Yearly Traffic Safety Analysis

26 CRASHES IN
GEORGIA, VT
2024

All metrics benchmarked against2023

Total crashes remained stable year-over-year, with 26 crashes recorded in both 2024 and 2023. Despite the stable overall crash count, total injuries increased by 75%, rising from 8 in 2023 to 14 in 2024. DUI-related crashes also saw a significant increase, more than doubling from 1 in 2023 to 3 in 2024.

26

Total Crash Events

1

Fatal Crashes

14

75.0%was 8

Injury Crashes

1

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons.

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash numbers remained stable year-over-year, with 26 crashes reported in both 2024 and 2023, indicating no change in the total volume of incidents. Fatalities also remained consistent at 1 in both periods. However, total injuries increased substantially by 75%, rising from 8 injuries in 2023 to 14 injuries in 2024.

When Crashes Happen

The temporal patterns for crashes shifted between the two periods. In 2024, the peak day for crashes was Sunday with 6 incidents, a change from 2023 where Thursday was the peak day with 7 incidents. The peak hour also changed, moving from 7 AM with 5 crashes in 2023 to 5 PM with 5 crashes in 2024.

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity showed notable changes year-over-year. While fatal crashes remained constant at 1 in both 2023 and 2024, the number of injury crashes increased by 75%, from 8 in 2023 to 14 in 2024. Consequently, the proportion of injury crashes rose from 30.8% of all crashes in 2023 to 53.8% in 2024, while crashes with no injuries decreased from 65.4% to 42.3%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3.8%
0.0%prior 1
Injury14minor injury crashes53.8%
75.0%prior 8
No Injury11no injury crashes42.3%
-35.3%prior 17

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Analysis of crash conditions reveals shifts in weather and lighting. Crashes occurring in clear weather increased by 50%, from 8 in 2023 to 12 in 2024, while those in freezing precipitation decreased by 60%, from 5 to 2. Crashes during daylight hours increased from 18 to 21, and crashes in dark conditions decreased by 37.5%, from 8 to 5. The number of crashes on dry road surfaces increased by 41.7%, from 12 to 17.

Weather

Clear12 (54.5%)
50.0%prior 8
Cloudy6 (27.3%)
Freezing Precipitation2 (9.1%)
-60.0%prior 5
Rain2 (9.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight21 (80.8%)
16.7%prior 18
Dark5 (19.2%)
-37.5%prior 8

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry17 (68.0%)
41.7%prior 12
Snow3 (12.0%)
Wet3 (12.0%)
Other - Explain in Narrative1 (4.0%)
Water (standing / moving)1 (4.0%)

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Vermont Crash Data, accessed programmatically via the Arcgis 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: Arcgis 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: 2024-01-01 through 2024-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: Georgia, VT
  • Total crash records analyzed: 26

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). "Georgia, VT Crash Intelligence Report: 2024." Published July 5, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/georgia/2024-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

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Georgia, VT Crash Report — 2024 | ThatCarHitMe.com