year-over-year. Fatalities in 25 mph zones also decreased from 11 to 9.
Fatal crashes by zone: 1 mph: 1 of 1,195 (0.084%) · 25 mph: 9 of 2,645 (0.34%) · 30 mph: 2 of 680 (0.294%) · 35 mph: 3 of 1,093 (0.274%) · 40 mph: 6 of 568 (1.056%) · 45 mph: 2 of 321 (0.623%) · 50 mph: 1 of 279 (0.358%) · 55 mph: 1 of 860 (0.116%) · 65 mph: 3 of 560 (0.536%)
Source: Connecticut Crash Data · Csv Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2023-10-01 through 2023-10-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,351
- Total persons involved: 22,831
- Total vehicles involved: 17,788
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: October 2023." Published August 20, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/october-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: 2023-10-01 – 2023-10-31
Generated: August 20, 2026 · All rights reserved
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