ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SUNDERLAND, VT · 2024
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/vermont/sunderland/2024-annual-report
Yearly Traffic Safety Analysis
16 CRASHES IN
SUNDERLAND, VT
2024
Total crashes in Sunderland increased by 33.3% year-over-year, rising from 12 crashes in the prior year to 16 crashes in the current year. This period also saw a notable and concerning shift, with total fatalities increasing from 0 in the prior year to 1 in the current year. Total injuries also increased by 50%, from 4 to 6.
16
▲ 33.3%was 12
Total Crash Events
1
Fatal Crashes
6
▲ 50.0%was 4
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 data indicates an upward trend year-over-year, with total crashes increasing from 12 to 16, a 33.3% rise. This increase in frequency is accompanied by a significant rise in severity, as total fatalities increased from 0 to 1, and total injuries increased from 4 to 6.
When Crashes Happen
The temporal patterns of crashes shifted, with the peak day moving from Friday (5 crashes) in the prior year to Thursday (4 crashes) in the current year. The peak crash hour also changed, moving from 4 PM (2 crashes) in the prior year to 7 PM (3 crashes) in the current year. Additionally, crashes on Sundays increased from 0 to 3, while crashes on Saturdays decreased from 2 to 0.
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 severity distribution saw a significant change, with fatal crashes increasing from 0% in the prior year to 6.3% (1 crash) in the current year. Injury crashes increased proportionally from 33.3% (4 crashes) of all crashes in the prior year to 37.5% (6 crashes) in the current year. Conversely, crashes resulting in no injuries decreased proportionally from 66.7% to 56.3%.
Outcome by Severity (Crash Events)
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
Crashes occurring in dark lighting conditions saw a substantial increase, rising from 1 in the prior year to 6 in the current year. While dry road crashes increased from 6 to 10, crashes on wet roads decreased from 4 to 2. Freezing precipitation was a factor in 2 crashes in the prior year but was not present in the current year's data, which instead showed 1 crash in slush and 1 in standing water.
Weather
Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
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: Sunderland, VT
- Total crash records analyzed: 16
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). "Sunderland, 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/sunderland/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Vermont Crash Data · Arcgis
Period: 2024-01-01 – 2024-12-31
Generated: July 5, 2026 · All rights reserved